https://ckg.semanticclimate.org/api.php?action=feedcontributions&feedformat=atom&user=Design 2026-10-22T13:48:08Z User contributions MediaWiki 1.45.1 https://ckg.semanticclimate.org/index.php?title=Template:GlossaryTerms&diff=1297 2026-05-20T12:08:24Z

<p>Design: </p> <hr /> <div>&lt;div class=&quot;glossary-terms-box&quot;&gt;<br /> &lt;div class=&quot;glossary-terms-title&quot;&gt;Glossary terms in this report&lt;/div&gt;<br /> &lt;div class=&quot;glossary-terms-pills&quot;&gt;<br /> [[IPCC:AR6/Glossary#Ablation|Ablation]]<br /> [[IPCC:AR6/Glossary#Aerosol|Aerosol]]<br /> [[IPCC:AR6/Glossary#Albedo|Albedo]]<br /> [[IPCC:AR6/Glossary#Anthropogenic|Anthropogenic]]<br /> [[IPCC:AR6/Glossary#Biosphere|Biosphere]]<br /> [[IPCC:AR6/Glossary#Carbon_cycle|Carbon cycle]]<br /> [[IPCC:AR6/Glossary#Climate_feedback|Climate feedback]]<br /> [[IPCC:AR6/Glossary#Cryosphere|Cryosphere]]<br /> [[IPCC:AR6/Glossary#Ecosystem|Ecosystem]]<br /> [[IPCC:AR6/Glossary#Emission|Emission]]<br /> [[IPCC:AR6/Glossary#Forcing|Forcing]]<br /> [[IPCC:AR6/Glossary#Greenhouse_gas|Greenhouse gas]]<br /> [[IPCC:AR6/Glossary#Mitigation|Mitigation]]<br /> [[IPCC:AR6/Glossary#Scenario|Scenario]]<br /> &lt;/div&gt;<br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Tables&diff=1291 2026-05-06T12:38:12Z

<p>Design: /* Testing table and table caption display */</p> <hr /> <div>= Testing table and table caption display =<br /> == Was ==<br /> ====== Table 4.1 ======<br /> <br /> Sectoral indicators of the pace of transformation in 1.5°C-consistent pathways, based on selected integrated pathways assessed in Chapter 2 (from the scenario database) and several other studies reviewed in Chapter 2 that assess mitigation transitions consistent with limiting warming to 1.5°C. Values for ‘1.5°C-no or -low-OS’’ indicate the median and the interquartile ranges for 1.5°C scenarios. If a number in square brackets is indicated, this is the number of scenarios for this indicator. S1, S2, S5 and LED represent the four illustrative pathway archetypes selected for this assessment (see Chapter 2, Section 2.1 and Supplementary Material 4.SM.1 for detailed description).<br /> <br /> {| class=&quot;wikitable&quot;<br /> |-<br /> ! rowspan=&quot;2&quot; colspan=&quot;2&quot;| Pathways<br /> ! rowspan=&quot;2&quot;| Number&lt;br /&gt;<br /> of scenarios<br /> ! colspan=&quot;2&quot;| Energy<br /> ! Buildings<br /> ! colspan=&quot;2&quot;| Transport<br /> ! Industry<br /> |}<br /> <br /> == Should be ==<br /> {| class=&quot;wikitable&quot;<br /> |+ Table Title<br /> |-<br /> ! Header 1 !! Header 2<br /> |-<br /> | Data 1 || Data 2<br /> |}</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Tables&diff=1290 2026-05-06T12:35:29Z

<p>Design: Created page with &quot;= Testing table and table caption display = == Was == ====== Table 4.1 ====== Sectoral indicators of the pace of transformation in 1.5°C-consistent pathways, based on selected integrated pathways assessed in Chapter 2 (from the scenario database) and several other studies reviewed in Chapter 2 that assess mitigation transitions consistent with limiting warming to 1.5°C. Values for ‘1.5°C-no or -low-OS’’ indicate the median and the interquartile ranges for 1.5°...&quot;</p> <hr /> <div>= Testing table and table caption display =<br /> == Was ==<br /> ====== Table 4.1 ======<br /> <br /> Sectoral indicators of the pace of transformation in 1.5°C-consistent pathways, based on selected integrated pathways assessed in Chapter 2 (from the scenario database) and several other studies reviewed in Chapter 2 that assess mitigation transitions consistent with limiting warming to 1.5°C. Values for ‘1.5°C-no or -low-OS’’ indicate the median and the interquartile ranges for 1.5°C scenarios. If a number in square brackets is indicated, this is the number of scenarios for this indicator. S1, S2, S5 and LED represent the four illustrative pathway archetypes selected for this assessment (see Chapter 2, Section 2.1 and Supplementary Material 4.SM.1 for detailed description).<br /> <br /> {| class=&quot;wikitable&quot;<br /> |-<br /> ! rowspan=&quot;2&quot; colspan=&quot;2&quot;| Pathways<br /> ! rowspan=&quot;2&quot;| Number&lt;br /&gt;<br /> of scenarios<br /> ! colspan=&quot;2&quot;| Energy<br /> ! Buildings<br /> ! colspan=&quot;2&quot;| Transport<br /> ! Industry<br /> |}</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1289 2026-05-06T12:12:19Z

<p>Design: /* Testing image and image caption display */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> &lt;figure&gt;<br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|upright]]<br /> <br /> &lt;figcaption&gt;<br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> &lt;/figcaption&gt;<br /> &lt;/figure&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1288 2026-05-06T12:10:54Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;figure&gt;<br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|upright]]<br /> <br /> &lt;figcaption&gt;'''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.&lt;/figcaption&gt;<br /> &lt;/figure&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1287 2026-05-06T12:08:53Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|800px|This is the caption]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1286 2026-05-06T12:08:41Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|class=mw-100|This is the caption]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1285 2026-05-06T12:08:17Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|800px|This is the caption]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=MediaWiki:Common.css&diff=1284 2026-05-06T12:08:04Z

<p>Design: </p> <hr /> <div>/* Design Styling ***************************************** */<br /> <br /> /* Glossary styling for MediaWiki */<br /> <br /> .glossary-letter-section {<br /> border-left: 5px solid #2b3990;<br /> padding-left: 16px;<br /> margin: 0 0 24px 0;<br /> }<br /> <br /> .glossary-letter-section h2 {<br /> font-size: 18px;<br /> font-weight: 500;<br /> color: #2b3990;<br /> margin: 0 0 16px 0;<br /> letter-spacing: 1px;<br /> }<br /> <br /> .glossary-entry {<br /> background: #ffffff;<br /> border: 0.5px solid #d3d1c7;<br /> border-radius: 12px;<br /> padding: 12px 16px;<br /> margin-bottom: 12px;<br /> }<br /> <br /> .glossary-entry h3 {<br /> margin: 0 0 8px 0;<br /> font-size: 16px;<br /> font-weight: 500;<br /> }<br /> <br /> .glossary-term {<br /> color: #1600ff;<br /> font-weight: 500;<br /> }<br /> <br /> .glossary-working-groups,<br /> .glossary-longer-term,<br /> .glossary-definition {<br /> font-size: 13px;<br /> line-height: 1.6;<br /> margin: 6px 0;<br 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.acronyms-description strong,<br /> .acronyms-report strong {<br /> color: #00aeef;<br /> font-weight: 500;<br /> }<br /> <br /> .acronyms-report strong {<br /> color: #b3b3b3;<br /> }<br /> <br /> /* Dark mode support (adjust as needed for your MediaWiki theme) */<br /> @media (prefers-color-scheme: dark) {<br /> .acronyms-letter-section {<br /> border-left-color: #00d9ff;<br /> }<br /> <br /> .acronyms-letter-section h2 {<br /> color: #7fb3ff;<br /> }<br /> <br /> .acronyms-entry {<br /> background: #1a1a1a;<br /> border-color: #444441;<br /> }<br /> <br /> .acronyms-term {<br /> color: #5eb3ff;<br /> }<br /> <br /> .acronyms-description,<br /> .acronyms-report {<br /> color: #f0f0f0;<br /> }<br /> <br /> .acronyms-report {<br /> color: #888888;<br /> }<br /> <br /> .acronyms-description strong,<br /> .acronyms-report strong {<br /> color: #00d9ff;<br /> font-weight: 500;<br /> }<br /> <br /> .acronyms-report strong {<br /> color: #888888;<br /> }<br /> }<br /> <br /> <br /> <br /> /* Breadcrumbs ************************** */<br /> <br /> /* Force breadcrumbs to single line */<br /> #mw-content-subtitle {<br /> white-space: nowrap;<br /> }<br /> <br /> #mw-content-subtitle .subpages {<br /> display: inline;<br /> }<br /> <br /> #mw-content-subtitle .breadcrumb-separator {<br /> display: inline;<br /> }<br /> <br /> #mw-content-subtitle .breadcrumb-current {<br /> display: inline;<br /> }<br /> <br /> <br /> /* BtnNeutral Button Template - Design Option 4 */<br /> .btn-neutral {<br /> /* Color scheme - Outline style */<br /> background-color: transparent;<br /> color: #00aeef; /* Cyan text */<br /> border: 3px solid #00aeef; /* Cyan border */<br /> <br /> /* Typography */<br /> font-size: 18px;<br /> font-weight: 600;<br /> font-family: inherit;<br /> line-height: 1;<br /> <br /> /* Sizing &amp; spacing */<br /> padding: 14px 30px;<br /> min-height: 50px;<br /> display: inline-flex;<br /> align-items: center;<br /> justify-content: center;<br /> <br /> /* Appearance */<br /> border-radius: 8px;<br /> text-align: center;<br /> white-space: nowrap;<br /> cursor: pointer;<br /> <br /> /* Effects */<br /> transition: all 0.2s ease;<br /> text-decoration: none;<br /> }<br /> <br /> /* Link styling inside button */<br /> .btn-neutral a {<br /> color: #00aeef;<br /> text-decoration: none;<br /> cursor: pointer;<br /> }<br /> <br /> /* Hover state - fill with cyan background */<br /> .btn-neutral:hover {<br /> background-color: #00aeef;<br /> color: #030001; /* Black text on cyan bg */<br /> box-shadow: 0 4px 12px rgba(0, 174, 239, 0.3);<br /> transform: translateY(-2px);<br /> }<br /> <br /> .btn-neutral:hover a {<br /> color: #030001;<br /> }<br /> <br /> /* Make link fill entire button */<br /> .btn-neutral a {<br /> color: #00aeef;<br /> text-decoration: none;<br /> cursor: pointer;<br /> display: flex;<br /> align-items: center;<br /> justify-content: center;<br /> }<br /> <br /> /* Active/pressed state */<br /> .btn-neutral:active {<br /> background-color: #00aeef;<br /> color: #030001;<br /> border-color: #2b3990; /* Navy border on active */<br /> transform: scale(0.98);<br /> box-shadow: 0 2px 6px rgba(0, 174, 239, 0.4);<br /> }<br /> <br /> .btn-neutral:active a {<br /> color: #030001;<br /> }<br /> <br /> /* Focus state for accessibility */<br /> .btn-neutral:focus-within {<br /> outline: 2px solid #2b3990;<br /> outline-offset: 2px;<br /> }<br /> <br /> /* Disabled state */<br /> .btn-neutral.disabled {<br /> opacity: 0.6;<br /> cursor: not-allowed;<br /> border-color: #b3b3b3; /* Grey border when disabled */<br /> color: #b3b3b3; /* Grey text when disabled */<br /> }<br /> <br /> .btn-neutral.disabled a {<br /> color: #b3b3b3;<br /> pointer-events: none;<br /> }<br /> <br /> /* Template Styling ***************************************** */<br /> <br /> <br /> /* Acronym terms ***************************************** */<br /> .acronym-terms-box {<br /> background: #ffffff;<br /> border: 0.5px solid #d3d1c7;<br /> border-radius: 12px;<br /> padding: 1.25rem;<br /> margin: 1rem 0;<br /> }<br /> <br /> .acronym-terms-title {<br /> font-size: 16px;<br /> font-weight: 500;<br /> color: #2b3990;<br /> margin-bottom: 1rem;<br /> }<br /> <br /> .acronym-terms-pills {<br /> display: flex;<br /> flex-wrap: wrap;<br /> gap: 8px;<br /> row-gap: 16px;<br /> margin-bottom: -4px;<br /> }<br /> <br /> .acronym-terms-pills a {<br /> display: inline-block;<br /> background: #feff03;<br /> color: #2b3990;<br /> padding: 5px 10px;<br /> border-radius: 16px;<br /> font-size: 12px;<br /> font-weight: 500;<br /> text-decoration: none;<br /> transition: background-color 0.2s;<br /> margin-bottom: 4px;<br /> font-family: monospace;<br /> }<br /> <br /> .acronym-terms-pills a:hover {<br /> background: #ffff33;<br /> text-decoration: none;<br /> }<br /> <br /> /* Dark mode support */<br /> @media (prefers-color-scheme: dark) {<br /> .acronym-terms-box {<br /> background: #1a1a1a;<br /> border-color: #444441;<br /> }<br /> <br /> .acronym-terms-title {<br /> color: #7fb3ff;<br /> }<br /> <br /> .acronym-terms-pills a {<br /> background: #feff03;<br /> color: #030001;<br /> }<br /> <br /> .acronym-terms-pills a:hover {<br /> background: #ffff33;<br /> }<br /> }<br /> <br /> <br /> /* Glossary terms ***************************************** */<br /> .glossary-terms-box {<br /> background: #ffffff;<br /> border: 0.5px solid #d3d1c7;<br /> border-radius: 12px;<br /> padding: 1.25rem;<br /> margin: 1rem 0;<br /> }<br /> <br /> .glossary-terms-title {<br /> font-size: 16px;<br /> font-weight: 500;<br /> color: #2b3990;<br /> margin-bottom: 1rem;<br /> }<br /> <br /> .glossary-terms-pills {<br /> display: flex;<br /> flex-wrap: wrap;<br /> gap: 8px;<br /> row-gap: 16px;<br /> margin-bottom: -4px;<br /> }<br /> <br /> .glossary-terms-pills a {<br /> display: inline-block;<br /> background: #00aeef;<br /> color: #030001;<br /> padding: 6px 12px;<br /> border-radius: 20px;<br /> font-size: 13px;<br /> font-weight: 500;<br /> text-decoration: none;<br /> transition: background-color 0.2s;<br /> margin-bottom: 4px;<br /> }<br /> <br /> .glossary-terms-pills a:hover {<br /> background: #0098d0;<br /> text-decoration: none;<br /> }<br /> <br /> /* Dark mode support */<br /> @media (prefers-color-scheme: dark) {<br /> .glossary-terms-box {<br /> background: #1a1a1a;<br /> border-color: #444441;<br /> }<br /> <br /> .glossary-terms-title {<br /> color: #7fb3ff;<br /> }<br /> <br /> .glossary-terms-pills a {<br /> background: #00d9ff;<br /> color: #030001;<br /> }<br /> <br /> .glossary-terms-pills a:hover {<br /> background: #00b8d9;<br /> }<br /> }<br /> <br /> /* AR6 Templates ***************************************** */<br /> <br /> /* AR6Covers */<br /> .ar6-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-radius: 4px;<br /> background: #f9f9f7;<br /> font-family: sans-serif;<br /> padding: 12px 14px;<br /> box-sizing: border-box;<br /> margin: 0 0 1.5em 0;<br /> }<br /> .ar6-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 10px;<br /> }<br /> .ar6-labels {<br /> display: grid;<br /> grid-template-columns: 1fr 21px 3fr 21px 3fr;<br /> margin-bottom: 6px;<br /> }<br /> .ar6-group-label {<br /> color: #b3b3b3;<br /> font-size: 9px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> text-align: center;<br /> }<br /> .ar6-grid {<br /> display: grid;<br /> grid-template-columns: 1fr 21px 1fr 1fr 1fr 21px 1fr 1fr 1fr;<br /> align-items: end;<br /> }<br /> .ar6-cover {<br /> display: flex;<br /> flex-direction: column;<br /> align-items: center;<br /> gap: 6px;<br /> padding: 0 3px;<br /> }<br /> .ar6-cover img {<br /> width: 100%;<br /> height: auto;<br /> aspect-ratio: 3/4;<br /> border: 1px solid #d0d0d0;<br /> border-radius: 2px;<br /> display: block;<br /> object-fit: cover;<br /> }<br /> .ar6-cover:hover img {<br /> border-color: #00aeef;<br /> }<br /> .ar6-label {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> font-weight: 500;<br /> text-align: center;<br /> }<br /> .ar6-cover:hover .ar6-label {<br /> color: #2b3990;<br /> }<br /> .ar6-divider-col {<br /> width: 1px;<br /> background: #e0e0e0;<br /> align-self: stretch;<br /> margin: 0 10px;<br /> }<br /> <br /> /* Active state — dim all covers, then highlight the active one */<br /> .ar6-active-syr .ar6-cover,<br /> .ar6-active-wgi .ar6-cover,<br /> .ar6-active-wgii .ar6-cover,<br /> .ar6-active-wgiii .ar6-cover,<br /> .ar6-active-sr15 .ar6-cover,<br /> .ar6-active-srccl .ar6-cover,<br /> .ar6-active-srocc .ar6-cover {<br /> opacity: 0.4;<br /> transition: opacity 0.15s;<br /> }<br /> .ar6-active-syr .ar6-cover:hover,<br /> .ar6-active-wgi .ar6-cover:hover,<br /> .ar6-active-wgii .ar6-cover:hover,<br /> .ar6-active-wgiii .ar6-cover:hover,<br /> .ar6-active-sr15 .ar6-cover:hover,<br /> .ar6-active-srccl .ar6-cover:hover,<br /> .ar6-active-srocc .ar6-cover:hover {<br /> opacity: 1;<br /> }<br /> .ar6-active-syr .ar6-syr,<br /> .ar6-active-wgi .ar6-wgi,<br /> .ar6-active-wgii .ar6-wgii,<br /> .ar6-active-wgiii .ar6-wgiii,<br /> .ar6-active-sr15 .ar6-sr15,<br /> .ar6-active-srccl .ar6-srccl,<br /> .ar6-active-srocc .ar6-srocc {<br /> opacity: 1;<br /> }<br /> .ar6-active-syr .ar6-syr img,<br /> .ar6-active-wgi .ar6-wgi img,<br /> .ar6-active-wgii .ar6-wgii img,<br /> .ar6-active-wgiii .ar6-wgiii img,<br /> .ar6-active-sr15 .ar6-sr15 img,<br /> .ar6-active-srccl .ar6-srccl img,<br /> .ar6-active-srocc .ar6-srocc img {<br /> border: 2px solid #00aeef;<br /> border-radius: 3px;<br /> }<br /> .ar6-active-syr .ar6-syr .ar6-label,<br /> .ar6-active-wgi .ar6-wgi .ar6-label,<br /> .ar6-active-wgii .ar6-wgii .ar6-label,<br /> .ar6-active-wgiii .ar6-wgiii .ar6-label,<br /> .ar6-active-sr15 .ar6-sr15 .ar6-label,<br /> .ar6-active-srccl .ar6-srccl .ar6-label,<br /> .ar6-active-srocc .ar6-srocc .ar6-label {<br /> color: #2b3990;<br /> }<br /> <br /> /* When active=none or parameter omitted — no dimming */<br /> .ar6-active-none .ar6-cover {<br /> opacity: 1;<br /> }<br /> <br /> /* AR6Report */<br /> .ar6r-card {<br /> width: 100%;<br /> border: 1px solid #00aeef;<br /> border-radius: 4px;<br /> overflow: hidden;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> background: #ffffff;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> display: flex;<br /> }<br /> .ar6r-img {<br /> width: 180px;<br /> min-width: 180px;<br /> background: #1e2a70;<br /> display: flex;<br /> align-items: center;<br /> justify-content: center;<br /> padding: 16px;<br /> border-right: 1px solid #00aeef;<br /> flex-shrink: 0;<br /> }<br /> .ar6r-img img {<br /> width: 100%;<br /> height: auto;<br /> display: block;<br /> border-radius: 2px;<br /> }<br /> .ar6r-img .thumbinner,<br /> .ar6r-img .thumbimage {<br /> width: 100% !important;<br /> margin: 0 !important;<br /> border: none !important;<br /> background: none !important;<br /> }<br /> .ar6r-right {<br /> flex: 1;<br /> display: flex;<br /> flex-direction: column;<br /> }<br /> .ar6r-header {<br /> background: #2b3990;<br /> padding: 14px 16px;<br /> }<br /> .ar6r-tag {<br /> color: #00aeef;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 4px;<br /> }<br /> .ar6r-title {<br /> color: #ffffff;<br /> font-size: 16px;<br /> font-weight: 500;<br /> line-height: 1.3;<br /> margin-bottom: 4px;<br /> }<br /> .ar6r-subtitle {<br /> color: #9aaee8;<br /> font-size: 12px;<br /> line-height: 1.4;<br /> }<br /> .ar6r-synopsis {<br /> color: #030001;<br /> font-size: 12px;<br /> line-height: 1.6;<br /> padding: 10px 16px;<br /> border-bottom: 1px solid #f0f0f0;<br /> flex: 1;<br /> }<br /> .ar6r-meta {<br /> display: grid;<br /> grid-template-columns: 1fr 1fr 1fr;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .ar6r-meta-field {<br /> padding: 6px 16px;<br /> border-right: 1px solid #f0f0f0;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .ar6r-meta-field:nth-child(3n) {<br /> border-right: none;<br /> }<br /> .ar6r-meta-lbl {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> display: block;<br /> margin-bottom: 2px;<br /> }<br /> .ar6r-meta-val {<br /> color: #030001;<br /> font-size: 12px;<br /> }<br /> .ar6r-meta-val a {<br /> color: #00aeef;<br /> text-decoration: none;<br /> word-break: break-all;<br /> }<br /> .ar6r-meta-val a:hover {<br /> text-decoration: underline;<br /> }<br /> .ar6r-topics {<br /> padding: 8px 16px;<br /> border-bottom: 1px solid #f0f0f0;<br /> display: flex;<br /> flex-wrap: wrap;<br /> gap: 6px;<br /> align-items: center;<br /> }<br /> .ar6r-topics-lbl {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> margin-right: 4px;<br /> flex-shrink: 0;<br /> }<br /> .ar6r-topic {<br /> background: #f5f7ff;<br /> border: 1px solid #2b3990;<br /> border-radius: 20px;<br /> color: #2b3990;<br /> font-size: 10px;<br /> padding: 3px 10px;<br /> }<br /> .ar6r-btn-wrap {<br /> display: block;<br /> background: #2b3990;<br /> }<br /> .ar6r-btn-wrap a {<br /> display: block;<br /> color: #feff03;<br /> text-align: center;<br /> padding: 11px;<br /> font-size: 13px;<br /> font-weight: 500;<br /> letter-spacing: 0.02em;<br /> text-decoration: none;<br /> }<br /> .ar6r-btn-wrap a:hover {<br /> background: #1e2a70;<br /> }<br /> .ar6r-btn-wrap a::after {<br /> display: none;<br /> }<br /> <br /> <br /> /* Report Templates ***************************************** */<br /> <br /> /* ReportHeader */<br /> .rh-banner {<br /> width: 100%;<br /> border: 1px solid #00aeef;<br /> border-radius: 4px;<br /> overflow: hidden;<br /> background: #2b3990;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> margin: 0 0 1.5em 0;<br /> }<br /> .rh-banner-top {<br /> display: flex;<br /> align-items: stretch;<br /> }<br /> .rh-banner-img {<br /> width: 160px;<br /> min-width: 160px;<br /> background: #1e2a70;<br /> display: flex;<br /> align-items: center;<br /> justify-content: center;<br /> padding: 12px;<br /> border-right: 1px solid #1a2260;<br /> }<br /> .rh-banner-img img {<br /> width: 100%;<br /> height: auto;<br /> display: block;<br /> border-radius: 2px;<br /> }<br /> .rh-banner-right {<br /> flex: 1;<br /> display: flex;<br /> flex-direction: column;<br /> }<br /> .rh-banner-titles {<br /> padding: 12px 14px 10px;<br /> flex: 1;<br /> }<br /> .rh-banner-tag {<br /> color: #feff03;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 4px;<br /> }<br /> .rh-banner-title {<br /> color: #ffffff;<br /> font-size: 14px;<br /> font-weight: 500;<br /> line-height: 1.35;<br /> margin-bottom: 3px;<br /> }<br /> .rh-banner-subtitle {<br /> color: #00aeef;<br /> font-size: 12px;<br /> font-weight: 500;<br /> line-height: 1.4;<br /> margin-bottom: 8px;<br /> }<br /> .rh-banner-abstract-text {<br /> color: #b3d4f0;<br /> font-size: 11px;<br /> line-height: 1.6;<br /> border-top: 1px solid #1a2260;<br /> padding-top: 7px;<br /> }<br /> .rh-banner-meta {<br /> display: flex;<br /> border-top: 1px solid #1a2260;<br /> background: #1e2a70;<br /> }<br /> .rh-banner-field {<br /> flex: 1;<br /> padding: 6px 14px;<br /> border-right: 1px solid #1a2260;<br /> }<br /> .rh-banner-field:last-child {<br /> border-right: none;<br /> }<br /> .rh-banner-lbl {<br /> color: #7b9fd4;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> display: block;<br /> margin-bottom: 2px;<br /> }<br /> .rh-banner-val {<br /> color: #ffffff;<br /> font-size: 12px;<br /> word-break: break-all;<br /> }<br /> .rh-banner-val a {<br /> color: #00aeef;<br /> text-decoration: none;<br /> }<br /> .rh-banner-val a:hover {<br /> text-decoration: underline;<br /> }<br /> <br /> /* ReportCitation */<br /> .rcit-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-left: 4px solid #00aeef;<br /> border-radius: 4px;<br /> background: #ffffff;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> padding: 12px 14px;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> }<br /> .rcit-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 10px;<br /> }<br /> .rcit-text {<br /> color: #2b3990;<br /> font-size: 12px;<br /> line-height: 1.7;<br /> border: 1px solid #e8e8e8;<br /> border-radius: 3px;<br /> background: #f5f7ff;<br /> padding: 10px 12px;<br /> margin-bottom: 8px;<br /> }<br /> .rcit-row {<br /> display: flex;<br /> align-items: baseline;<br /> gap: 8px;<br /> margin-bottom: 10px;<br /> }<br /> .rcit-lbl {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> min-width: 28px;<br /> flex-shrink: 0;<br /> }<br /> .rcit-val a {<br /> color: #00aeef;<br /> font-size: 12px;<br /> word-break: break-all;<br /> text-decoration: none;<br /> }<br /> .rcit-val a:hover {<br /> text-decoration: underline;<br /> }<br /> .rcit-btn {<br /> display: inline-flex;<br /> align-items: center;<br /> gap: 6px;<br /> border: 1px solid #b3b3b3;<br /> border-radius: 20px;<br /> background: #ffffff;<br /> color: #b3b3b3;<br /> font-size: 11px;<br /> font-weight: 500;<br /> padding: 5px 12px;<br /> cursor: not-allowed;<br /> font-family: sans-serif;<br /> opacity: 0.6;<br /> }<br /> <br /> /* ReportContributors */<br /> .rc-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-left: 4px solid #00aeef;<br /> border-radius: 4px;<br /> background: #ffffff;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> padding: 12px 14px;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> }<br /> .rc-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 10px;<br /> }<br /> .rc-names {<br /> color: #2b3990;<br /> font-size: 12px;<br /> line-height: 1.7;<br /> }<br /> <br /> /* ReportTOC */<br /> .rtoc-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-left: 4px solid #00aeef;<br /> border-radius: 4px;<br /> background: #ffffff;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> margin: 0 0 1.5em 0;<br /> overflow: hidden;<br /> box-sizing: border-box;<br /> }<br /> .rtoc-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> padding: 12px 14px 8px;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .rtoc-section-title {<br /> font-size: 11px;<br /> font-weight: 500;<br /> padding: 6px 14px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> }<br /> .rtoc-entry {<br /> display: flex;<br /> align-items: center;<br /> justify-content: space-between;<br /> padding: 6px 14px 6px 22px;<br /> border-top: 1px solid rgba(255,255,255,0.5);<br /> }<br /> .rtoc-entry-text {<br /> display: flex;<br /> flex-direction: column;<br /> gap: 2px;<br /> flex: 1;<br /> padding-right: 12px;<br /> }<br /> .rtoc-entry-title {<br /> color: #2b3990;<br /> font-size: 12px;<br /> }<br /> .rtoc-entry-subtitle {<br /> color: #b3b3b3;<br /> font-size: 11px;<br /> line-height: 1.4;<br /> }<br /> .rtoc-read {<br /> display: inline-flex;<br /> align-items: center;<br /> border: 1px solid #2b3990;<br /> border-radius: 20px;<br /> color: #2b3990;<br /> font-size: 10px;<br /> font-weight: 500;<br /> padding: 3px 10px;<br /> text-decoration: none;<br /> white-space: nowrap;<br /> margin-left: 10px;<br /> background: #ffffff;<br /> }<br /> .rtoc-read:hover {<br /> background: #f5f7ff;<br /> }<br /> .rtoc-oos {<br /> padding: 7px 14px;<br /> font-size: 11px;<br /> font-style: italic;<br /> color: #888888;<br /> }<br /> <br /> /* Section colours */<br /> .s-fm .rtoc-section-title { background: #e55425; color: #ffffff; }<br /> .s-fm .rtoc-entry { background: #fdf3ef; }<br /> <br /> .s-spm .rtoc-section-title { background: #c67b2a; color: #ffffff; }<br /> .s-spm .rtoc-entry { background: #fdf6ef; }<br /> <br /> .s-ts .rtoc-section-title { background: #1e4f26; color: #ffffff; }<br /> .s-ts .rtoc-entry { background: #eff5f0; }<br /> <br /> .s-ch .rtoc-section-title { background: #4c8fcc; color: #ffffff; }<br /> .s-ch .rtoc-entry { background: #eff6fc; }<br /> <br /> .s-an .rtoc-section-title { background: #19305b; color: #ffffff; }<br /> .s-an .rtoc-entry { background: #eff2f7; }<br /> <br /> <br /> /* Chapter Templates ***************************************** */<br /> <br /> /* ChapterSynopsis */<br /> .cs-box {<br /> width: 100%;<br /> border-left: 4px solid #00aeef;<br /> padding: 12px 16px;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> }<br /> .cs-abstract-label {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 8px;<br /> }<br /> .cs-abstract-text {<br /> color: #2b3990;<br /> font-size: 16px;<br /> line-height: 1.8;<br /> }<br /> <br /> <br /> /* ChapterNav — cover centred between prev and next */<br /> .cn-box {<br /> width: 100%;<br /> border: 1px solid #e8c84a;<br /> border-radius: 4px;<br /> overflow: hidden;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> background: #ffffff;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> }<br /> .cn-row {<br /> width: 100%;<br /> border-collapse: collapse;<br /> margin: 0;<br /> }<br /> .cn-prev,<br /> .cn-next {<br /> width: 40%;<br /> padding: 12px 14px;<br /> vertical-align: middle;<br /> background: #fffdf0;<br /> }<br /> .cn-prev {<br /> border-right: 1px solid #e8c84a;<br /> }<br /> .cn-next {<br /> border-left: 1px solid #e8c84a;<br /> text-align: right;<br /> }<br /> .cn-prev:hover,<br /> .cn-next:hover {<br /> background: #fef9d6;<br /> }<br /> .cn-center {<br /> width: 20%;<br /> padding: 10px 14px;<br /> text-align: center;<br /> vertical-align: middle;<br /> background: #fef9d6;<br /> border-top: 3px solid #e8c84a;<br /> }<br /> .cn-center-img img {<br /> width: 48px;<br /> height: auto;<br /> border-radius: 2px;<br /> border: 1px solid #c8a820;<br /> display: block;<br /> margin: 0 auto 6px;<br /> }<br /> .cn-center-label {<br /> color: #c8a820;<br /> font-size: 9px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> margin-bottom: 2px;<br /> }<br /> .cn-center-title a {<br /> color: #2b3990;<br /> font-size: 10px;<br /> font-weight: 500;<br /> text-decoration: none;<br /> line-height: 1.3;<br /> }<br /> .cn-center-title a:hover {<br /> color: #00aeef;<br /> }<br /> .cn-direction {<br /> color: #c8a820;<br /> font-size: 9px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> display: block;<br /> margin-bottom: 3px;<br /> }<br /> .cn-chapter-title a {<br /> color: #2b3990;<br /> font-size: 12px;<br /> font-weight: 500;<br /> line-height: 1.3;<br /> text-decoration: none;<br /> }<br /> .cn-chapter-title a:hover {<br /> color: #00aeef;<br /> }<br /> .cn-chapter-desc {<br /> color: #b3b3b3;<br /> font-size: 11px;<br /> line-height: 1.4;<br /> margin-top: 2px;<br /> display: block;<br /> }<br /> .cn-empty {<br /> background: #fafafa;<br /> }<br /> .cn-prev.cn-empty {<br /> border-right: 1px solid #e8e8e8;<br /> }<br /> .cn-next.cn-empty {<br /> border-left: 1px solid #e8e8e8;<br /> }<br /> .cn-empty-label {<br /> color: #d0d0d0;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> font-style: italic;<br /> }<br /> <br /> /* ChapterContributors */<br /> .ccon-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-left: 4px solid #00aeef;<br /> border-radius: 4px;<br /> background: #ffffff;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> box-sizing: border-box;<br /> margin: 0 0 1.5em 0;<br /> overflow: hidden;<br /> }<br /> .ccon-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> padding: 10px 14px 6px;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .ccon-group {<br /> display: flex;<br /> gap: 12px;<br /> align-items: baseline;<br /> padding: 7px 14px;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .ccon-group:last-child {<br /> border-bottom: none;<br /> }<br /> .ccon-label {<br /> color: #2b3990;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> font-weight: 500;<br /> min-width: 160px;<br /> flex-shrink: 0;<br /> }<br /> .ccon-names {<br /> color: #030001;<br /> font-size: 12px;<br /> line-height: 1.7;<br /> flex: 1;<br /> }<br /> .ccon-country {<br /> color: #b3b3b3;<br /> font-size: 11px;<br /> }</div>

Design https://ckg.semanticclimate.org/index.php?title=MediaWiki:Common.css&diff=1283 2026-05-06T12:07:05Z

<p>Design: </p> <hr /> <div>/* Design Styling ***************************************** */<br /> <br /> /* Images */<br /> .responsive-image {<br /> width: 100%;<br /> max-width: 100%;<br /> height: auto;<br /> border: 4px solid red;<br /> }<br /> <br /> /* Glossary styling for MediaWiki */<br /> <br /> .glossary-letter-section {<br /> border-left: 5px solid #2b3990;<br /> padding-left: 16px;<br /> margin: 0 0 24px 0;<br /> }<br /> <br /> .glossary-letter-section h2 {<br /> font-size: 18px;<br /> font-weight: 500;<br /> color: #2b3990;<br /> margin: 0 0 16px 0;<br /> letter-spacing: 1px;<br /> }<br /> <br /> .glossary-entry {<br /> background: #ffffff;<br /> border: 0.5px solid #d3d1c7;<br /> border-radius: 12px;<br /> padding: 12px 16px;<br /> margin-bottom: 12px;<br /> }<br /> <br /> .glossary-entry h3 {<br /> margin: 0 0 8px 0;<br /> font-size: 16px;<br /> font-weight: 500;<br /> }<br /> <br /> .glossary-term {<br /> color: #1600ff;<br /> font-weight: 500;<br /> }<br /> <br /> .glossary-working-groups,<br /> .glossary-longer-term,<br /> .glossary-definition {<br /> font-size: 13px;<br /> line-height: 1.6;<br /> margin: 6px 0;<br /> color: #030001;<br /> }<br /> <br /> .glossary-working-groups strong,<br /> .glossary-longer-term strong,<br /> .glossary-definition strong {<br /> color: #2b3990;<br /> font-weight: 500;<br /> }<br /> <br /> /* Dark mode support (adjust as needed for your MediaWiki theme) */<br /> @media (prefers-color-scheme: dark) {<br /> .glossary-letter-section {<br /> border-left-color: #7fb3ff;<br /> }<br /> <br /> .glossary-letter-section h2 {<br /> color: #7fb3ff;<br /> }<br /> <br /> .glossary-entry {<br /> background: #1a1a1a;<br /> border-color: #444441;<br /> }<br /> <br /> .glossary-term {<br /> color: #5eb3ff;<br /> }<br /> <br /> .glossary-working-groups,<br /> .glossary-longer-term,<br /> .glossary-definition {<br /> color: #f0f0f0;<br /> }<br /> <br /> .glossary-working-groups strong,<br /> .glossary-longer-term strong,<br /> .glossary-definition strong {<br /> color: #7fb3ff;<br /> }<br /> }<br /> <br /> /* Acronyms list styling for MediaWiki */<br /> <br /> .acronyms-letter-section {<br /> border-left: 5px solid #00aeef;<br /> padding-left: 16px;<br /> margin: 0 0 24px 0;<br /> }<br /> <br /> .acronyms-letter-section h2 {<br /> font-size: 13px;<br /> font-weight: 500;<br /> color: #2b3990;<br /> margin: 0 0 12px 0;<br /> letter-spacing: 1px;<br /> }<br /> <br /> .acronyms-entry {<br /> background: #ffffff;<br /> border: 0.5px solid #d3d1c7;<br /> border-radius: 12px;<br /> padding: 12px 16px;<br /> margin-bottom: 8px;<br /> }<br /> <br /> .acronyms-entry h3 {<br /> margin: 0 0 8px 0;<br /> font-size: 15px;<br /> font-weight: 500;<br /> }<br /> <br /> .acronyms-term {<br /> color: #1600ff;<br /> font-weight: 500;<br /> font-family: monospace;<br /> }<br /> <br /> .acronyms-description {<br /> font-size: 13px;<br /> line-height: 1.5;<br /> margin: 4px 0;<br /> color: #030001;<br /> }<br /> <br /> .acronyms-report {<br /> font-size: 11px;<br /> line-height: 1.4;<br /> margin: 6px 0 0 0;<br /> color: #b3b3b3;<br /> }<br /> <br /> .acronyms-description strong,<br /> .acronyms-report strong {<br /> color: #00aeef;<br /> font-weight: 500;<br /> }<br /> <br /> .acronyms-report strong {<br /> color: #b3b3b3;<br /> }<br /> <br /> /* Dark mode support (adjust as needed for your MediaWiki theme) */<br /> @media (prefers-color-scheme: dark) {<br /> .acronyms-letter-section {<br /> border-left-color: #00d9ff;<br /> }<br /> <br /> .acronyms-letter-section h2 {<br /> color: #7fb3ff;<br /> }<br /> <br /> .acronyms-entry {<br /> background: #1a1a1a;<br /> border-color: #444441;<br /> }<br /> <br /> .acronyms-term {<br /> color: #5eb3ff;<br /> }<br /> <br /> .acronyms-description,<br /> .acronyms-report {<br /> color: #f0f0f0;<br /> }<br /> <br /> .acronyms-report {<br /> color: #888888;<br /> }<br /> <br /> .acronyms-description strong,<br /> .acronyms-report strong {<br /> color: #00d9ff;<br /> font-weight: 500;<br /> }<br /> <br /> .acronyms-report strong {<br /> color: #888888;<br /> }<br /> }<br /> <br /> <br /> <br /> /* Breadcrumbs ************************** */<br /> <br /> /* Force breadcrumbs to single line */<br /> #mw-content-subtitle {<br /> white-space: nowrap;<br /> }<br /> <br /> #mw-content-subtitle .subpages {<br /> display: inline;<br /> }<br /> <br /> #mw-content-subtitle .breadcrumb-separator {<br /> display: inline;<br /> }<br /> <br /> #mw-content-subtitle .breadcrumb-current {<br /> display: inline;<br /> }<br /> <br /> <br /> /* BtnNeutral Button Template - Design Option 4 */<br /> .btn-neutral {<br /> /* Color scheme - Outline style */<br /> background-color: transparent;<br /> color: #00aeef; /* Cyan text */<br /> border: 3px solid #00aeef; /* Cyan border */<br /> <br /> /* Typography */<br /> font-size: 18px;<br /> font-weight: 600;<br /> font-family: inherit;<br /> line-height: 1;<br /> <br /> /* Sizing &amp; spacing */<br /> padding: 14px 30px;<br /> min-height: 50px;<br /> display: inline-flex;<br /> align-items: center;<br /> justify-content: center;<br /> <br /> /* Appearance */<br /> border-radius: 8px;<br /> text-align: center;<br /> white-space: nowrap;<br /> cursor: pointer;<br /> <br /> /* Effects */<br /> transition: all 0.2s ease;<br /> text-decoration: none;<br /> }<br /> <br /> /* Link styling inside button */<br /> .btn-neutral a {<br /> color: #00aeef;<br /> text-decoration: none;<br /> cursor: pointer;<br /> }<br /> <br /> /* Hover state - fill with cyan background */<br /> .btn-neutral:hover {<br /> background-color: #00aeef;<br /> color: #030001; /* Black text on cyan bg */<br /> box-shadow: 0 4px 12px rgba(0, 174, 239, 0.3);<br /> transform: translateY(-2px);<br /> }<br /> <br /> .btn-neutral:hover a {<br /> color: #030001;<br /> }<br /> <br /> /* Make link fill entire button */<br /> .btn-neutral a {<br /> color: #00aeef;<br /> text-decoration: none;<br /> cursor: pointer;<br /> display: flex;<br /> align-items: center;<br /> justify-content: center;<br /> }<br /> <br /> /* Active/pressed state */<br /> .btn-neutral:active {<br /> background-color: #00aeef;<br /> color: #030001;<br /> border-color: #2b3990; /* Navy border on active */<br /> transform: scale(0.98);<br /> box-shadow: 0 2px 6px rgba(0, 174, 239, 0.4);<br /> }<br /> <br /> .btn-neutral:active a {<br /> color: #030001;<br /> }<br /> <br /> /* Focus state for accessibility */<br /> .btn-neutral:focus-within {<br /> outline: 2px solid #2b3990;<br /> outline-offset: 2px;<br /> }<br /> <br /> /* Disabled state */<br /> .btn-neutral.disabled {<br /> opacity: 0.6;<br /> cursor: not-allowed;<br /> border-color: #b3b3b3; /* Grey border when disabled */<br /> color: #b3b3b3; /* Grey text when disabled */<br /> }<br /> <br /> .btn-neutral.disabled a {<br /> color: #b3b3b3;<br /> pointer-events: none;<br /> }<br /> <br /> /* Template Styling ***************************************** */<br /> <br /> <br /> /* Acronym terms ***************************************** */<br /> .acronym-terms-box {<br /> background: #ffffff;<br /> border: 0.5px solid #d3d1c7;<br /> border-radius: 12px;<br /> padding: 1.25rem;<br /> margin: 1rem 0;<br /> }<br /> <br /> .acronym-terms-title {<br /> font-size: 16px;<br /> font-weight: 500;<br /> color: #2b3990;<br /> margin-bottom: 1rem;<br /> }<br /> <br /> .acronym-terms-pills {<br /> display: flex;<br /> flex-wrap: wrap;<br /> gap: 8px;<br /> row-gap: 16px;<br /> margin-bottom: -4px;<br /> }<br /> <br /> .acronym-terms-pills a {<br /> display: inline-block;<br /> background: #feff03;<br /> color: #2b3990;<br /> padding: 5px 10px;<br /> border-radius: 16px;<br /> font-size: 12px;<br /> font-weight: 500;<br /> text-decoration: none;<br /> transition: background-color 0.2s;<br /> margin-bottom: 4px;<br /> font-family: monospace;<br /> }<br /> <br /> .acronym-terms-pills a:hover {<br /> background: #ffff33;<br /> text-decoration: none;<br /> }<br /> <br /> /* Dark mode support */<br /> @media (prefers-color-scheme: dark) {<br /> .acronym-terms-box {<br /> background: #1a1a1a;<br /> border-color: #444441;<br /> }<br /> <br /> .acronym-terms-title {<br /> color: #7fb3ff;<br /> }<br /> <br /> .acronym-terms-pills a {<br /> background: #feff03;<br /> color: #030001;<br /> }<br /> <br /> .acronym-terms-pills a:hover {<br /> background: #ffff33;<br /> }<br /> }<br /> <br /> <br /> /* Glossary terms ***************************************** */<br /> .glossary-terms-box {<br /> background: #ffffff;<br /> border: 0.5px solid #d3d1c7;<br /> border-radius: 12px;<br /> padding: 1.25rem;<br /> margin: 1rem 0;<br /> }<br /> <br /> .glossary-terms-title {<br /> font-size: 16px;<br /> font-weight: 500;<br /> color: #2b3990;<br /> margin-bottom: 1rem;<br /> }<br /> <br /> .glossary-terms-pills {<br /> display: flex;<br /> flex-wrap: wrap;<br /> gap: 8px;<br /> row-gap: 16px;<br /> margin-bottom: -4px;<br /> }<br /> <br /> .glossary-terms-pills a {<br /> display: inline-block;<br /> background: #00aeef;<br /> color: #030001;<br /> padding: 6px 12px;<br /> border-radius: 20px;<br /> font-size: 13px;<br /> font-weight: 500;<br /> text-decoration: none;<br /> transition: background-color 0.2s;<br /> margin-bottom: 4px;<br /> }<br /> <br /> .glossary-terms-pills a:hover {<br /> background: #0098d0;<br /> text-decoration: none;<br /> }<br /> <br /> /* Dark mode support */<br /> @media (prefers-color-scheme: dark) {<br /> .glossary-terms-box {<br /> background: #1a1a1a;<br /> border-color: #444441;<br /> }<br /> <br /> .glossary-terms-title {<br /> color: #7fb3ff;<br /> }<br /> <br /> .glossary-terms-pills a {<br /> background: #00d9ff;<br /> color: #030001;<br /> }<br /> <br /> .glossary-terms-pills a:hover {<br /> background: #00b8d9;<br /> }<br /> }<br /> <br /> /* AR6 Templates ***************************************** */<br /> <br /> /* AR6Covers */<br /> .ar6-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-radius: 4px;<br /> background: #f9f9f7;<br /> font-family: sans-serif;<br /> padding: 12px 14px;<br /> box-sizing: border-box;<br /> margin: 0 0 1.5em 0;<br /> }<br /> .ar6-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 10px;<br /> }<br /> .ar6-labels {<br /> display: grid;<br /> grid-template-columns: 1fr 21px 3fr 21px 3fr;<br /> margin-bottom: 6px;<br /> }<br /> .ar6-group-label {<br /> color: #b3b3b3;<br /> font-size: 9px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> text-align: center;<br /> }<br /> .ar6-grid {<br /> display: grid;<br /> grid-template-columns: 1fr 21px 1fr 1fr 1fr 21px 1fr 1fr 1fr;<br /> align-items: end;<br /> }<br /> .ar6-cover {<br /> display: flex;<br /> flex-direction: column;<br /> align-items: center;<br /> gap: 6px;<br /> padding: 0 3px;<br /> }<br /> .ar6-cover img {<br /> width: 100%;<br /> height: auto;<br /> aspect-ratio: 3/4;<br /> border: 1px solid #d0d0d0;<br /> border-radius: 2px;<br /> display: block;<br /> object-fit: cover;<br /> }<br /> .ar6-cover:hover img {<br /> border-color: #00aeef;<br /> }<br /> .ar6-label {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> font-weight: 500;<br /> text-align: center;<br /> }<br /> .ar6-cover:hover .ar6-label {<br /> color: #2b3990;<br /> }<br /> .ar6-divider-col {<br /> width: 1px;<br /> background: #e0e0e0;<br /> align-self: stretch;<br /> margin: 0 10px;<br /> }<br /> <br /> /* Active state — dim all covers, then highlight the active one */<br /> .ar6-active-syr .ar6-cover,<br /> .ar6-active-wgi .ar6-cover,<br /> .ar6-active-wgii .ar6-cover,<br /> .ar6-active-wgiii .ar6-cover,<br /> .ar6-active-sr15 .ar6-cover,<br /> .ar6-active-srccl .ar6-cover,<br /> .ar6-active-srocc .ar6-cover {<br /> opacity: 0.4;<br /> transition: opacity 0.15s;<br /> }<br /> .ar6-active-syr .ar6-cover:hover,<br /> .ar6-active-wgi .ar6-cover:hover,<br /> .ar6-active-wgii .ar6-cover:hover,<br /> .ar6-active-wgiii .ar6-cover:hover,<br /> .ar6-active-sr15 .ar6-cover:hover,<br /> .ar6-active-srccl .ar6-cover:hover,<br /> .ar6-active-srocc .ar6-cover:hover {<br /> opacity: 1;<br /> }<br /> .ar6-active-syr .ar6-syr,<br /> .ar6-active-wgi .ar6-wgi,<br /> .ar6-active-wgii .ar6-wgii,<br /> .ar6-active-wgiii .ar6-wgiii,<br /> .ar6-active-sr15 .ar6-sr15,<br /> .ar6-active-srccl .ar6-srccl,<br /> .ar6-active-srocc .ar6-srocc {<br /> opacity: 1;<br /> }<br /> .ar6-active-syr .ar6-syr img,<br /> .ar6-active-wgi .ar6-wgi img,<br /> .ar6-active-wgii .ar6-wgii img,<br /> .ar6-active-wgiii .ar6-wgiii img,<br /> .ar6-active-sr15 .ar6-sr15 img,<br /> .ar6-active-srccl .ar6-srccl img,<br /> .ar6-active-srocc .ar6-srocc img {<br /> border: 2px solid #00aeef;<br /> border-radius: 3px;<br /> }<br /> .ar6-active-syr .ar6-syr .ar6-label,<br /> .ar6-active-wgi .ar6-wgi .ar6-label,<br /> .ar6-active-wgii .ar6-wgii .ar6-label,<br /> .ar6-active-wgiii .ar6-wgiii .ar6-label,<br /> .ar6-active-sr15 .ar6-sr15 .ar6-label,<br /> .ar6-active-srccl .ar6-srccl .ar6-label,<br /> .ar6-active-srocc .ar6-srocc .ar6-label {<br /> color: #2b3990;<br /> }<br /> <br /> /* When active=none or parameter omitted — no dimming */<br /> .ar6-active-none .ar6-cover {<br /> opacity: 1;<br /> }<br /> <br /> /* AR6Report */<br /> .ar6r-card {<br /> width: 100%;<br /> border: 1px solid #00aeef;<br /> border-radius: 4px;<br /> overflow: hidden;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> background: #ffffff;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> display: flex;<br /> }<br /> .ar6r-img {<br /> width: 180px;<br /> min-width: 180px;<br /> background: #1e2a70;<br /> display: flex;<br /> align-items: center;<br /> justify-content: center;<br /> padding: 16px;<br /> border-right: 1px solid #00aeef;<br /> flex-shrink: 0;<br /> }<br /> .ar6r-img img {<br /> width: 100%;<br /> height: auto;<br /> display: block;<br /> border-radius: 2px;<br /> }<br /> .ar6r-img .thumbinner,<br /> .ar6r-img .thumbimage {<br /> width: 100% !important;<br /> margin: 0 !important;<br /> border: none !important;<br /> background: none !important;<br /> }<br /> .ar6r-right {<br /> flex: 1;<br /> display: flex;<br /> flex-direction: column;<br /> }<br /> .ar6r-header {<br /> background: #2b3990;<br /> padding: 14px 16px;<br /> }<br /> .ar6r-tag {<br /> color: #00aeef;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 4px;<br /> }<br /> .ar6r-title {<br /> color: #ffffff;<br /> font-size: 16px;<br /> font-weight: 500;<br /> line-height: 1.3;<br /> margin-bottom: 4px;<br /> }<br /> .ar6r-subtitle {<br /> color: #9aaee8;<br /> font-size: 12px;<br /> line-height: 1.4;<br /> }<br /> .ar6r-synopsis {<br /> color: #030001;<br /> font-size: 12px;<br /> line-height: 1.6;<br /> padding: 10px 16px;<br /> border-bottom: 1px solid #f0f0f0;<br /> flex: 1;<br /> }<br /> .ar6r-meta {<br /> display: grid;<br /> grid-template-columns: 1fr 1fr 1fr;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .ar6r-meta-field {<br /> padding: 6px 16px;<br /> border-right: 1px solid #f0f0f0;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .ar6r-meta-field:nth-child(3n) {<br /> border-right: none;<br /> }<br /> .ar6r-meta-lbl {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> display: block;<br /> margin-bottom: 2px;<br /> }<br /> .ar6r-meta-val {<br /> color: #030001;<br /> font-size: 12px;<br /> }<br /> .ar6r-meta-val a {<br /> color: #00aeef;<br /> text-decoration: none;<br /> word-break: break-all;<br /> }<br /> .ar6r-meta-val a:hover {<br /> text-decoration: underline;<br /> }<br /> .ar6r-topics {<br /> padding: 8px 16px;<br /> border-bottom: 1px solid #f0f0f0;<br /> display: flex;<br /> flex-wrap: wrap;<br /> gap: 6px;<br /> align-items: center;<br /> }<br /> .ar6r-topics-lbl {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> margin-right: 4px;<br /> flex-shrink: 0;<br /> }<br /> .ar6r-topic {<br /> background: #f5f7ff;<br /> border: 1px solid #2b3990;<br /> border-radius: 20px;<br /> color: #2b3990;<br /> font-size: 10px;<br /> padding: 3px 10px;<br /> }<br /> .ar6r-btn-wrap {<br /> display: block;<br /> background: #2b3990;<br /> }<br /> .ar6r-btn-wrap a {<br /> display: block;<br /> color: #feff03;<br /> text-align: center;<br /> padding: 11px;<br /> font-size: 13px;<br /> font-weight: 500;<br /> letter-spacing: 0.02em;<br /> text-decoration: none;<br /> }<br /> .ar6r-btn-wrap a:hover {<br /> background: #1e2a70;<br /> }<br /> .ar6r-btn-wrap a::after {<br /> display: none;<br /> }<br /> <br /> <br /> /* Report Templates ***************************************** */<br /> <br /> /* ReportHeader */<br /> .rh-banner {<br /> width: 100%;<br /> border: 1px solid #00aeef;<br /> border-radius: 4px;<br /> overflow: hidden;<br /> background: #2b3990;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> margin: 0 0 1.5em 0;<br /> }<br /> .rh-banner-top {<br /> display: flex;<br /> align-items: stretch;<br /> }<br /> .rh-banner-img {<br /> width: 160px;<br /> min-width: 160px;<br /> background: #1e2a70;<br /> display: flex;<br /> align-items: center;<br /> justify-content: center;<br /> padding: 12px;<br /> border-right: 1px solid #1a2260;<br /> }<br /> .rh-banner-img img {<br /> width: 100%;<br /> height: auto;<br /> display: block;<br /> border-radius: 2px;<br /> }<br /> .rh-banner-right {<br /> flex: 1;<br /> display: flex;<br /> flex-direction: column;<br /> }<br /> .rh-banner-titles {<br /> padding: 12px 14px 10px;<br /> flex: 1;<br /> }<br /> .rh-banner-tag {<br /> color: #feff03;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 4px;<br /> }<br /> .rh-banner-title {<br /> color: #ffffff;<br /> font-size: 14px;<br /> font-weight: 500;<br /> line-height: 1.35;<br /> margin-bottom: 3px;<br /> }<br /> .rh-banner-subtitle {<br /> color: #00aeef;<br /> font-size: 12px;<br /> font-weight: 500;<br /> line-height: 1.4;<br /> margin-bottom: 8px;<br /> }<br /> .rh-banner-abstract-text {<br /> color: #b3d4f0;<br /> font-size: 11px;<br /> line-height: 1.6;<br /> border-top: 1px solid #1a2260;<br /> padding-top: 7px;<br /> }<br /> .rh-banner-meta {<br /> display: flex;<br /> border-top: 1px solid #1a2260;<br /> background: #1e2a70;<br /> }<br /> .rh-banner-field {<br /> flex: 1;<br /> padding: 6px 14px;<br /> border-right: 1px solid #1a2260;<br /> }<br /> .rh-banner-field:last-child {<br /> border-right: none;<br /> }<br /> .rh-banner-lbl {<br /> color: #7b9fd4;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> display: block;<br /> margin-bottom: 2px;<br /> }<br /> .rh-banner-val {<br /> color: #ffffff;<br /> font-size: 12px;<br /> word-break: break-all;<br /> }<br /> .rh-banner-val a {<br /> color: #00aeef;<br /> text-decoration: none;<br /> }<br /> .rh-banner-val a:hover {<br /> text-decoration: underline;<br /> }<br /> <br /> /* ReportCitation */<br /> .rcit-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-left: 4px solid #00aeef;<br /> border-radius: 4px;<br /> background: #ffffff;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> padding: 12px 14px;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> }<br /> .rcit-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 10px;<br /> }<br /> .rcit-text {<br /> color: #2b3990;<br /> font-size: 12px;<br /> line-height: 1.7;<br /> border: 1px solid #e8e8e8;<br /> border-radius: 3px;<br /> background: #f5f7ff;<br /> padding: 10px 12px;<br /> margin-bottom: 8px;<br /> }<br /> .rcit-row {<br /> display: flex;<br /> align-items: baseline;<br /> gap: 8px;<br /> margin-bottom: 10px;<br /> }<br /> .rcit-lbl {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> min-width: 28px;<br /> flex-shrink: 0;<br /> }<br /> .rcit-val a {<br /> color: #00aeef;<br /> font-size: 12px;<br /> word-break: break-all;<br /> text-decoration: none;<br /> }<br /> .rcit-val a:hover {<br /> text-decoration: underline;<br /> }<br /> .rcit-btn {<br /> display: inline-flex;<br /> align-items: center;<br /> gap: 6px;<br /> border: 1px solid #b3b3b3;<br /> border-radius: 20px;<br /> background: #ffffff;<br /> color: #b3b3b3;<br /> font-size: 11px;<br /> font-weight: 500;<br /> padding: 5px 12px;<br /> cursor: not-allowed;<br /> font-family: sans-serif;<br /> opacity: 0.6;<br /> }<br /> <br /> /* ReportContributors */<br /> .rc-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-left: 4px solid #00aeef;<br /> border-radius: 4px;<br /> background: #ffffff;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> padding: 12px 14px;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> }<br /> .rc-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 10px;<br /> }<br /> .rc-names {<br /> color: #2b3990;<br /> font-size: 12px;<br /> line-height: 1.7;<br /> }<br /> <br /> /* ReportTOC */<br /> .rtoc-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-left: 4px solid #00aeef;<br /> border-radius: 4px;<br /> background: #ffffff;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> margin: 0 0 1.5em 0;<br /> overflow: hidden;<br /> box-sizing: border-box;<br /> }<br /> .rtoc-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> padding: 12px 14px 8px;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .rtoc-section-title {<br /> font-size: 11px;<br /> font-weight: 500;<br /> padding: 6px 14px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> }<br /> .rtoc-entry {<br /> display: flex;<br /> align-items: center;<br /> justify-content: space-between;<br /> padding: 6px 14px 6px 22px;<br /> border-top: 1px solid rgba(255,255,255,0.5);<br /> }<br /> .rtoc-entry-text {<br /> display: flex;<br /> flex-direction: column;<br /> gap: 2px;<br /> flex: 1;<br /> padding-right: 12px;<br /> }<br /> .rtoc-entry-title {<br /> color: #2b3990;<br /> font-size: 12px;<br /> }<br /> .rtoc-entry-subtitle {<br /> color: #b3b3b3;<br /> font-size: 11px;<br /> line-height: 1.4;<br /> }<br /> .rtoc-read {<br /> display: inline-flex;<br /> align-items: center;<br /> border: 1px solid #2b3990;<br /> border-radius: 20px;<br /> color: #2b3990;<br /> font-size: 10px;<br /> font-weight: 500;<br /> padding: 3px 10px;<br /> text-decoration: none;<br /> white-space: nowrap;<br /> margin-left: 10px;<br /> background: #ffffff;<br /> }<br /> .rtoc-read:hover {<br /> background: #f5f7ff;<br /> }<br /> .rtoc-oos {<br /> padding: 7px 14px;<br /> font-size: 11px;<br /> font-style: italic;<br /> color: #888888;<br /> }<br /> <br /> /* Section colours */<br /> .s-fm .rtoc-section-title { background: #e55425; color: #ffffff; }<br /> .s-fm .rtoc-entry { background: #fdf3ef; }<br /> <br /> .s-spm .rtoc-section-title { background: #c67b2a; color: #ffffff; }<br /> .s-spm .rtoc-entry { background: #fdf6ef; }<br /> <br /> .s-ts .rtoc-section-title { background: #1e4f26; color: #ffffff; }<br /> .s-ts .rtoc-entry { background: #eff5f0; }<br /> <br /> .s-ch .rtoc-section-title { background: #4c8fcc; color: #ffffff; }<br /> .s-ch .rtoc-entry { background: #eff6fc; }<br /> <br /> .s-an .rtoc-section-title { background: #19305b; color: #ffffff; }<br /> .s-an .rtoc-entry { background: #eff2f7; }<br /> <br /> <br /> /* Chapter Templates ***************************************** */<br /> <br /> /* ChapterSynopsis */<br /> .cs-box {<br /> width: 100%;<br /> border-left: 4px solid #00aeef;<br /> padding: 12px 16px;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> }<br /> .cs-abstract-label {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> margin-bottom: 8px;<br /> }<br /> .cs-abstract-text {<br /> color: #2b3990;<br /> font-size: 16px;<br /> line-height: 1.8;<br /> }<br /> <br /> <br /> /* ChapterNav — cover centred between prev and next */<br /> .cn-box {<br /> width: 100%;<br /> border: 1px solid #e8c84a;<br /> border-radius: 4px;<br /> overflow: hidden;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> background: #ffffff;<br /> margin: 0 0 1.5em 0;<br /> box-sizing: border-box;<br /> }<br /> .cn-row {<br /> width: 100%;<br /> border-collapse: collapse;<br /> margin: 0;<br /> }<br /> .cn-prev,<br /> .cn-next {<br /> width: 40%;<br /> padding: 12px 14px;<br /> vertical-align: middle;<br /> background: #fffdf0;<br /> }<br /> .cn-prev {<br /> border-right: 1px solid #e8c84a;<br /> }<br /> .cn-next {<br /> border-left: 1px solid #e8c84a;<br /> text-align: right;<br /> }<br /> .cn-prev:hover,<br /> .cn-next:hover {<br /> background: #fef9d6;<br /> }<br /> .cn-center {<br /> width: 20%;<br /> padding: 10px 14px;<br /> text-align: center;<br /> vertical-align: middle;<br /> background: #fef9d6;<br /> border-top: 3px solid #e8c84a;<br /> }<br /> .cn-center-img img {<br /> width: 48px;<br /> height: auto;<br /> border-radius: 2px;<br /> border: 1px solid #c8a820;<br /> display: block;<br /> margin: 0 auto 6px;<br /> }<br /> .cn-center-label {<br /> color: #c8a820;<br /> font-size: 9px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> margin-bottom: 2px;<br /> }<br /> .cn-center-title a {<br /> color: #2b3990;<br /> font-size: 10px;<br /> font-weight: 500;<br /> text-decoration: none;<br /> line-height: 1.3;<br /> }<br /> .cn-center-title a:hover {<br /> color: #00aeef;<br /> }<br /> .cn-direction {<br /> color: #c8a820;<br /> font-size: 9px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> display: block;<br /> margin-bottom: 3px;<br /> }<br /> .cn-chapter-title a {<br /> color: #2b3990;<br /> font-size: 12px;<br /> font-weight: 500;<br /> line-height: 1.3;<br /> text-decoration: none;<br /> }<br /> .cn-chapter-title a:hover {<br /> color: #00aeef;<br /> }<br /> .cn-chapter-desc {<br /> color: #b3b3b3;<br /> font-size: 11px;<br /> line-height: 1.4;<br /> margin-top: 2px;<br /> display: block;<br /> }<br /> .cn-empty {<br /> background: #fafafa;<br /> }<br /> .cn-prev.cn-empty {<br /> border-right: 1px solid #e8e8e8;<br /> }<br /> .cn-next.cn-empty {<br /> border-left: 1px solid #e8e8e8;<br /> }<br /> .cn-empty-label {<br /> color: #d0d0d0;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> font-style: italic;<br /> }<br /> <br /> /* ChapterContributors */<br /> .ccon-box {<br /> width: 100%;<br /> border: 1px solid #e0e0e0;<br /> border-left: 4px solid #00aeef;<br /> border-radius: 4px;<br /> background: #ffffff;<br /> font-family: sans-serif;<br /> font-size: 12px;<br /> box-sizing: border-box;<br /> margin: 0 0 1.5em 0;<br /> overflow: hidden;<br /> }<br /> .ccon-header {<br /> color: #b3b3b3;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.05em;<br /> padding: 10px 14px 6px;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .ccon-group {<br /> display: flex;<br /> gap: 12px;<br /> align-items: baseline;<br /> padding: 7px 14px;<br /> border-bottom: 1px solid #f0f0f0;<br /> }<br /> .ccon-group:last-child {<br /> border-bottom: none;<br /> }<br /> .ccon-label {<br /> color: #2b3990;<br /> font-size: 10px;<br /> text-transform: uppercase;<br /> letter-spacing: 0.04em;<br /> font-weight: 500;<br /> min-width: 160px;<br /> flex-shrink: 0;<br /> }<br /> .ccon-names {<br /> color: #030001;<br /> font-size: 12px;<br /> line-height: 1.7;<br /> flex: 1;<br /> }<br /> .ccon-country {<br /> color: #b3b3b3;<br /> font-size: 11px;<br /> }</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1282 2026-05-06T12:05:30Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|class=responsive-image|This is the caption]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1281 2026-05-06T12:05:06Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|upright=1.2|This is the caption]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1280 2026-05-06T12:04:48Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|This is the caption]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1279 2026-05-06T12:02:56Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|800px|A caption describing the image]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1278 2026-05-06T12:02:44Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|A caption describing the image]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1277 2026-05-06T12:02:31Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|A caption describing the image]]]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1276 2026-05-06T12:02:08Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|frameless|400px|A caption describing the image]]]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1275 2026-05-06T11:59:41Z

<p>Design: /* Should be */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==<br /> <br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> &lt;/div&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1274 2026-05-06T11:59:03Z

<p>Design: /* Testing image and image caption display */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> == Was ==<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.<br /> <br /> == Should be ==</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1273 2026-05-06T11:58:19Z

<p>Design: </p> <hr /> <div>= Testing image and image caption display =<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:Fe4f469f42e1850d2b04e644d89e7d1c IPCC AR6 WGII Figure 16 008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.</div>

Design https://ckg.semanticclimate.org/index.php?title=File:Fe4f469f42e1850d2b04e644d89e7d1c_IPCC_AR6_WGII_Figure_16_008.png&diff=1272 2026-05-06T11:57:21Z

<p>Design: </p> <hr /> <div></div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1271 2026-05-06T11:56:30Z

<p>Design: /* Testing image and image caption display */</p> <hr /> <div>= Testing image and image caption display =<br /> <br /> &lt;div id=&quot;_idContainer028&quot; class=&quot;Figure&quot;&gt;&lt;/div&gt;<br /> <br /> [[File:fe4f469f42e1850d2b04e644d89e7d1c IPCC_AR6_WGII_Figure_16_008.png|thumb|400x300px]]<br /> <br /> '''Figure 16.8 |''' '''Constraints associated with limits by region and sector.''' Data from [[#Thomas--2021|Thomas et al. (2021)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems. See SM16.1 for methods. Constraints are categorised as: (1) economic: existing livelihoods, economic structures, and economic mobility; (2) social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) human capacity: individual, organisational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) governance, institutions and policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) financial: lack of financial resources; (6) information/awareness/technology: lack of awareness or access to information or technology; (7) physical: presence of physical barriers; and (8) biologic/climatic: temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind. '''Insufficient data:''' there is not enough literature to support an assessment (fewer than five studies available); '''Minor constraint:''' &amp;lt;20% of assessed literature identifies this constraint; '''Secondary constraint:''' 20–50% of assessed literature identifies this constraint; '''Primary constraint:''' &amp;gt;50% of assessed literature identifies this constraint.</div>

Design https://ckg.semanticclimate.org/index.php?title=Test:Images&diff=1270 2026-05-06T11:56:07Z

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Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SR15/TS&diff=1269 2026-05-04T10:48:02Z

<p>Design: /* Technical Summary */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Coordinating Lead Authors:'''<br /> <br /> Myles R. Allen (UK), Heleen de Coninck (Netherlands/EU), Opha Pauline Dube (Botswana), Ove Hoegh-Guldberg (Australia), Daniela Jacob (Germany), Kejun Jiang (China), Aromar Revi (India), Joeri Rogelj (Belgium/Austria), Joyashree Roy (India), Drew Shindell (USA), William Solecki (USA), Michael Taylor (Jamaica), Petra Tschakert (Australia/Austria), Henri Waisman (France)<br /> <br /> '''Lead Authors:'''<br /> <br /> Sharina Abdul Halim (Malaysia), Philip Antwi-Agyei (Ghana), Fernando Aragón–Durand (Mexico), Mustafa Babiker (Sudan), Paolo Bertoldi (Italy), Marco Bindi (Italy), Sally Brown (UK), Marcos Buckeridge (Brazil), Ines Camilloni (Argentina), Anton Cartwright (South Africa), Wolfgang Cramer (France/Germany), Purnamita Dasgupta (India), Arona Diedhiou (Ivory Coast/Senegal), Riyanti Djalante (Japan/Indonesia), Wenjie Dong (China), Kristie L. Ebi (USA), Francois Engelbrecht (South Africa), Solomone Fifita (Fiji), James Ford (UK/Canada), Piers Forster (UK), Sabine Fuss (Germany), Bronwyn Hayward (New Zealand), Jean-Charles Hourcade (France), Veronika Ginzburg (Russia), Joel Guiot (France), Collins Handa (Kenya), Yasuaki Hijioka (Japan), Stephen Humphreys (UK/Ireland), Mikiko Kainuma (Japan), Jatin Kala (Australia), Markku Kanninen (Finland), Haroon Kheshgi (USA), Shigeki Kobayashi (Japan), Elmar Kriegler (Germany), Debora Ley (Guatemala/Mexico), Diana Liverman (USA), Natalie Mahowald (USA), Reinhard Mechler (Germany), Shagun Mehrotra (USA/India), Yacob Mulugetta (UK/Ethiopia), Luis Mundaca (Sweden/Chile), Peter Newman (Australia), Chukwumerije Okereke (UK/Nigeria), Antony Payne (UK), Rosa Perez (Philippines), Patricia Fernanda Pinho (Brazil), Anastasia Revokatova (Russian Federation), Keywan Riahi (Austria), Seth Schultz (USA), Roland Séférian (France), Sonia I. Seneviratne (Switzerland), Linda Steg (Netherlands), Avelino G. Suarez Rodriguez (Cuba), Taishi Sugiyama (Japan), Adelle Thomas (Bahamas), Maria Virginia Vilariño (Argentina), Morgan Wairiu (Solomon Islands), Rachel Warren (UK), Guangsheng Zhou (China), Kirsten Zickfeld (Canada/Germany)<br /> <br /> '''Contributing Authors:'''<br /> <br /> Michelle Achlatis (Australia/Greece), Lisa V. Alexander (Australia), Malcolm Araos (Maldives/ Canada), Stefan Bakker (Netherlands), Mook Bangalore (USA), Amir Bazaz (India), Ella Belfer (Canada), Tim Benton (UK), Peter Berry (Canada), Bishwa Bhaskar Choudhary (India), Christopher Boyer (USA), Lorenzo Brilli (Italy), Katherine Calvin (USA), William Cheung (Canada), Sarah Connors (France/UK), Joana Correia de Oliveira de Portugal Pereira (UK/ Portugal), Marlies Craig (South Africa), Dipak Dasgupta (India), Kiane de Kleijne (Netherlands/ EU), Maria del Mar Zamora Dominguez (Mexico), Michel den Elzen (Netherlands), Haile Eakin (USA), Oreane Edelenbosch (Netherlands/Italy), Neville Ellis (Australia), Johannes Emmerling (Italy/Germany), Jason Evans (Australia), Maria Figueroa (Denmark/Venezuela), Dominique Finon (France), Hubertus Fisher (Switzerland), Klaus Fraedrich (Germany), Jan Fuglestvedt (Norway), Anjani Ganase (Trinidad and Tobago), Thomas Gasser (Austria/ France), Jean Pierre Gattuso (France), Frédéric Ghersi (France), Nathan Gillett (Canada), Adriana Grandis (Brazil), Peter Greve (Germany/Austria), Tania Guillén Bolaños (Germany/ Nicaragua), Mukesh Gupta (India), Amaha Medhin Haileselassie (Ethiopia), Naota Hanasaki (Japan), Tomoko Hasegawa (Japan), Eamon Haughey (Ireland), Katie Hayes (Canada), Chenmin He (China), Edgar Hertwich (USA/Austria), Diana Hinge Salili (Vanuatu), Annette Hirsch (Australia/Switzerland), Lena Höglund-Isaksson (Austria/Sweden), Daniel Huppmann (Austria), Saleemul Huq (Bangladesh/UK), Rachel James (UK), Chris Jones (UK), Thomas Jung (Germany), Richard Klein (Netherlands/Germany), Gerhard Krinner (France), David Lawrence (USA), Tim Lenton (UK), Gunnar Luderer (Germany), Peter Marcotullio (USA), Anil Markandya (Spain/UK), Omar Massera (Mexico), David L. McCollum (Austria/USA), Kathleen McInnes (Australia), Malte Meinshausen (Australia/Germany), Katrin J. Meissner (Australia), Richard Millar (UK), Katja Mintenbeck (Germany), Dann Mitchell (UK), Alan C. Mix (USA), Dirk Notz (Germany), Leonard Nurse (Barbados), Andrew Okem (Nigeria), Lennart Olsson (Sweden), Carolyn Opio (Uganda), Michael Oppenheimer (USA), Karen Paiva Henrique (Brazil), Simon Parkinson (Canada), Shlomit Paz (Israel), Juliane Petersen (Germany), Jan Petzold (Germany), Maxime Plazzotta (France), Alexander Popp (Germany), Swantje Preuschmann (Germany), Pallav Purohit (Austria/India), Graciela Raga (Mexico/Argentina), Mohammad Feisal Rahman (Bangladesh), Andy Reisinger (New Zealand), Kevon Rhiney (Jamaica), Aurélien Ribes (France), Mark Richardson (USA/UK), Wilfried Rickels (Germany), Timmons Roberts (USA), Maisa Rojas (Chile), Harry Saunders (Canada/USA), Christina Schädel (USA/Switzerland), Hanna Scheuffele (Germany), Lisa Schipper (UK/Sweden), Carl-Friedrich Schleussner (Germany), Jörn Schmidt (Germany), Daniel Scott (Canada), Jana Sillmann (Germany/ Norway), Chandni Singh (India), Raphael Slade (UK), Christopher Smith (UK), Pete Smith (UK), Shreya Some (India), Gerd Sparovek (Brazil), Will Steffen (Australia), Kimberly Stephenson (Jamaica), Tannecia Stephenson (Jamaica), Pablo Suarez (Argentina), Mouhamadou B. Sylla (Senegal), Nenenteiti Teariki-Ruatu (Kiribati), Mark Tebboth (UK), Peter Thorne (Ireland/UK), Evelina Trutnevyte (Switzerland/Lithuania), Penny Urquhart (South Africa), Arjan van Rooij (Netherlands), Anne M. van Valkengoed (Netherlands), Robert Vautard (France), Richard Wartenburger (Germany/Switzerland), Michael Wehner (USA), Margaretha Wewerinke-Singh (Netherlands), Nora M. Weyer (Germany), Felicia Whyte (Jamaica), Lini Wollenberg (USA), Yang Xiu (China), Gary Yohe (USA), Xuebin Zhang (Canada), Wenji Zhou (Austria/ China), Robert B. Zougmoré (Burkina Faso/Mali)<br /> <br /> '''Review Editors:'''<br /> <br /> Amjad Abdulla (Maldives), Rizaldi Boer (Indonesia), Ismail Elgizouli Idris (Sudan), Andreas Fischlin (Switzerland), Greg Flato (Canada), Jan Fuglestvedt (Norway), Xuejie Gao (China), Mark Howden (Australia), Svitlana Krakovska (Ukraine), Ramon Pichs Madruga (Cuba), Jose Antonio Marengo (Brazil/Peru), Rachid Mrabet (Morocco), Joy Pereira (Malaysia), Roberto Sanchez (Mexico), Roberto Schaeffer (Brazil), Boris Sherstyukov (Russian Federation), Diana Ürge-Vorsatz (Hungary)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Daniel Huppmann (Austria), Tania Guillén Bolaños (Germany/Nicaragua), Neville Ellis (Australia), Kiane de Kleijne (Netherlands/EU), Richard Millar (UK), Chandni Singh (India), Chris Smith (UK)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> Allen, M.R., H. de Coninck, O.P. Dube, O. Hoegh-Guldberg, D. Jacob, K. Jiang, A. Revi, J. Rogelj, J. Roy, D. Shindell, W. Solecki, M. Taylor, P. Tschakert, H. Waisman, S. Abdul Halim, P. Antwi-Agyei, F. Aragón-Durand, M. Babiker, P. Bertoldi, M. Bindi, S. Brown, M. Buckeridge, I. Camilloni, A. Cartwright, W. Cramer, P. Dasgupta, A. Diedhiou, R. Djalante, W. Dong, K.L. Ebi, F. Engelbrecht, S. Fifita, J. Ford, P. Forster, S. Fuss, V. Ginzburg, J. Guiot, C. Handa, B. Hayward, Y. Hijioka, J.-C. Hourcade, S. Humphreys, M. Kainuma, J. Kala, M. Kanninen, H. Kheshgi, S. Kobayashi, E. Kriegler, D. Ley, D. Liverman, N. Mahowald, R. Mechler, S. Mehrotra, Y. Mulugetta, L. Mundaca, P. Newman, C. Okereke, A. Payne, R. Perez, P.F. Pinho, A. Revokatova, K. Riahi, S. Schultz, R. Séférian, S.I. Seneviratne, L. Steg, A.G. Suarez Rodriguez, T. Sugiyama, A. Thomas, M.V. Vilariño, M. Wairiu, R. Warren, K. Zickfeld, and G. Zhou, 2018: Technical Summary. In: ''Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty'' [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press.<br /> <br /> == TS.1 Framing and Context ==<br /> <br /> This chapter frames the context, knowledge-base and assessment approaches used to understand the impacts of 1.5°C global warming above pre-industrial levels and related global greenhouse gas emission pathways, building on the IPCC Fifth Assessment Report (AR5), in the context of strengthening the global response to the threat of climate change, sustainable development and efforts to eradicate poverty.<br /> <br /> '''Human-induced warming reached approximately 1°C (''likely'') between 0.8°C and 1.2°C) above pre-industrial levels in 2017, increasing at 0.2°C (''likely'' between 0.1°C and 0.3°C) per decade (''high confidence'').''' Global warming is defined in this report as an increase in combined surface air and sea surface temperatures averaged over the globe and over a 30-year period. Unless otherwise specified, warming is expressed relative to the period 1850–1900, used as an approximation of pre-industrial temperatures in AR5. For periods shorter than 30 years, warming refers to the estimated average temperature over the 30 years centred on that shorter period, accounting for the impact of any temperature fluctuations or trend within those 30 years. Accordingly, warming from pre-industrial levels to the decade 2006–2015 is assessed to be 0.87°C (''likely'' between 0.75°C and 0.99°C). Since 2000, the estimated level of human-induced warming has been equal to the level of observed warming with a likely range of ±20% accounting for uncertainty due to contributions from solar and volcanic activity over the historical period (''high confidence''). {1.2.1}<br /> <br /> '''Warming greater than the global average has already been experienced in many regions and seasons, with higher average warming over land than over the ocean (''high confidence'').''' Most land regions are experiencing greater warming than the global average, while most ocean regions are warming at a slower rate. Depending on the temperature dataset considered, 20–40% of the global human population live in regions that, by the decade 2006–2015, had already experienced warming of more than 1.5°C above pre-industrial in at least one season (''medium confidence''). {1.2.1, 1.2.2}<br /> <br /> '''Past emissions alone are unlikely to raise global-mean temperature to 1.5°C above pre-industrial levels (''medium confidence''), but past emissions do commit to other changes, such as further sea level rise (''high confidence'').''' If all anthropogenic emissions (including aerosol-related) were reduced to zero immediately, any further warming beyond the 1°C already experienced would ''likely'' be less than 0.5°C over the next two to three decades (''high confidence''), and ''likely'' less than 0.5°C on a century time scale (''medium confidence''), due to the opposing effects of different climate processes and drivers. A warming greater than 1.5°C is therefore not geophysically unavoidable: whether it will occur depends on future rates of emission reductions. {1.2.3, 1.2.4}<br /> <br /> '''1.5°C emission pathways are defined as those that, given current knowledge of the climate response, provide a one-in-two to two-in-three chance of warming either remaining below 1.5°C or returning to 1.5°C by around 2100 following an overshoot.''' Overshoot pathways are characterized by the peak magnitude of the overshoot, which may have implications for impacts. All 1.5°C pathways involve limiting cumulative emissions of long-lived greenhouse gases, including carbon dioxide and nitrous oxide, and substantial reductions in other climate forcers (''high confidence''). Limiting cumulative emissions requires either reducing net global emissions of long-lived greenhouse gases to zero before the cumulative limit is reached, or net negative global emissions (anthropogenic removals) after the limit is exceeded. {1.2.3, 1.2.4, Cross-Chapter Boxes 1 and 2}<br /> <br /> '''This report assesses projected impacts at a global average warming of 1.5°C and higher levels of warming.''' Global warming of 1.5°C is associated with global average surface temperatures fluctuating naturally on either side of 1.5°C, together with warming substantially greater than 1.5°C in many regions and seasons (''high confidence''), all of which must be considered in the assessment of impacts. Impacts at 1.5°C of warming also depend on the emission pathway to 1.5°C. Very different impacts result from pathways that remain below 1.5°C versus pathways that return to 1.5°C after a substantial overshoot, and when temperatures stabilize at 1.5°C versus a transient warming past 1.5°C (''medium confidence''). {1.2.3, 1.3}<br /> <br /> '''Ethical considerations, and the principle of equity in particular, are central to this report, recognizing that many of the impacts of warming up to and beyond 1.5°C, and some potential impacts of mitigation actions required to limit warming to 1.5°C, fall disproportionately on the poor and vulnerable (''high confidence'').''' Equity has procedural and distributive dimensions and requires fairness in burden sharing both between generations and between and within nations. In framing the objective of holding the increase in the global average temperature rise to well below 2°C above pre-industrial levels, and to pursue efforts to limit warming to 1.5°C, the Paris Agreement associates the principle of equity with the broader goals of poverty eradication and sustainable development, recognising that effective responses to climate change require a global collective effort that may be guided by the 2015 United Nations Sustainable Development Goals. {1.1.1}<br /> <br /> '''Climate adaptation refers to the actions taken to manage impacts of climate change by reducing vulnerability and exposure to its harmful effects and exploiting any potential benefits.''' Adaptation takes place at international, national and local levels. Subnational jurisdictions and entities, including urban and rural municipalities, are key to developing and reinforcing measures for reducing weather- and climate-related risks. Adaptation implementation faces several barriers including lack of up-to-date and locally relevant information, lack of finance and technology, social values and attitudes, and institutional constraints (''high confidence''). Adaptation is more likely to contribute to sustainable development when policies align with mitigation and poverty eradication goals (''medium confidence''). {1.1, 1.4}<br /> <br /> '''Ambitious mitigation actions are indispensable to limit warming to 1.5°C while achieving sustainable development and poverty eradication (''high confidence'').''' Ill-designed responses, however, could pose challenges especially – but not exclusively – for countries and regions contending with poverty and those requiring significant transformation of their energy systems. This report focuses on ‘climate-resilient development pathways’, which aim to meet the goals of sustainable development, including climate adaptation and mitigation, poverty eradication and reducing inequalities. But any feasible pathway that remains within 1.5°C involves synergies and trade-offs (''high confidence''). Significant uncertainty remains as to which pathways are more consistent with the principle of equity. {1.1.1, 1.4}<br /> <br /> '''Multiple forms of knowledge, including scientific evidence, narrative scenarios and prospective pathways, inform the understanding of 1.5°C.''' This report is informed by traditional evidence of the physical climate system and associated impacts and vulnerabilities of climate change, together with knowledge drawn from the perceptions of risk and the experiences of climate impacts and governance systems. Scenarios and pathways are used to explore conditions enabling goal-oriented futures while recognizing the significance of ethical considerations, the principle of equity, and the societal transformation needed. {1.2.3, 1.5.2}<br /> <br /> '''There is no single answer to the question of whether it is feasible to limit warming to 1.5°C and adapt to the consequences.''' Feasibility is considered in this report as the capacity of a system as a whole to achieve a specific outcome. The global transformation that would be needed to limit warming to 1.5°C requires enabling conditions that reflect the links, synergies and trade-offs between mitigation, adaptation and sustainable development. These enabling conditions are assessed across many dimensions of feasibility – geophysical, environmental-ecological, technological, economic, socio-cultural and institutional – that may be considered through the unifying lens of the Anthropocene, acknowledging profound, differential but increasingly geologically significant human influences on the Earth system as a whole. This framing also emphasises the global interconnectivity of past, present and future human–environment relations, highlighting the need and opportunities for integrated responses to achieve the goals of the Paris Agreement. {1.1, Cross-Chapter Box 1}<br /> <br /> == TS.2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development == <br /> <br /> This chapter assesses mitigation pathways consistent with limiting warming to 1.5°C above pre-industrial levels. In doing so, it explores the following key questions: What role do CO&lt;sub&gt;2&lt;/sub&gt; and non-CO&lt;sub&gt;2&lt;/sub&gt; emissions play? {2.2, 2.3, 2.4, 2.6} To what extent do 1.5°C pathways involve overshooting and returning below 1.5°C during the 21st century? {2.2,<br /> 2.3} What are the implications for transitions in energy, land use and sustainable development? {2.3, 2.4, 2.5} How do policy frameworks affect the ability to limit warming to 1.5°C? {2.3, 2.5} What are the associated knowledge gaps? {2.6}<br /> <br /> '''The assessed pathways describe integrated, quantitative evolutions of all emissions over the 21st century associated with global energy and land use and the world economy.''' The assessment is contingent upon available integrated assessment literature and model assumptions, and is complemented by other studies with different scope, for example, those focusing on individual sectors. In recent years, integrated mitigation studies have improved the characterizations of mitigation pathways. However, limitations remain, as climate damages, avoided impacts, or societal co-benefits of the modelled transformations remain largely unaccounted for, while concurrent rapid technological changes, behavioural aspects, and uncertainties about input data present continuous challenges. (''high confidence'') {2.1.3, 2.3, 2.5.1, 2.6, Technical Annex 2}<br /> <br /> === The Chances of Limiting Warming to 1.5°C and the Requirements for Urgent Action ===<br /> <br /> '''Pathways consistent with 1.5°C of warming above pre-industrial levels can be identified under a range of assumptions about economic growth, technology developments and lifestyles.''' However, lack of global cooperation, lack of governance of the required energy and land transformation, and increases in resource-intensive consumption are key impediments to achieving 1.5°C pathways. Governance challenges have been related to scenarios with high inequality and high population growth in the 1.5°C pathway literature. {2.3.1, 2.3.2, 2.5}<br /> <br /> '''Under emissions in line with current pledges under the Paris Agreement (known as Nationally Determined Contributions, or NDCs), global warming is expected to surpass 1.5°C above pre-industrial levels, even if these pledges are supplemented with very challenging increases in the scale and ambition of mitigation after 2030 (''high confidence'').''' This increased action would need to achieve net zero CO&lt;sub&gt;2&lt;/sub&gt; emissions in less than 15 years. Even if this is achieved, temperatures would only be expected to remain below the 1.5°C threshold if the actual geophysical response ends up being towards the low end of the currently estimated uncertainty range. Transition challenges as well as identified trade-offs can be reduced if global emissions peak before 2030 and marked emissions reductions compared to today are already achieved by 2030. {2.2, 2.3.5, Cross-Chapter Box 11 in Chapter 4}<br /> <br /> '''Limiting warming to 1.5°C depends on greenhouse gas (GHG) emissions over the next decades, where lower GHG emissions in 2030 lead to a higher chance of keeping peak warming to 1.5°C (''high confidence'').''' Available pathways that aim for no or limited (less than 0.1°C) overshoot of 1.5°C keep GHG emissions in 2030 to 25–30 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;-1&lt;/sup&gt; in 2030 (interquartile range). This contrasts with median estimates for current unconditional NDCs of 52–58 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;-1&lt;/sup&gt; in 2030. Pathways that aim for limiting warming to 1.5°C by 2100 after a temporary temperature overshoot rely on large-scale deployment of carbon dioxide removal (CDR) measures, which are uncertain and entail clear risks. In model pathways with no or limited overshoot of 1.5°C, global net anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions decline by about 45% from 2010 levels by 2030 (40–60% interquartile range), reaching net zero around 2050 (2045–2055 interquartile range). For limiting global warming to below 2°C with at least 66% probability CO&lt;sub&gt;2&lt;/sub&gt; emissions are projected to decline by about 25% by 2030 in most pathways (10–30% interquartile range) and reach net zero around 2070 (2065–2080 interquartile range). &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; {2.2, 2.3.3, 2.3.5, 2.5.3, Cross-Chapter Boxes 6 in Chapter 3 and 9 in Chapter 4, 4.3.7}<br /> <br /> '''Limiting warming to 1.5°C implies reaching net zero CO&lt;sub&gt;2&lt;/sub&gt; emissions globally around 2050 and concurrent deep reductions in emissions of non-CO&lt;sub&gt;2&lt;/sub&gt; forcers, particularly methane (''high confidence'').''' Such mitigation pathways are characterized by energy-demand reductions, decarbonization of electricity and other fuels, electrification of energy end use, deep reductions in agricultural emissions, and some form of CDR with carbon storage on land or sequestration in geological reservoirs. Low energy demand and low demand for land- and GHG-intensive consumption goods facilitate limiting warming to as close as possible to 1.5°C. {2.2.2, 2.3.1, 2.3.5, 2.5.1, Cross-Chapter Box 9 in Chapter 4}.<br /> <br /> '''In comparison to a 2°C limit, the transformations required to limit warming to 1.5°C are qualitatively similar but more pronounced and rapid over the next decades (''high confidence'').''' 1.5°C implies very ambitious, internationally cooperative policy environments that transform both supply and demand (''high confidence''). {2.3, 2.4, 2.5}<br /> <br /> '''Policies reflecting a high price on emissions are necessary in models to achieve cost-effective 1.5°C pathways (''high confidence'').''' Other things being equal, modelling studies suggest the global average discounted marginal abatement costs for limiting warming to 1.5°C being about 3–4 times higher compared to 2°C over the 21st century, with large variations across models and socio-economic and policy assumptions. Carbon pricing can be imposed directly or implicitly by regulatory policies. Policy instruments, like technology policies or performance standards, can complement explicit carbon pricing in specific areas. {2.5.1, 2.5.2, 4.4.5}<br /> <br /> '''Limiting warming to 1.5°C requires a marked shift in investment patterns (''medium confidence'').''' Additional annual average energy-related investments for the period 2016 to 2050 in pathways limiting warming to 1.5°C compared to pathways without new climate policies beyond those in place today (i.e., baseline) are estimated to be around 830 billion USD2010 (range of 150 billion to 1700 billion USD2010 across six models). Total energy-related investments increase by about 12% (range of 3% to 24%) in 1.5°C pathways relative to 2°C pathways. Average annual investment in low-carbon energy technologies and energy efficiency are upscaled by roughly a factor of six (range of factor of 4 to 10) by 2050 compared to 2015, overtaking fossil investments globally by around 2025 (''medium confidence''). Uncertainties and strategic mitigation portfolio choices affect the magnitude and focus of required investments. {2.5.2}<br /> <br /> === Future Emissions in 1.5°C Pathways ===<br /> <br /> '''Mitigation requirements can be quantified using carbon budget approaches that relate cumulative CO&lt;sub&gt;2&lt;/sub&gt; emissions to global mean temperature increase.''' Robust physical understanding underpins this relationship, but uncertainties become increasingly relevant as a specific temperature limit is approached. These uncertainties relate to the transient climate response to cumulative carbon emissions (TCRE), non-CO&lt;sub&gt;2&lt;/sub&gt; emissions, radiative forcing and response, potential additional Earth system feedbacks (such as permafrost thawing), and historical emissions and temperature. {2.2.2, 2.6.1}<br /> <br /> '''Cumulative CO&lt;sub&gt;2&lt;/sub&gt; emissions are kept within a budget by reducing global annual CO&lt;sub&gt;2&lt;/sub&gt; emissions to net zero. This assessment suggests a remaining budget of about 420 GtCO&lt;sub&gt;2&lt;/sub&gt; for a two-thirds chance of limiting warming to 1.5°C, and of about 580 GtCO&lt;sub&gt;2&lt;/sub&gt; for an even chance (''medium confidence'').''' The remaining carbon budget is defined here as cumulative CO&lt;sub&gt;2&lt;/sub&gt; emissions from the start of 2018 until the time of net zero global emissions for global warming defined as a change in global near-surface air temperatures. Remaining budgets applicable to 2100 would be approximately 100 GtCO&lt;sub&gt;2&lt;/sub&gt; lower than this to account for permafrost thawing and potential methane release from wetlands in the future, and more thereafter. These estimates come with an additional geophysical uncertainty of at least ±400 GtCO&lt;sub&gt;2&lt;/sub&gt;, related to non-CO&lt;sub&gt;2&lt;/sub&gt; response and TCRE distribution. Uncertainties in the level of historic warming contribute ±250 GtCO&lt;sub&gt;2&lt;/sub&gt;. In addition, these estimates can vary by ±250 GtCO&lt;sub&gt;2&lt;/sub&gt; depending on non-CO&lt;sub&gt;2&lt;/sub&gt; mitigation strategies as found in available pathways. {2.2.2, 2.6.1}<br /> <br /> '''Staying within a remaining carbon budget of 580 GtCO&lt;sub&gt;2&lt;/sub&gt; implies that CO&lt;sub&gt;2&lt;/sub&gt; emissions reach carbon neutrality in about 30 years, reduced to 20 years for a 420 GtCO&lt;sub&gt;2&lt;/sub&gt; remaining carbon budget (''high confidence'').''' The ±400 GtCO&lt;sub&gt;2&lt;/sub&gt; geophysical uncertainty range surrounding a carbon budget translates into a variation of this timing of carbon neutrality of roughly ±15–20 years. If emissions do not start declining in the next decade, the point of carbon neutrality would need to be reached at least two decades earlier to remain within the same carbon budget. {2.2.2, 2.3.5}<br /> <br /> '''Non-CO&lt;sub&gt;2&lt;/sub&gt; emissions contribute to peak warming and thus affect the remaining carbon budget. The evolution of methane and sulphur dioxide emissions strongly influences the chances of limiting warming to 1.5°C. In the near-term, a weakening of aerosol cooling would add to future warming, but can be tempered by reductions in methane emissions (''high confidence'').''' Uncertainty in radiative forcing estimates (particularly aerosol) affects carbon budgets and the certainty of pathway categorizations. Some non-CO&lt;sub&gt;2&lt;/sub&gt; forcers are emitted alongside CO&lt;sub&gt;2&lt;/sub&gt;, particularly in the energy and transport sectors, and can be largely addressed through CO&lt;sub&gt;2&lt;/sub&gt; mitigation. Others require specific measures, for example, to target agricultural nitrous oxide (N2O) and methane (CH4), some sources of black carbon, or hydrofluorocarbons (''high confidence''). In many cases, non-CO&lt;sub&gt;2&lt;/sub&gt; emissions reductions are similar in 2°C pathways, indicating reductions near their assumed maximum potential by integrated assessment models. Emissions of N2O and NH3increase in some pathways with strongly increased bioenergy demand. {2.2.2, 2.3.1, 2.4.2, 2.5.3}<br /> <br /> === The Role of Carbon Dioxide Removal (CDR) ===<br /> <br /> '''All analysed pathways limiting warming to 1.5°C with no or limited overshoot use CDR to some extent to neutralize emissions from sources for which no mitigation measures have been identified and, in most cases, also to achieve net negative emissions to return global warming to 1.5°C following a peak (''high confidence''). The longer the delay in reducing CO&lt;sub&gt;2&lt;/sub&gt; emissions towards zero, the larger the likelihood of exceeding 1.5°C, and the heavier the implied reliance on net negative emissions after mid-century to return warming to 1.5°C (''high confidence'').''' The faster reduction of net CO&lt;sub&gt;2&lt;/sub&gt; emissions in 1.5°C compared to 2°C pathways is predominantly achieved by measures that result in less CO&lt;sub&gt;2&lt;/sub&gt; being produced and emitted, and only to a smaller degree through additional CDR. Limitations on the speed, scale and societal acceptability of CDR deployment also limit the conceivable extent of temperature overshoot. Limits to our understanding of how the carbon cycle responds to net negative emissions increase the uncertainty about the effectiveness of CDR to decline temperatures after a peak. {2.2, 2.3, 2.6, 4.3.7}<br /> <br /> '''CDR deployed at scale is unproven, and reliance on such technology is a major risk in the ability to limit warming to 1.5°C. CDR is needed less in pathways with particularly strong emphasis on energy efficiency and low demand. The scale and type of CDR deployment varies widely across 1.5°C pathways, with different consequences for achieving sustainable development objectives (''high confidence'').''' Some pathways rely more on bioenergy with carbon capture and storage (BECCS), while others rely more on afforestation, which are the two CDR methods most often included in integrated pathways. Trade-offs with other sustainability objectives occur predominantly through increased land, energy, water and investment demand. Bioenergy use is substantial in 1.5°C pathways with or without BECCS due to its multiple roles in decarbonizing energy use. {2.3.1, 2.5.3, 2.6.3, 4.3.7}<br /> <br /> === Properties of Energy and Land Transitions in 1.5°C Pathways ===<br /> <br /> '''The share of primary energy from renewables increases while coal usage decreases across pathways limiting warming to 1.5°C with no or limited overshoot (''high confidence'').''' By 2050, renewables (including bioenergy, hydro, wind, and solar, with direct-equivalence method) supply a share of 52–67% (interquartile range) of primary energy in 1.5°C pathways with no or limited overshoot; while the share from coal decreases to 1–7% (interquartile range), with a large fraction of this coal use combined with carbon capture and storage (CCS). From 2020 to 2050 the primary energy supplied by oil declines in most pathways (−39 to −77% interquartile range). Natural gas changes by −13% to −62% (interquartile range), but some pathways show a marked increase albeit with widespread deployment of CCS. The overall deployment of CCS varies widely across 1.5°C pathways with no or limited overshoot, with cumulative CO&lt;sub&gt;2&lt;/sub&gt; stored through 2050 ranging from zero up to 300 GtCO&lt;sub&gt;2&lt;/sub&gt; (minimum–maximum range), of which zero up to 140 GtCO&lt;sub&gt;2&lt;/sub&gt; is stored from biomass. Primary energy supplied by bioenergy ranges from 40–310 EJ yr&lt;sup&gt;−1&lt;/sup&gt; in 2050 (minimum-maximum range), and nuclear from 3–66 EJ yr&lt;sup&gt;−1&lt;/sup&gt; (minimum–maximum range). These ranges reflect both uncertainties in technological development and strategic mitigation portfolio choices. {2.4.2}<br /> <br /> 1'''.5°C pathways with no or limited overshoot include a rapid decline in the carbon intensity of electricity and an increase in electrification of energy end use (high confidence).''' By 2050, the carbon intensity of electricity decreases to −92 to +11 gCO&lt;sub&gt;2&lt;/sub&gt;MJ&lt;sup&gt;−1&lt;/sup&gt; (minimum–maximum range) from about 140 gCO&lt;sub&gt;2&lt;/sub&gt;MJ&lt;sup&gt;−1&lt;/sup&gt; in 2020, and electricity covers 34–71% (minimum–maximum range) of final energy across 1.5°C pathways with no or limited overshoot from about 20% in 2020. By 2050, the share of electricity supplied by renewables increases to 59–97% (minimum-maximum range) across 1.5°C pathways with no or limited overshoot. Pathways with higher chances of holding warming to below 1.5°C generally show a faster decline in the carbon intensity of electricity by 2030 than pathways that temporarily overshoot 1.5°C. {2.4.1, 2.4.2, 2.4.3}<br /> <br /> '''Transitions in global and regional land use are found in all pathways limiting global warming to 1.5°C with no or limited overshoot, but their scale depends on the pursued mitigation portfolio (''high confidence'').''' Pathways that limit global warming to 1.5°C with no or limited overshoot project a 4 million km2reduction to a 2.5 million km2 increase of non-pasture agricultural land for food and feed crops and a 0.5–11 million km2reduction of pasture land, to be converted into 0-6 million km2of agricultural land for energy crops and a 2 million km2reduction to 9.5 million km2increase in forests by 2050 relative to 2010 (''medium confidence''). Land-use transitions of similar magnitude can be observed in modelled 2°C pathways (''medium confidence''). Such large transitions pose profound challenges for sustainable management of the various demands on land for human settlements, food, livestock feed, fibre, bioenergy, carbon storage, biodiversity and other ecosystem services (''high confidence''). {2.3.4, 2.4.4}<br /> <br /> === Demand-Side Mitigation and Behavioural Changes ===<br /> <br /> '''Demand-side measures are key elements of 1.5°C pathways. Lifestyle choices lowering energy demand and the land- and GHG-intensity of food consumption can further support achievement of 1.5°C pathways (''high confidence'').''' By 2030 and 2050, all end-use sectors (including building, transport, and industry) show marked energy demand reductions in modelled 1.5°C pathways, comparable and beyond those projected in 2°C pathways. Sectoral models support the scale of these reductions. {2.3.4, 2.4.3, 2.5.1}<br /> <br /> === Links between 1.5°C Pathways and Sustainable Development ===<br /> <br /> '''Choices about mitigation portfolios for limiting warming to 1.5°C can positively or negatively impact the achievement of other societal objectives, such as sustainable development (''high confidence''). In particular, demand-side and efficiency measures, and lifestyle choices that limit energy, resource, and GHG-intensive food demand support sustainable development (''medium confidence'').''' Limiting warming to 1.5°C can be achieved synergistically with poverty alleviation and improved energy security and can provide large public health benefits through improved air quality, preventing millions of premature deaths. However, specific mitigation measures, such as bioenergy, may result in trade-offs that require consideration. {2.5.1, 2.5.2, 2.5.3}<br /> <br /> == TS.3 Impacts of 1.5ºC Global Warming on Natural and Human Systems ==<br /> <br /> This chapter builds on findings of AR5 and assesses new scientific evidence of changes in the climate system and the associated impacts on natural and human systems, with a specific focus on the magnitude and pattern of risks linked for global warming of 1.5°C above temperatures in the pre-industrial period. Chapter 3 explores observed impacts and projected risks to a range of natural and human systems, with a focus on how risk levels change from 1.5°C to 2°C of global warming. The chapter also revisits major categories of risk (Reasons for Concern, RFC) based on the assessment of new knowledge that has become available since AR5.<br /> <br /> === 1.5°C and 2°C Warmer Worlds ===<br /> <br /> '''The global climate has changed relative to the pre-industrial period, and there are multiple lines of evidence that these changes have had impacts on organisms and ecosystems, as well as on human systems and well-being (''high confidence'').''' The increase in global mean surface temperature (GMST), which reached 0.87°C in 2006–2015 relative to 1850–1900, has increased the frequency and magnitude of impacts (''high confidence''), strengthening evidence of how an increase in GMST of 1.5°C or more could impact natural and human systems (1.5°C versus 2°C). {3.3, 3.4, 3.5, 3.6, Cross-Chapter Boxes 6, 7 and 8 in this chapter}<br /> <br /> '''Human-induced global warming has already caused multiple observed changes in the climate system (''high confidence'').''' Changes include increases in both land and ocean temperatures, as well as more frequent heatwaves in most land regions (''high confidence''). There is also ''high confidence'' that global warming has resulted in an increase in the frequency and duration of marine heatwaves. Further, there is substantial evidence that human-induced global warming has led to an increase in the frequency, intensity and/or amount of heavy precipitation events at the global scale (''medium confidence''), as well as an increased risk of drought in the Mediterranean region (''medium confidence''). {3.3.1, 3.3.2, 3.3.3, 3.3.4, Box 3.4}<br /> <br /> '''Trends in intensity and frequency of some climate and weather extremes have been detected over time spans during which about 0.5°C of global warming occurred (''medium confidence'').''' This assessment is based on several lines of evidence, including attribution studies for changes in extremes since 1950. {3.2, 3.3.1, 3.3.2, 3.3.3, 3.3.4}<br /> <br /> '''Several regional changes in climate are assessed to occur with global warming up to 1.5°C as compared to pre-industrial levels, including warming of extreme temperatures in many regions (''high confidence''),''' increases in frequency, intensity and/or amount of heavy precipitation in several regions (''high confidence''), and an increase in intensity or frequency of droughts in some regions (''medium confidence''). {3.3.1, 3.3.2, 3.3.3, 3.3.4, Table 3.2}<br /> <br /> '''There is no single ‘1.5°C warmer world’ (''high confidence'').''' In addition to the overall increase in GMST, it is important to consider the size and duration of potential overshoots in temperature. Furthermore, there are questions on how the stabilization of an increase in GMST of 1.5°C can be achieved, and how policies might be able to influence the resilience of human and natural systems, and the nature of regional and subregional risks. Overshooting poses large risks for natural and human systems, especially if the temperature at peak warming is high, because some risks may be long-lasting and irreversible, such as the loss of some ecosystems (''high confidence''). The rate of change for several types of risks may also have relevance, with potentially large risks in the case of a rapid rise to overshooting temperatures, even if a decrease to 1.5°C can be achieved at the end of the 21st century or later (''medium confidence''). If overshoot is to be minimized, the remaining equivalent CO&lt;sub&gt;2&lt;/sub&gt; budget available for emissions is very small, which implies that large, immediate and unprecedented global efforts to mitigate greenhouse gases are required (''high confidence''). {3.2, 3.6.2, Cross-Chapter Box 8 in this chapter}<br /> <br /> '''Robust &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; global differences in temperature means and extremes are expected if global warming reaches 1.5°C versus 2°C above the pre-industrial levels (''high confidence'').''' For oceans, regional surface temperature means and extremes are projected to be higher at 2°C compared to 1.5°C of global warming (''high confidence''). Temperature means and extremes are also projected to be higher at 2°C compared to 1.5°C in most land regions, with increases being 2–3 times greater than the increase in GMST projected for some regions (''high confidence''). Robust increases in temperature means and extremes are also projected at 1.5°C compared to present-day values (''high confidence'') {3.3.1, 3.3.2}. There are decreases in the occurrence of cold extremes, but substantial increases in their temperature, in particular in regions with snow or ice cover (''high confidence'') {3.3.1}.<br /> <br /> '''Climate models project robust &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; differences in regional climate between present-day and global warming up to 1.5°C &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt;, and between 1.5°C and 2°C &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; ''(high confidence)'', depending on the variable and region in question''(high confidence).''Large, robust and widespread differences are expected for temperature extremes (''high confidence'').''' Regarding hot extremes, the strongest warming is expected to occur at mid-latitudes in the warm season (with increases of up to 3°C for 1.5°C of global warming, i.e., a factor of two) and at high latitudes in the cold season (with increases of up to 4.5°C at 1.5°C of global warming, i.e., a factor of three) (high confidence). The strongest warming of hot extremes is projected to occur in central and eastern North America, central and southern Europe, the Mediterranean region (including southern Europe, northern Africa and the Near East), western and central Asia, and southern Africa (''medium confidence''). The number of exceptionally hot days are expected to increase the most in the tropics, where interannual temperature variability is lowest; extreme heatwaves are thus projected to emerge earliest in these regions, and they are expected to already become widespread there at 1.5°C global warming (''high confidence''). Limiting global warming to 1.5°C instead of 2°C could result in around 420 million fewer people being frequently exposed to extreme heatwaves, and about 65 million fewer people being exposed to exceptional heatwaves, assuming constant vulnerability (''medium confidence''). {3.3.1, 3.3.2, Cross-Chapter Box 8 in this chapter}<br /> <br /> '''Limiting global warming to 1.5°C would limit risks of increases in heavy precipitation events on a global scale and in several regions compared to conditions at 2°C global warming (''medium confidence'').''' The regions with the largest increases in heavy precipitation events for 1.5°C to 2°C global warming include: several high-latitude regions (e.g. Alaska/western Canada, eastern Canada/ Greenland/Iceland, northern Europe and northern Asia); mountainous regions (e.g.,Tibetan Plateau); eastern Asia (including China and Japan); and eastern North America (''medium confidence''). Tropical cyclones are projected to decrease in frequency but with an increase in the number of very intense cyclones (''limited evidence, low confidence''). Heavy precipitation associated with tropical cyclones is projected to be higher at 2°C compared to 1.5°C of global warming (''medium confidence''). Heavy precipitation, when aggregated at a global scale, is projected to be higher at 2°C than at 1.5°C of global warming (''medium confidence'')<br /> {3.3.3, 3.3.6}<br /> <br /> '''Limiting global warming to 1.5°C is expected to substantially reduce the probability of extreme drought, precipitation deficits, and risks associated with water availability (i.e., water stress) in some regions (''medium confidence'').''' In particular, risks associated with increases in drought frequency and magnitude are projected to be substantially larger at 2°C than at 1.5°C in the Mediterranean region (including southern Europe, northern Africa and the Near East) and southern Africa (''medium confidence''). {3.3.3, 3.3.4, Box 3.1, Box 3.2}<br /> <br /> '''Risks to natural and human systems are expected to be lower at 1.5°C than at 2°C of global warming (''high confidence'').''' This difference is due to the smaller rates and magnitudes of climate change associated with a 1.5°C temperature increase, including lower frequencies and intensities of temperature-related extremes. Lower rates of change enhance the ability of natural and human systems to adapt, with substantial benefits for a wide range of terrestrial, freshwater, wetland, coastal and ocean ecosystems (including coral reefs) (''high confidence''), as well as food production systems, human health, and tourism (''medium confidence''), together with energy systems and transportation (''low confidence''). {3.3.1, 3.4}<br /> <br /> '''Exposure to multiple and compound climate-related risks is projected to increase between 1.5°C and 2°C of global warming''' with greater proportions of people both exposed and susceptible to poverty in Africa and Asia (''high confidence''). For global warming from 1.5°C to 2°C, risks across energy, food, and water sectors could overlap spatially and temporally, creating new – and exacerbating current – hazards, exposures, and vulnerabilities that could affect increasing numbers of people and regions (''medium confidence''). Small island states and economically disadvantaged populations are particularly at risk (''high confidence''). {3.3.1, 3.4.5.3, 3.4.5.6, 3.4.11, 3.5.4.9, Box 3.5}<br /> <br /> '''Global warming of 2°C would lead to an expansion of areas with significant increases in runoff, as well as those affected by flood hazard, compared to conditions at 1.5°C (''medium confidence'').''' Global warming of 1.5°C would also lead to an expansion of the global land area with significant increases in runoff (''medium confidence'') and an increase in flood hazard in some regions (''medium confidence'') compared to present-day conditions. {3.3.5}<br /> <br /> '''The probability of a sea-ice-free Arctic Ocean &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; during summer is substantially higher at 2°C compared to 1.5°C of global warming (''medium confidence'').''' Model simulations suggest that at least one sea-ice-free Arctic summer is expected every 10 years for global warming of 2°C, with the frequency decreasing to one sea-ice-free Arctic summer every 100 years under 1.5°C (''medium confidence''). An intermediate temperature overshoot will have no long-term consequences for Arctic sea ice coverage, and hysteresis is not expected (''high confidence''). {3.3.8, 3.4.4.7}<br /> <br /> '''Global mean sea level rise (GMSLR) is projected to be around 0.1 m (0.04 – 0.16 m) less by the end of the 21st century in a 1.5°C warmer world compared to a 2°C warmer world (''medium confidence'').''' Projected GMSLR for 1.5°C of global warming has an indicative range of 0.26 – 0.77m, relative to 1986–2005, (''medium confidence''). A smaller sea level rise could mean that up to 10.4 million fewer people (based on the 2010 global population and assuming no adaptation) would be exposed to the impacts of sea level rise globally in 2100 at 1.5°C compared to at 2°C. A slower rate of sea level rise enables greater opportunities for adaptation (''medium confidence''). There is ''high confidence'' that sea level rise will continue beyond 2100. Instabilities exist for both the Greenland and Antarctic ice sheets, which could result in multi-meter rises in sea level on time scales of century to millennia. There is ''medium confidence'' that these instabilities could be triggered at around 1.5°C to 2°C of global warming. {3.3.9, 3.4.5, 3.6.3}<br /> <br /> '''The ocean has absorbed about 30% of the anthropogenic carbon dioxide, resulting in ocean acidification and changes to carbonate chemistry that are unprecedented for at least the last 65 million years (''high confidence'').''' Risks have been identified for the survival, calcification, growth, development and abundance of a broad range of marine taxonomic groups, ranging from algae to fish, with substantial evidence of predictable trait-based sensitivities (''high confidence''). There are multiple lines of evidence that ocean warming and acidification corresponding to 1.5°C of global warming would impact a wide range of marine organisms and ecosystems, as well as sectors such as aquaculture and fisheries (''high confidence''). {3.3.10, 3.4.4}<br /> <br /> '''Larger risks are expected for many regions and systems for global warming at 1.5°C, as compared to today,''' with adaptation required now and up to 1.5°C. However, risks would be larger at 2°C of warming and an even greater effort would be needed for adaptation to a temperature increase of that magnitude (''high confidence''). {3.4, Box 3.4, Box 3.5, Cross-Chapter Box 6 in this chapter}<br /> <br /> '''Future risks at 1.5°C of global warming will depend on the mitigation pathway and on the possible occurrence of a transient overshoot (''high confidence'').''' The impacts on natural and human systems would be greater if mitigation pathways temporarily overshoot 1.5°C and return to 1.5°C later in the century, as compared to pathways that stabilize at 1.5°C without an overshoot (''high confidence''). The size and duration of an overshoot would also affect future impacts (e.g., irreversible loss of some ecosystems) (''high confidence''). Changes in land use resulting from mitigation choices could have impacts on food production and ecosystem diversity. {3.6.1, 3.6.2, Cross-Chapter Boxes 7 and 8 in this chapter}<br /> <br /> === Climate Change Risks for Natural and Human systems ===<br /> <br /> ==== Terrestrial and Wetland Ecosystems ====<br /> <br /> '''Risks of local species losses and, consequently, risks of extinction are much less in a 1.5°C versus a 2°C warmer world (''high confidence'').''' The number of species projected to lose over half of their climatically determined geographic range at 2°C global warming (18% of insects, 16% of plants, 8% of vertebrates) is projected to be reduced to 6% of insects, 8% of plants and 4% of vertebrates at 1.5°C warming (''medium confidence''). Risks associated with other biodiversity-related factors, such as forest fires, extreme weather events, and the spread of invasive species, pests and diseases, would also be lower at 1.5°C than at 2°C of warming (''high confidence''), supporting a greater persistence of ecosystem services. {3.4.3, 3.5.2}<br /> <br /> '''Constraining global warming to 1.5°C, rather than to 2°C and higher, is projected to have many benefits for terrestrial and wetland ecosystems and for the preservation of their services to humans (''high confidence'').''' Risks for natural and managed ecosystems are higher on drylands compared to humid lands. The global terrestrial land area projected to be affected by ecosystem transformations (13%, interquartile range 8–20%) at 2°C is approximately halved at 1.5°C global warming to 4% (interquartile range 2–7%) (''medium confidence''). Above 1.5°C, an expansion of desert terrain and vegetation would occur in the Mediterranean biome (''medium confidence''), causing changes unparalleled in the last 10,000 years (''medium confidence''). {3.3.2.2, 3.4.3.2, 3.4.3.5, 3.4.6.1, 3.5.5.10, Box 4.2}<br /> <br /> '''Many impacts are projected to be larger at higher latitudes, owing to mean and cold-season warming rates above the global average (''medium confidence'').''' High-latitude tundra and boreal forest are particularly at risk, and woody shrubs are already encroaching into tundra (''high confidence'') and will proceed with further warming. Constraining warming to 1.5°C would prevent the thawing of an estimated permafrost area of 1.5 to 2.5 million km2over centuries compared to thawing under 2°C (''medium confidence''). {3.3.2, 3.4.3, 3.4.4}<br /> <br /> ==== Ocean Ecosystems ====<br /> <br /> '''Ocean ecosystems are already experiencing large-scale changes, and critical thresholds are expected to be reached at 1.5°C and higher levels of global warming (''high confidence'').''' In the transition to 1.5°C of warming, changes to water temperatures are expected to drive some species (e.g., plankton, fish) to relocate to higher latitudes and cause novel ecosystems to assemble (''high confidence''). Other ecosystems (e.g., kelp forests, coral reefs) are relatively less able to move, however, and are projected to experience high rates of mortality and loss (''very high confidence''). For example, multiple lines of evidence indicate that the majority (70–90%) of warm water (tropical) coral reefs that exist today will disappear even if global warming is constrained to 1.5°C (''very high confidence''). {3.4.4, Box 3.4}<br /> <br /> '''Current ecosystem services from the ocean are expected to be reduced at 1.5°C of global warming, with losses being even greater at 2°C of global warming (''high confidence'').''' The risks of declining ocean productivity, shifts of species to higher latitudes, damage to ecosystems (e.g., coral reefs, and mangroves, seagrass and other wetland ecosystems), loss of fisheries productivity (at low latitudes), and changes to ocean chemistry (e.g., acidification, hypoxia and dead zones) are projected to be substantially lower when global warming is limited to 1.5°C (''high confidence''). {3.4.4, Box 3.4}<br /> <br /> ==== Water Resources ====<br /> <br /> '''The projected frequency and magnitude of floods and droughts in some regions are smaller under 1.5°C than under 2°C of warming (''medium confidence'').''' Human exposure to increased flooding is projected to be substantially lower at 1.5°C compared to 2°C of global warming, although projected changes create regionally differentiated risks (''medium confidence''). The differences in the risks among regions are strongly influenced by local socio-economic conditions (''medium confidence''). {3.3.4, 3.3.5, 3.4.2}<br /> <br /> '''Risks of water scarcity are projected to be greater at 2°C than at 1.5°C of global warming in some regions (''medium confidence'').''' Depending on future socio-economic conditions, limiting global warming to 1.5°C, compared to 2°C, may reduce the proportion of the world population exposed to a climate change-induced increase in water stress by up to 50%, although there is considerable variability between regions (''medium confidence''). Regions with particularly large benefits could include the Mediterranean and the Caribbean (''medium confidence''). Socio-economic drivers, however, are expected to have a greater influence on these risks than the changes in climate (''medium confidence''). {3.3.5, 3.4.2, Box 3.5}<br /> <br /> ==== Land Use, Food Security and Food Production Systems ====<br /> <br /> '''Limiting global warming to 1.5°C, compared with 2°C, is projected to result in smaller net reductions in yields of maize, rice, wheat, and potentially other cereal crops,''' particularly in sub-Saharan Africa, Southeast Asia, and Central and South America; and in the CO&lt;sub&gt;2&lt;/sub&gt;-dependent nutritional quality of rice and wheat (''high confidence''). A loss of 7–10% of rangeland livestock globally is projected for approximately 2°C of warming, with considerable economic consequences for many communities and regions (''medium confidence''). {3.4.6, 3.6, Box 3.1, Cross-Chapter Box 6 in this chapter}<br /> <br /> '''Reductions in projected food availability are larger at 2°C than at 1.5°C of global warming in the Sahel, southern Africa, the Mediterranean, central Europe and the Amazon (''medium confidence'').''' This suggests a transition from medium to high risk of regionally differentiated impacts on food security between 1.5°C and 2°C (''medium confidence''). Future economic and trade environments and their response to changing food availability (''medium confidence'') are important potential adaptation options for reducing hunger risk in low- and middle-income countries. {Cross-Chapter Box 6 in this chapter}<br /> <br /> '''Fisheries and aquaculture are important to global food security but are already facing increasing risks from ocean warming and acidification''(medium confidence)''. These risks are projected to increase at 1.5°C of global warming and impact key organisms such as fin fish and bivalves (e.g., oysters), especially at low latitudes (''medium confidence'').''' Small-scale fisheries in tropical regions, which are very dependent on habitat provided by coastal ecosystems such as coral reefs, mangroves, seagrass and kelp forests, are expected to face growing risks at 1.5°C of warming because of loss of habitat (''medium confidence''). Risks of impacts and decreasing food security are projected to become greater as global warming reaches beyond 1.5°C and both ocean warming and acidification increase, with substantial losses likely for coastal livelihoods and industries (e.g., fisheries and aquaculture) (''medium to high confidence''). {3.4.4, 3.4.5, 3.4.6, Box 3.1, Box 3.4, Box 3.5, Cross-Chapter Box 6 in this chapter}<br /> <br /> '''Land use and land-use change emerge as critical features of virtually all mitigation pathways that seek to limit global warming to 1.5°C (''high confidence'').''' Most least-cost mitigation pathways to limit peak or end-of-century warming to 1.5°C make use of carbon dioxide removal (CDR), predominantly employing significant levels of bioenergy with carbon capture and storage (BECCS) and/or afforestation and reforestation (AR) in their portfolio of mitigation measures (''high confidence''). {Cross-Chapter Box 7 in this chapter}<br /> <br /> '''Large-scale deployment of BECCS and/or AR would have a far-reaching land and water footprint (''high confidence'').''' Whether this footprint would result in adverse impacts, for example on biodiversity or food production, depends on the existence and effectiveness of measures to conserve land carbon stocks, measures to limit agricultural expansion in order to protect natural ecosystems, and the potential to increase agricultural productivity (''medium agreement''). In addition, BECCS and/or AR would have substantial direct effects on regional climate through biophysical feedbacks, which are generally not included in Integrated Assessments Models (''high confidence''). {3.6.2, Cross-Chapter Boxes 7 and 8 in this chapter}<br /> <br /> '''The impacts of large-scale CDR deployment could be greatly reduced if a wider portfolio of CDR options were deployed, if a holistic policy for sustainable land management were adopted, and if increased mitigation efforts were employed to strongly limit the demand for land, energy and material resources, including through lifestyle and dietary changes (''medium confidence'').''' In particular, reforestation could be associated with significant co-benefits if implemented in a manner than helps restore natural ecosystems (''high confidence''). {Cross-Chapter Box 7 in this chapter}<br /> <br /> ==== Human Health, Well-Being, Cities and Poverty ====<br /> <br /> '''Any increase in global temperature (e.g., +0.5°C) is projected to affect human health, with primarily negative consequences (''high confidence'').''' Lower risks are projected at 1.5°C than at 2°C for heat-related morbidity and mortality (''very high confidence''), and for ozone-related mortality if emissions needed for ozone formation remain high (''high confidence''). Urban heat islands often amplify the impacts of heatwaves in cities (''high confidence''). Risks for some vector-borne diseases, such as malaria and dengue fever are projected to increase with warming from 1.5°C to 2°C, including potential shifts in their geographic range (''high confidence''). Overall for vector-borne diseases, whether projections are positive or negative depends on the disease, region and extent of change (''high confidence''). Lower risks of undernutrition are projected at 1.5°C than at 2°C (''medium confidence''). Incorporating estimates of adaptation into projections reduces the magnitude of risks (''high confidence''). {3.4.7, 3.4.7.1, 3.4.8, 3.5.5.8}<br /> <br /> '''Global warming of 2°C is expected to pose greater risks to urban areas than global warming of 1.5°C (''medium confidence'').''' The extent of risk depends on human vulnerability and the effectiveness of adaptation for regions (coastal and non-coastal), informal settlements and infrastructure sectors (such as energy, water and transport) (''high confidence''). {3.4.5, 3.4.8}<br /> <br /> '''Poverty and disadvantage have increased with recent warming (about 1°C) and are expected to increase for many populations as average global temperatures increase from 1°C to 1.5°C and higher (''medium confidence'').''' Outmigration in agricultural-dependent communities is positively and statistically significantly associated with global temperature (medium confidence). Our understanding of the links of 1.5°C and 2°C of global warming to human migration are limited and represent an important knowledge gap. {3.4.10, 3.4.11, 5.2.2, Table 3.5}<br /> <br /> ==== Key Economic Sectors and Services ====<br /> <br /> '''Risks to global aggregated economic growth due to climate change impacts are projected to be lower at 1.5°C than at 2°C by the end of this century (''medium confidence'').''' {3.5.2, 3.5.3}<br /> <br /> '''The largest reductions in economic growth at 2°C compared to 1.5°C of warming are projected for low- and middle-income countries and regions''' (the African continent, Southeast Asia, India, Brazil and Mexico) (''low to medium confidence''). Countries in the tropics and Southern Hemisphere subtropics are projected to experience the largest impacts on economic growth due to climate<br /> change should global warming increase from 1.5°C to 2°C (''medium confidence''). {3.5}<br /> <br /> '''Global warming has already affected tourism, with increased risks projected under 1.5°C of warming in specific geographic regions and for seasonal tourism including sun, beach and snow sports destinations (''very high confidence'').''' Risks will be lower for tourism markets that are less climate sensitive, such as gaming and large hotel-based activities (''high confidence''). Risks for coastal tourism, particularly in subtropical and tropical regions, will increase with temperature-related degradation (e.g., heat extremes, storms) or loss of beach and coral reef assets (''high confidence''). {3.3.6, 3.4.4.12, 3.4.9.1, Box 3.4}<br /> <br /> ==== Small Islands, and Coastal and Low-lying areas ====<br /> <br /> '''Small islands are projected to experience multiple inter-related risks at 1.5°C of global warming that will increase with warming of 2°C and higher levels (''high confidence'').''' Climate hazards at 1.5°C are projected to be lower compared to those at 2°C (''high confidence''). Long-term risks of coastal flooding and impacts on populations, infrastructures and assets (''high confidence''), freshwater stress (''medium confidence''), and risks across marine ecosystems (''high confidence'') and critical sectors (''medium confidence'') are projected to increase at 1.5°C compared to present-day levels and increase further at 2°C, limiting adaptation opportunities and increasing loss and damage (''medium confidence''). Migration in small islands (internally and internationally) occurs for multiple reasons and purposes, mostly for better livelihood opportunities (''high confidence'') and increasingly owing to sea level rise (''medium confidence''). {3.3.2.2, 3.3.6–9, 3.4.3.2, 3.4.4.2, 3.4.4.5, 3.4.4.12, 3.4.5.3, 3.4.7.1, 3.4.9.1, 3.5.4.9,<br /> Box 3.4, Box 3.5}<br /> <br /> '''Impacts associated with sea level rise and changes to the salinity of coastal groundwater, increased flooding and damage to infrastructure, are projected to be critically important in vulnerable environments, such as small islands, low-lying coasts and deltas, at global warming of 1.5°C and 2°C (''high confidence'').''' Localized subsidence and changes to river discharge can potentially exacerbate these effects. Adaptation is already happening (''high confidence'') and will remain important over multi-centennial time scales. {3.4.5.3, 3.4.5.4, 3.4.5.7, 5.4.5.4, Box 3.5}<br /> <br /> '''Existing and restored natural coastal ecosystems may be effective in reducing the adverse impacts of rising sea levels and intensifying storms by protecting coastal and deltaic regions (''medium confidence'').''' Natural sedimentation rates are expected to be able to offset the effect of rising sea levels, given the slower rates of sea level rise associated with 1.5°C of warming (''medium confidence''). Other feedbacks, such as landward migration of wetlands and the adaptation of infrastructure, remain important (''medium confidence''). {3.4.4.12, 3.4.5.4, 3.4.5.7}<br /> <br /> === Increased Reasons for Concern ===<br /> <br /> '''There are multiple lines of evidence that since AR5 the assessed levels of risk increased for four of the five Reasons for Concern (RFCs) for global warming levels of up to 2°C (''high confidence'').''' The risk transitions by degrees of global warming are now: from high to very high between 1.5°C and 2°C for RFC1 (Unique and threatened systems) (''high confidence''); from moderate to high risk between 1°C and 1.5°C for RFC2 (Extreme weather events) (''medium confidence''); from moderate to high risk between 1.5°C and 2°C for RFC3 (Distribution of impacts) (''high confidence''); from moderate to high risk between 1.5°C and 2.5°C for RFC4 (Global aggregate impacts) (''medium confidence''); and from moderate to high risk between 1°C and 2.5°C for RFC5 (Large-scale singular events) (''medium confidence''). {3.5.2}<br /> <br /> # '''The category ‘Unique and threatened systems’ (RFC1) display a transition from high to very high risk which is now located between 1.5°C and 2°C of global warming''' as opposed to at 2.6°C of global warming in AR5, owing to new and multiple lines of evidence for changing risks for coral reefs, the Arctic and biodiversity in general (''high confidence''). {3.5.2.1}<br /> # '''In ‘Extreme weather events’ (RFC2), the transition from moderate to high risk is now located between 1.0°C and 1.5°C of global warming,''' which is very similar to the AR5 assessment but is projected with greater confidence (''medium confidence''). The impact literature contains little information about the potential for human society to adapt to extreme weather events, and hence it has not been possible to locate the transition from ‘high’ to ‘very high’ risk within the context of assessing impacts at 1.5°C versus 2°C of global warming. There is thus ''low confidence'' in the level at which global warming could lead to very high risks associated with extreme weather events in the context of this report. {3.5}<br /> # '''With respect to the ‘Distribution of impacts’ (RFC3) a transition from moderate to high risk is now located between 1.5°C and 2°C of global warming,''' compared with between 1.6°C and 2.6°C global warming in AR5, owing to new evidence about regionally differentiated risks to food security, water resources, drought, heat exposure and coastal submergence (''high confidence''). {3.5}<br /> # '''In ‘global aggregate impacts’ (RFC4) a transition from moderate to high levels of risk is now located between 1.5°C and 2.5°C of global warming,''' as opposed to at 3.6°C of warming in AR5, owing to new evidence about global aggregate economic impacts and risks to Earth’s biodiversity (''medium confidence''). {3.5}<br /> # '''Finally, ‘large-scale singular events’ (RFC5), moderate risk is now located at 1°C of global warming and high risk is located at 2.5°C of global warming,''' as opposed to at 1.6°C (moderate risk) and around 4°C (high risk) in AR5, because of new observations and models of the West Antarctic ice sheet (''medium confidence''). {3.3.9, 3.5.2, 3.6.3}<br /> <br /> == TS.4 Strengthening and Implementing the Global Response == <br /> <br /> '''Limiting warming to 1.5°C above pre-industrial levels would require transformative systemic change, integrated with sustainable development. Such change would require the upscaling and acceleration of the implementation of far-reaching, multilevel and cross-sectoral climate mitigation and addressing barriers. Such systemic change would need to be linked to complementary adaptation actions, including transformational adaptation, especially for pathways that temporarily overshoot 1.5°C (''medium evidence, high agreement'') {Chapter 2, Chapter 3, 4.2.1, 4.4.5, 4.5}.''' Current national pledges on mitigation and adaptation are not enough to stay below the Paris Agreement temperature limits and achieve its adaptation goals. While transitions in energy efficiency, carbon intensity of fuels, electrification and land-use change are underway in various countries, limiting warming to 1.5°C will require a greater scale and pace of change to transform energy, land, urban and industrial systems globally. {4.3, 4.4, Cross-Chapter Box 9 in this Chapter}<br /> <br /> '''Although multiple communities around the world are demonstrating the possibility of implementation consistent with<br /> 1.5°C pathways {Boxes 4.1-4.10}, very few countries, regions, cities, communities or businesses can currently make such a claim (''high confidence''). To strengthen the global response, almost all countries would need to significantly raise their level of ambition. Implementation of this raised ambition would require enhanced institutional capabilities in all countries, including building the capability to utilize indigenous and local knowledge(''medium evidence, high agreement'').''' In developing countries and for poor and vulnerable people, implementing the response would require financial, technological and other forms of support to build capacity, for which additional local, national and international resources would need to be mobilized (''high confidence''). However, public, financial, institutional and innovation capabilities currently fall short of implementing far-reaching measures at scale in all countries (''high confidence''). Transnational networks that support multilevel climate action are growing, but challenges in their scale-up remain. {4.4.1, 4.4.2, 4.4.4, 4.4.5, Box 4.1, Box 4.2, Box 4.7}<br /> <br /> '''Adaptation needs will be lower in a 1.5°C world compared to a 2°C world (''high confidence'') {Chapter 3; Cross-Chapter Box 11 in this chapter}.''' Learning from current adaptation practices and strengthening them through adaptive governance {4.4.1}, lifestyle and behavioural change {4.4.3} and innovative financing mechanisms {4.4.5} can help their mainstreaming within sustainable development practices. Preventing maladaptation, drawing on bottom-up approaches {Box 4.6} and using indigenous knowledge {Box 4.3} would effectively engage and protect vulnerable people and communities. While adaptation finance has increased quantitatively, significant further expansion would be needed to adapt to 1.5°C. Qualitative gaps in the distribution of adaptation finance, readiness to absorb resources, and monitoring mechanisms undermine the potential of adaptation finance to reduce impacts. {Chapter 3, 4.4.2, 4.4.5, 4.6}<br /> <br /> === System Transitions ===<br /> <br /> '''The energy system transition that would be required to limit global warming to 1.5°C above pre-industrial conditions is underway in many sectors and regions around the world (''medium evidence, high agreement'').''' The political, economic, social and technical feasibility of solar energy, wind energy and electricity storage technologies has improved dramatically over the past few years, while that of nuclear energy and carbon dioxide capture and storage (CCS) in the electricity sector have not shown similar improvements. {4.3.1}<br /> <br /> '''Electrification, hydrogen, bio-based feedstocks and substitution, and, in several cases, carbon dioxide capture, utilization and storage (CCUS) would lead to the deep emissions reductions required in energy-intensive industries to limit warming to<br /> 1.5°C.''' However, those options are limited by institutional, economic and technical constraints, which increase financial risks to many incumbent firms (''medium evidence, high agreement''). Energy efficiency in industry is more economically feasible and helps enable industrial system transitions but would have to be complemented with greenhouse gas (GHG)-neutral processes or carbon dioxide removal (CDR) to make energy-intensive industries consistent with 1.5°C (''high confidence'').<br /> {4.3.1, 4.3.4}<br /> <br /> '''Global and regional land-use and ecosystems transitions and associated changes in behaviour that would be required to limit warming to 1.5°C can enhance future adaptation and land-based agricultural and forestry mitigation potential. Such transitions could, however, carry consequences for livelihoods that depend on agriculture and natural resources {4.3.2, Cross-Chapter Box 6 in Chapter 3}.''' Alterations of agriculture and forest systems to achieve mitigation goals could affect current ecosystems and their services and potentially threaten food, water and livelihood security. While this could limit the social and environmental feasibility of land-based mitigation options, careful design and implementation could enhance their acceptability and support sustainable development objectives (''medium evidence, medium agreement''). {4.3.2, 4.5.3}<br /> <br /> '''Changing agricultural practices can be an effective climate adaptation strategy.''' A diversity of adaptation options exists, including mixed crop-livestock production systems which can be a cost-effective adaptation strategy in many global agriculture systems (''robust evidence, medium agreement''). Improving irrigation efficiency could effectively deal with changing global water endowments, especially if achieved via farmers adopting new behaviours and water-efficient practices rather than through large-scale infrastructural interventions (''medium evidence, medium agreement''). Well-designed adaptation processes such as community-based adaptation can be effective depending upon context and levels of vulnerability. {4.3.2, 4.5.3}<br /> <br /> '''Improving the efficiency of food production and closing yield gaps have the potential to reduce emissions from agriculture, reduce pressure on land, and enhance food security and future mitigation potential (''high confidence'').''' Improving productivity of<br /> existing agricultural systems generally reduces the emissions intensity of food production and offers strong synergies with rural development, poverty reduction and food security objectives, but options to reduce absolute emissions are limited unless paired with demand-side measures. Technological innovation including biotechnology, with adequate safeguards, could contribute to resolving current feasibility constraints and expand the future mitigation potential of agriculture.<br /> {4.3.2, 4.4.4}<br /> <br /> '''Shifts in dietary choices towards foods with lower emissions and requirements for land, along with reduced food loss and waste, could reduce emissions and increase adaptation options (''high confidence'').''' Decreasing food loss and waste and changing dietary behaviour could result in mitigation and adaptation (high confidence) by reducing both emissions and pressure on land, with significant co-benefits for food security, human health and sustainable development {4.3.2, 4.4.5, 4.5.2, 4.5.3, 5.4.2}, but evidence of successful policies to modify dietary choices remains limited.<br /> <br /> === Mitigation and Adaptation Options and Other Measures ===<br /> <br /> '''A mix of mitigation and adaptation options implemented in a participatory and integrated manner can enable rapid, systemic transitions – in urban and rural areas – that are necessary elements of an accelerated transition consistent with limiting warming to 1.5°C. Such options and changes are most effective when aligned with economic and sustainable development, and when local and regional governments are supported by national governments {4.3.3, 4.4.1, 4.4.3}.''' Various mitigation options are expanding rapidly across many geographies. Although many have development synergies, not all income groups have so far benefited from them. Electrification, end-use energy efficiency and increased share of renewables, amongst other options, are lowering energy use and decarbonizing energy supply in the built environment, especially in buildings. Other rapid changes needed in urban environments include demotorization and decarbonization of transport, including the expansion of electric vehicles, and greater use of energy-efficient appliances (''medium evidence, high agreement''). Technological and social innovations can contribute to limiting warming to 1.5°C, for example, by enabling the use of smart grids, energy storage technologies and general-purpose technologies, such as information and communication technology (ICT) that can be deployed to help reduce emissions. Feasible adaptation options include green infrastructure, resilient water and urban ecosystem services, urban and peri-urban agriculture, and adapting buildings and land use through regulation and planning (''medium evidence, medium to high agreement''). {4.3.3, 4.4.3, 4.4.4}<br /> <br /> '''Synergies can be achieved across systemic transitions through several overarching adaptation options in rural and urban areas.''' Investments in health, social security and risk sharing and spreading are cost-effective adaptation measures with high potential for scaling up (''medium evidence, medium to high agreement''). Disaster risk management and education-based adaptation have lower prospects of scalability and cost-effectiveness (''medium evidence, high agreement'') but are critical for building adaptive capacity. {4.3.5, 4.5.3}<br /> <br /> '''Converging adaptation and mitigation options can lead to synergies and potentially increase cost-effectiveness, but multiple trade-offs can limit the speed of and potential for scaling up.''' Many examples of synergies and trade-offs exist in all sectors and system transitions. For instance, sustainable water management (''high evidence, medium agreement'') and investment in green infrastructure (''medium evidence, high agreement'') to deliver sustainable water and environmental services and to support urban agriculture are less cost-effective than other adaptation options but can help build climate resilience. Achieving the governance, finance and social support required to enable these synergies and to avoid trade-offs is often challenging, especially when addressing multiple objectives, and attempting appropriate sequencing and timing of interventions. {4.3.2, 4.3.4, 4.4.1, 4.5.2, 4.5.3, 4.5.4}<br /> <br /> '''Though CO&lt;sub&gt;2&lt;/sub&gt; dominates long-term warming, the reduction of warming short-lived climate forcers (SLCFs), such as methane and black carbon, can in the short term contribute significantly to limiting warming to 1.5°C above pre-industrial levels. Reductions of black carbon and methane would have substantial co-benefits (''high confidence''), including improved health due to reduced air pollution. This, in turn, enhances the institutional and socio-cultural feasibility of such actions.''' Reductions of several warming SLCFs are constrained by economic and social feasibility (''low evidence, high agreement''). As they are often co-emitted with CO&lt;sub&gt;2&lt;/sub&gt;, achieving the energy, land and urban transitions necessary to limit warming to 1.5°C would see emissions of warming SLCFs greatly reduced. {2.3.3.2, 4.3.6}<br /> <br /> '''Most CDR options face multiple feasibility constraints, which differ between options, limiting the potential for any single option to sustainably achieve the large-scale deployment required in the 1.5°C-consistent pathways described in Chapter 2 (''high confidence'').''' Those 1.5°C pathways typically rely on bioenergy with carbon capture and storage (BECCS), afforestation and reforestation (AR), or both, to neutralize emissions that are expensive to avoid, or to draw down CO&lt;sub&gt;2&lt;/sub&gt; emissions in excess of the carbon budget {Chapter 2}. Though BECCS and AR may be technically and geophysically feasible, they face partially overlapping yet different constraints related to land use. The land footprint per tonne of CO&lt;sub&gt;2&lt;/sub&gt; removed is higher for AR than for BECCS, but given the low levels of current deployment, the speed and scales required for limiting warming to 1.5°C pose a considerable implementation challenge, even if the issues of public acceptance and absence of economic incentives were to be resolved (''high agreement, medium evidence''). The large potential of afforestation and the co-benefits if implemented appropriately (e.g., on biodiversity and soil quality) will diminish over time, as forests saturate (''high confidence''). The energy requirements and economic costs of direct air carbon capture and storage (DACCS) and enhanced weathering remain high (''medium evidence, medium agreement''). At the local scale, soil carbon sequestration has co-benefits with agriculture and is cost-effective even without climate policy (''high confidence''). Its potential feasibility and cost-effectiveness at the global scale appears to be more limited. {4.3.7}<br /> <br /> '''Uncertainties surrounding solar radiation modification (SRM) measures constrain their potential deployment.''' These uncertainties include: technological immaturity; limited physical understanding about their effectiveness to limit global warming; and a weak capacity to govern, legitimize, and scale such measures. Some recent model-based analysis suggests SRM would be effective but that it is too early to evaluate its feasibility. Even in the uncertain case that the most adverse side-effects of SRM can be avoided, public resistance, ethical concerns and potential impacts on sustainable development could render SRM economically, socially and institutionally undesirable (''low agreement, medium evidence''). {4.3.8, Cross-Chapter Box 10 in this chapter}<br /> <br /> === Enabling Rapid and Far-Reaching Change ===<br /> <br /> '''The speed of transitions and of technological change required to limit warming to 1.5°C above pre-industrial levels has been observed in the past within specific sectors and technologies {4.2.2.1}. But the geographical and economic scales at which the required rates of change in the energy, land, urban, infrastructure and industrial systems would need to take place are larger and have no documented historic precedent (''limited evidence, medium agreement'').''' To reduce inequality and alleviate poverty, such transformations would require more planning and stronger institutions (including inclusive markets) than observed in the past, as well as stronger coordination and disruptive innovation across actors and scales of governance. {4.3, 4.4}<br /> <br /> '''Governance consistent with limiting warming to 1.5°C and the political economy of adaptation and mitigation can enable and acceleratesystemstransitions,behaviouralchange,innovationand technology deployment (''medium evidence, medium agreement'').''' For 1.5°C-consistent actions, an effective governance framework would include: accountable multilevel governance that includes non-state actors, such as industry, civil society and scientific institutions; coordinated sectoral and cross-sectoral policies that enable collaborative multi-stakeholder partnerships; strengthened global-to-local financial architecture that enables greater access to finance and technology; addressing climate-related trade barriers; improved climate education and greater public awareness; arrangements to enable accelerated behaviour change; strengthened climate monitoring and evaluation systems; and reciprocal international agreements that are sensitive to equity and the Sustainable Development Goals (SDGs). System transitions can be enabled by enhancing the capacities of public, private and financial institutions to accelerate climate change policy planning and implementation, along with accelerated technological innovation, deployment and upkeep. {4.4.1, 4.4.2, 4.4.3, 4.4.4}<br /> <br /> '''Behaviour change and demand-side management can significantly reduce emissions, substantially limiting the reliance on CDR to limit warming to 1.5°C {Chapter 2, 4.4.3}.''' Political and financial stakeholders may find climate actions more cost-effective and socially acceptable if multiple factors affecting behaviour are considered, including aligning these actions with people’s core values (''medium evidence, high agreement''). Behaviour- and lifestyle-related measures and demand-side management have already led to emission reductions around the world and can enable significant future reductions (''high confidence''). Social innovation through bottom-up initiatives can result in greater participation in the governance of systems transitions and increase support for technologies, practices and policies that are part of the global response to limit warming to 1.5°C . {Chapter 2, 4.4.1, 4.4.3, Figure 4.3}<br /> <br /> '''This rapid and far-reaching response required to keep warming below 1.5°C and enhance the capacity to adapt to climate risks would require large increases of investments in low-emission infrastructure and buildings, along with a redirection of financial flows towards low-emission investments (''robust evidence, high agreement'').''' An estimated mean annual incremental investment of around 1.5% of global gross fixed capital formation (GFCF) for the energy sector is indicated between 2016 and 2035, as well as about 2.5% of global GFCF for other development infrastructure that could also address SDG implementation. Though quality policy design and effective implementation may enhance efficiency, they cannot fully substitute for these investments. {2.5.2, 4.2.1, 4.4.5}<br /> <br /> '''Enabling this investment requires the mobilization and better integration of a range of policy instruments''' that include the reduction of socially inefficient fossil fuel subsidy regimes and innovative price and non-price national and international policy instruments. These would need to be complemented by de-risking financial instruments and the emergence of long-term low-emission assets. These instruments would aim to reduce the demand for carbon-intensive services and shift market preferences away from fossil fuel-based technology. Evidence and theory suggest that carbon pricing alone, in the absence of sufficient transfers to compensate their unintended distributional cross-sector, cross-nation effects, cannot reach the incentive levels needed to trigger system transitions (''robust evidence, medium agreement''). But, embedded in consistent policy packages, they can help mobilize incremental resources and provide flexible mechanisms that help reduce the social and economic costs of the triggering phase of the transition (''robust evidence, medium agreement''). {4.4.3, 4.4.4, 4.4.5}<br /> <br /> '''Increasing evidence suggests that a climate-sensitive realignment of savings and expenditure towards low-emission, climate-resilient infrastructure and services requires an evolution of global and national financial systems.''' Estimates suggest that, in addition to climate-friendly allocation of public investments, a potential redirection of 5% to 10% of the annual capital revenues &lt;sup&gt;[[#fn:5|5]]&lt;/sup&gt; is necessary for limiting warming to 1.5°C {4.4.5, Table 1 in Box 4.8}. This could be facilitated by a change of incentives for private day-to-day expenditure and the redirection of savings from speculative and precautionary investments towards long-term productive low-emission assets and services. This implies the mobilization of institutional investors and mainstreaming of climate finance within financial and banking system regulation. Access by developing countries to low-risk and low-interest finance through multilateral and national development banks would have to be facilitated (''medium evidence, high agreement''). New forms of public–private partnerships may be needed with multilateral, sovereign and sub-sovereign guarantees to de-risk climate-friendly investments, support new business models for small-scale enterprises and help households with limited access to capital. Ultimately, the aim is to promote a portfolio shift towards long-term low-emission assets that would help redirect capital away from potentially stranded assets (''medium evidence, medium agreement''). {4.4.5}<br /> <br /> === Knowledge Gaps ===<br /> <br /> '''Knowledge gaps around implementing and strengthening the global response to climate change would need to be urgently resolved if the transition to a 1.5°C world is to become reality.''' Remaining questions include: how much can be realistically expected from innovation and behavioural and systemic political and economic changes in improving resilience, enhancing adaptation and reducing GHG emissions? How can rates of changes be accelerated and scaled up? What is the outcome of realistic assessments of mitigation and adaptation land transitions that are compliant with sustainable development, poverty eradication and addressing inequality? What are life-cycle emissions and prospects of early-stage CDR options? How can climate and sustainable development policies converge, and how can they be organised within a global governance framework and financial system, based on principles of justice and ethics (including ‘common but differentiated responsibilities and respective capabilities’ (CBDR-RC)), reciprocity and partnership? To what extent would limiting warming to 1.5°C require a harmonization of macro-financial and fiscal policies, which could include financial regulators such as central banks? How can different actors and processes in climate governance reinforce each other, and hedge against the fragmentation of initiatives? {4.1, 4.3.7, 4.4.1, 4.4.5, 4.6}<br /> <br /> == TS.5 Sustainable Development, Poverty Eradication and Reducing Inequalities == <br /> <br /> This chapter takes sustainable development as the starting point and focus for analysis. It considers the broad and multifaceted bi-directional interplay between sustainable development, including its focus on eradicating poverty and reducing inequality in their multidimensional aspects, and climate actions in a 1.5°C warmer world.These fundamental connections are embedded in the Sustainable Development Goals (SDGs). The chapter also examines synergies and trade-offs of adaptation and mitigation options with sustainable development and the SDGs and offers insights into possible pathways, especially climate-resilient development pathways towards a 1.5°C warmer world.<br /> <br /> === Sustainable Development, Poverty and Inequality in a 1.5°C Warmer World ===<br /> <br /> '''Limiting global warming to 1.5°C rather than 2°C above pre-industrial levels would make it markedly easier to achieve many aspects of sustainable development, with greater potential to eradicate poverty and reduce inequalities (''medium evidence, high agreement'').''' Impacts avoided with the lower temperature limit could reduce the number of people exposed to climate risks and vulnerable to poverty by 62 to 457 million, and lessen the risks of poor people to experience food and water insecurity, adverse health impacts, and economic losses, particularly in regions that already face development challenges (medium evidence, medium agreement). {5.2.2, 5.2.3} Avoided impacts expected to occur between 1.5°C and 2°C warming would also make it easier to achieve certain SDGs, such as those that relate to poverty, hunger, health, water and sanitation, cities and ecosystems (SDGs 1, 2, 3, 6, 11, 14 and 15) (''medium evidence, high agreement''). {5.2.3, Table 5.2 available at the end of the chapter}<br /> <br /> '''Compared to current conditions, 1.5°C of global warming would nonetheless pose heightened risks to eradicating poverty, reducing inequalities and ensuring human and ecosystem well-being (medium evidence, high agreement).''' Warming of 1.5°C is not considered ‘safe’ for most nations, communities, ecosystems and sectors and poses significant risks to natural and human systems as compared to the current warming of 1°C (''high confidence''). {Cross-Chapter Box 12 in Chapter 5} The impacts of 1.5°C of warming would disproportionately affect disadvantaged and vulnerable populations through food insecurity, higher food prices, income losses, lost livelihood opportunities, adverse health impacts and population displacements (''medium evidence, high agreement''). {5.2.1} Some of the worst impacts on sustainable development are expected to be felt among agricultural and coastal dependent livelihoods, indigenous people, children and the elderly, poor labourers, poor urban dwellers in African cities, and people and ecosystems in the Arctic and Small Island Developing States (SIDS) (''medium evidence, high agreement''). {5.2.1, Box 5.3, Chapter 3, Box 3.5, Cross-Chapter Box 9 in Chapter 4}<br /> <br /> === Climate Adaptation and Sustainable Development ===<br /> <br /> '''Prioritization of sustainable development and meeting the SDGs is consistent with efforts to adapt to climate change (''high confidence'').''' Many strategies for sustainable development enable transformational adaptation for a 1.5°C warmer world, provided attention is paid to reducing poverty in all its forms and to promoting equity and participation in decision-making (''medium evidence, high agreement''). As such, sustainable development has the potential to significantly reduce systemic vulnerability, enhance adaptive capacity, and promote livelihood security for poor and disadvantaged populations (''high confidence''). {5.3.1}<br /> <br /> '''Synergies between adaptation strategies and the SDGs are expected to hold true in a 1.5°C warmer world, across sectors and contexts (''medium evidence, medium agreement'').''' Synergies between adaptation and sustainable development are significant for agriculture and health, advancing SDGs 1 (extreme poverty), 2 (hunger), 3 (healthy lives and well-being) and 6 (clean water) (''robust evidence, medium agreement''). {5.3.2} Ecosystem- and community-based adaptation, along with the incorporation of indigenous and local knowledge, advances synergies with SDGs 5 (gender equality), 10 (reducing inequalities) and 16 (inclusive societies), as exemplified in drylands and the Arctic (''high evidence, medium agreement''). {5.3.2, Box 5.1, Cross-Chapter Box 10 in Chapter 4}<br /> <br /> '''Adaptation strategies can result in trade-offs with and among the SDGs (''medium evidence, high agreement'').''' Strategies that advance one SDG may create negative consequences for other SDGs, for instance SDGs 3 (health) versus 7 (energy consumption) and agricultural adaptation and SDG 2 (food security) versus SDGs 3 (health), 5 (gender equality), 6 (clean water), 10 (reducing inequalities), 14 (life below water) and 15 (life on the land) (''medium evidence, medium agreement''). {5.3.2}<br /> <br /> '''Pursuing place-specific adaptation pathways towards a 1.5°C warmer world has the potential for significant positive outcomes for well-being in countries at all levels of development (''medium evidence, high agreement'').''' Positive outcomes emerge when adaptation pathways (i) ensure a diversity of adaptation options based on people’s values and the trade-offs they consider acceptable, (ii) maximize synergies with sustainable development through inclusive, participatory and deliberative processes, and (iii) facilitate equitable transformation. Yet such pathways would be difficult to achieve without redistributive measures to overcome path dependencies, uneven power structures, and entrenched social inequalities (''medium evidence, high agreement''). {5.3.3}<br /> <br /> === Mitigation and Sustainable Development ===<br /> <br /> '''The deployment of mitigation options consistent with 1.5°C pathways leads to multiple synergies across a range of sustainable development dimensions. At the same time, the rapid pace and magnitude of change that would be required to limit warming to 1.5°C, if not carefully managed, would lead to trade-offs with some sustainable development dimensions (''high confidence'').''' The number of synergies between mitigation response options and sustainable development exceeds the number of trade-offs in energy demand and supply sectors; agriculture, forestry and other land use (AFOLU); and for oceans (very high confidence). {Figure 5.2, Table 5.2 available at the end of the chapter} The 1.5°C pathways indicate robust synergies, particularly for the SDGs 3 (health), 7 (energy), 12 (responsible consumption and production) and 14 (oceans) (''very high confidence''). {5.4.2, Figure 5.3} For SDGs 1 (poverty), 2 (hunger), 6 (water) and 7 (energy), there is a risk of trade-offs or negative side effects from stringent mitigation actions compatible with 1.5°C of warming (''medium evidence, high agreement''). {5.4.2}<br /> <br /> '''Appropriately designed mitigation actions to reduce energy demand can advance multiple SDGs simultaneously. Pathways compatible with 1.5°C that feature low energy demand show the most pronounced synergies and the lowest number of trade-offs with respect to sustainable development and the SDGs (''very high confidence'').''' Accelerating energy efficiency in all sectors has synergies with SDGs 7 (energy), 9 (industry, innovation and infrastructure), 11 (sustainable cities and communities), 12 (responsible consumption and production), 16 (peace, justice and strong institutions), and 17 (partnerships for the goals) (''robust evidence, high agreement''). {5.4.1, Figure 5.2, Table 5.2} Low-demand pathways, which would reduce or completely avoid the reliance on bioenergy with carbon capture and storage (BECCS) in 1.5°C pathways, would result in significantly reduced pressure on food security, lower food prices and fewer people at risk of hunger (''medium evidence, high agreement''). {5.4.2, Figure 5.3}<br /> <br /> '''The impacts of carbon dioxide removal options on SDGs depend on the type of options and the scale of deployment (''high confidence'').''' If poorly implemented, carbon dioxide removal (CDR) options such as bioenergy, BECCS and AFOLU would lead to trade-offs. Appropriate design and implementation requires considering local people’s needs, biodiversity and other sustainable development dimensions (''very high confidence''). {5.4.1.3, Cross-Chapter Box 7 in Chapter 3}<br /> <br /> '''The design of the mitigation portfolios and policy instruments to limit warming to 1.5°C will largely determine the overall synergies and trade-offs between mitigation and sustainable development (''very high confidence''). Redistributive policies that shield the poor and vulnerable can resolve trade-offs for a range of SDGs (''medium evidence, high agreement'').''' Individual mitigation options are associated with both positive and negative interactions with the SDGs (''very high confidence''). {5.4.1} However, appropriate choices across the mitigation portfolio can help to maximize positive side effects while minimizing negative side effects (''high confidence''). {5.4.2, 5.5.2} Investment needs for complementary policies resolving trade-offs with a range of SDGs are only a small fraction of the overall mitigation investments in 1.5°C pathways (''medium evidence, high agreement''). {5.4.2, Figure 5.4} Integration of mitigation with adaptation and sustainable development compatible with 1.5°C warming requires a systems perspective (''high confidence''). {5.4.2, 5.5.2}<br /> <br /> '''Mitigation consistent with 1.5°C of warming create high risks for sustainable development in countries with high dependency on fossil fuels for revenue and employment generation (''high confidence'').''' These risks are caused by the reduction of global demand affecting mining activity and export revenues and challenges to rapidly decrease high carbon intensity of the domestic economy (''robust evidence, high agreement''). {5.4.1.2, Box 5.2} Targeted policies that promote diversification of the economy and the energy sector could ease this transition (''medium evidence, high agreement''). {5.4.1.2, Box 5.2}<br /> <br /> === Sustainable Development Pathways to 1.5°C ===<br /> <br /> '''Sustainable development broadly supports and often enables the fundamental societal and systems transformations that would be required for limiting warming to 1.5°C above pre-industrial levels (''high confidence'').''' Simulated pathways that feature the most sustainable worlds (e.g., Shared Socio-Economic Pathways (SSP) 1) are associated with relatively lower mitigation and adaptation challenges and limit warming to 1.5°C at comparatively lower mitigation costs. In contrast, development pathways with high fragmentation, inequality and poverty (e.g., SSP3) are associated with comparatively higher mitigation and adaptation challenges. In such pathways, it is not possible to limit warming to 1.5°C for the vast majority of the integrated assessment models (''medium evidence, high agreement''). {5.5.2} In all SSPs, mitigation costs substantially increase in 1.5°C pathways compared to 2°C pathways. No pathway in the literature integrates or achieves all 17 SDGs (''high confidence''). {5.5.2} Real-world experiences at the project level show that the actual integration between adaptation, mitigation and sustainable development is challenging as it requires reconciling trade-offs across sectors and spatial scales (''very high confidence''). {5.5.1}<br /> <br /> '''Without societal transformation and rapid implementation of ambitious greenhouse gas reduction measures, pathways to limiting warming to 1.5°C and achieving sustainable development will be exceedingly difficult, if not impossible, to achieve (''high confidence'').''' The potential for pursuing such pathways differs between and within nations and regions, due to different development trajectories, opportunities and challenges (''very high confidence''). {5.5.3.2, Figure 5.1} Limiting warming to 1.5°C would require all countries and non-state actors to strengthen their contributions without delay. This could be achieved through sharing efforts based on bolder and more committed cooperation, with support for those with the least capacity to adapt, mitigate and transform (''medium evidence, high agreement''). {5.5.3.1, 5.5.3.2} Current efforts towards reconciling low-carbon trajectories and reducing inequalities, including those that avoid difficult trade-offs associated with transformation, are partially successful yet demonstrate notable obstacles (''medium evidence, medium agreement''). {5.5.3.3, Box 5.3, Cross-Chapter Box 13 in this chapter}<br /> <br /> '''Social justice and equity are core aspects of climate-resilient development pathways for transformational social change. Addressing challenges and widening opportunities between and within countries and communities would be necessary to achieve sustainable development and limit warming to 1.5°C, without making the poor and disadvantaged worse off (''high confidence'').''' Identifying and navigating inclusive and socially acceptable pathways towards low-carbon, climate-resilient futures is a challenging yet important endeavour, fraught with moral, practical and political difficulties and inevitable trade-offs (''very high confidence''). {5.5.2, 5.5.3.3, Box 5.3} It entails deliberation and problem-solving processes to negotiate societal values, well-being, risks and resilience and to determine what is desirable and fair, and to whom (''medium evidence, high agreement''). Pathways that encompass joint, iterative planning and transformative visions, for instance in Pacific SIDS like Vanuatu and in urban contexts, show potential for liveable and sustainable futures (''high confidence''). {5.5.3.1, 5.5.3.3, Figure 5.5, Box 5.3, Cross-Chapter Box 13 in this chapter}<br /> <br /> '''The fundamental societal and systemic changes to achieve sustainable development, eradicate poverty and reduce inequalities while limiting warming to 1.5°C would require meeting a set of institutional, social, cultural, economic and technological conditions (''high confidence'').''' The coordination and monitoring of policy actions across sectors and spatial scales is essential to support sustainable development in 1.5°C warmer conditions (''very high confidence''). {5.6.2, Box 5.3} External funding and technology transfer better support these efforts when they consider recipients’ context-specific needs (''medium evidence, high agreement''). {5.6.1} Inclusive processes can facilitate transformations by ensuring participation, transparency, capacity building and iterative social learning (''high confidence''). {5.5.3.3, Cross-Chapter Box 13, 5.6.3} Attention to power asymmetries and unequal opportunities for development, among and within countries, is key to adopting 1.5°C-compatible development pathways that benefit all populations (''high confidence''). {5.5.3, 5.6.4, Box 5.3} Re-examining individual and collective values could help spur urgent, ambitious and cooperative change (''medium evidence, high agreement''). {5.5.3, 5.6.5}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;Kyoto-GHG emissions in this statement are aggregated with GWP-100 values of the IPCC Second Assessment Report.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Robust is used here to mean that at least two thirds of climate models show the same sign of changes at the grid point scale, and that differences in large regions are statistically significant.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Projected changes in impacts between different levels of global warming are determined with respect to changes in global mean near-surface air temperature.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;Ice free is defined for the Special Report as when the sea ice extent is less than 106 km2. Ice coverage less than this is considered to be equivalent to an ice-free Arctic Ocean for practical purposes in all recent studies.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:5&quot;&gt;Annual capital revenues are the paid interests plus the increase of the asset value.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1268 2026-05-04T10:33:13Z

<p>Design: /* End table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |-<br /> | rowspan=&quot;7&quot; | Land management in all other ecosystems<br /> | Fire management<br /> | Fire suppression, prescribed fire management, mechanical treatments {7.4.3}<br /> |-<br /> | Reduced landslides and natural hazards<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Reduced pollution – acidification<br /> | Environmental regulations, climate mitigation (carbon pricing) {7.4.4}<br /> |-<br /> | Management of invasive species/encroachment<br /> | Invasive species regulations, trade regulations {5.7.2, 7.4.6}<br /> |-<br /> | Restoration and reduced conversion of coastal wetlands<br /> | Flood zone mapping {7.4.3}, land-use zoning {7.4.6}<br /> |-<br /> | Restoration and reduced conversion of peatlands<br /> | Payment for ES {7.4.6; 7.5.3}, standards and certification programmes {7.4.6}, land-use moratoriums<br /> |-<br /> | Biodiversity conservation<br /> | Conservation regulations, protected areas policies<br /> |-<br /> | rowspan=&quot;2&quot; | Carbon dioxide removal (CDR) land management<br /> | Enhanced weathering of minerals<br /> | No data<br /> |-<br /> | Bioenergy and bioenergy with carbon capture and storage (BECCS)<br /> | Standards and certification for sustainability of biomass and land use {7.4.6}<br /> |-<br /> | rowspan=&quot;2&quot; | Demand management<br /> | Dietary change<br /> | Awareness campaigns/education, changing food choices through nudges, synergies with health insurance and policy {5.7.2}<br /> |-<br /> | Reduced post-harvest losses<br /> Reduced food waste (consumer or retailer), material substitution<br /> | Agricultural business risk programmes {7.4.8}; regulations to reduce and taxes on food waste, improved shelf life, circularising the economy to produce substitute goods, carbon pricing, sugar/fat taxes {5.7.2}<br /> |-<br /> | rowspan=&quot;4&quot; | Supply management<br /> | Sustainable sourcing<br /> | Food labelling, innovation to switch to food with lower environmental footprint, public procurement policies {5.7.2}, standards and certification programmes {7.4.6}<br /> |-<br /> | Management of supply chains<br /> | Liberalised international trade {5.7.2}, food purchasing and storage policies of governments, standards and certification programmes {7.4.6}, regulations on speculation in food systems<br /> |-<br /> | Enhanced urban food systems<br /> | Buy local policies; land-use zoning to encourage urban agriculture, nature-based solutions and green infrastructure in cities; incentives for technologies like vertical farming<br /> |-<br /> | Improved food processing and retailing, improved energy use in food systems<br /> | Agriculture emission trading {7.4.4}; investment in R&amp;D for new technologies; certification<br /> |-<br /> | rowspan=&quot;4&quot; | Risk management<br /> | Management of urban sprawl<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Livelihood diversification<br /> | Climate-smart agriculture policies, adaptation policies, extension services {7.5.6}<br /> |-<br /> | Disaster risk management<br /> | Disaster risk reduction {7.5.4; 7.4.3}, adaptation planning<br /> |-<br /> | Risk-sharing instruments<br /> | Insurance, iterative risk management, CAT bonds, risk layering, contingency funds {7.4.3}, agriculture business risk portfolios {7.4.8}<br /> |}<br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1267 2026-05-04T10:32:53Z

<p>Design: /* Table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |-<br /> | rowspan=&quot;7&quot; | Land management in all other ecosystems<br /> | Fire management<br /> | Fire suppression, prescribed fire management, mechanical treatments {7.4.3}<br /> |-<br /> | Reduced landslides and natural hazards<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Reduced pollution – acidification<br /> | Environmental regulations, climate mitigation (carbon pricing) {7.4.4}<br /> |-<br /> | Management of invasive species/encroachment<br /> | Invasive species regulations, trade regulations {5.7.2, 7.4.6}<br /> |-<br /> | Restoration and reduced conversion of coastal wetlands<br /> | Flood zone mapping {7.4.3}, land-use zoning {7.4.6}<br /> |-<br /> | Restoration and reduced conversion of peatlands<br /> | Payment for ES {7.4.6; 7.5.3}, standards and certification programmes {7.4.6}, land-use moratoriums<br /> |-<br /> | Biodiversity conservation<br /> | Conservation regulations, protected areas policies<br /> |-<br /> | rowspan=&quot;2&quot; | Carbon dioxide removal (CDR) land management<br /> | Enhanced weathering of minerals<br /> | No data<br /> |-<br /> | Bioenergy and bioenergy with carbon capture and storage (BECCS)<br /> | Standards and certification for sustainability of biomass and land use {7.4.6}<br /> |-<br /> | rowspan=&quot;2&quot; | Demand management<br /> | Dietary change<br /> | Awareness campaigns/education, changing food choices through nudges, synergies with health insurance and policy {5.7.2}<br /> |-<br /> | Reduced post-harvest losses<br /> Reduced food waste (consumer or retailer), material substitution<br /> | Agricultural business risk programmes {7.4.8}; regulations to reduce and taxes on food waste, improved shelf life, circularising the economy to produce substitute goods, carbon pricing, sugar/fat taxes {5.7.2}<br /> |-<br /> | rowspan=&quot;4&quot; | Supply management<br /> | Sustainable sourcing<br /> | Food labelling, innovation to switch to food with lower environmental footprint, public procurement policies {5.7.2}, standards and certification programmes {7.4.6}<br /> |-<br /> | Management of supply chains<br /> | Liberalised international trade {5.7.2}, food purchasing and storage policies of governments, standards and certification programmes {7.4.6}, regulations on speculation in food systems<br /> |-<br /> | Enhanced urban food systems<br /> | Buy local policies; land-use zoning to encourage urban agriculture, nature-based solutions and green infrastructure in cities; incentives for technologies like vertical farming<br /> |-<br /> | Improved food processing and retailing, improved energy use in food systems<br /> | Agriculture emission trading {7.4.4}; investment in R&amp;D for new technologies; certification<br /> |-<br /> | rowspan=&quot;4&quot; | Risk management<br /> | Management of urban sprawl<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Livelihood diversification<br /> | Climate-smart agriculture policies, adaptation policies, extension services {7.5.6}<br /> |-<br /> | Disaster risk management<br /> | Disaster risk reduction {7.5.4; 7.4.3}, adaptation planning<br /> |-<br /> | Risk-sharing instruments<br /> | Insurance, iterative risk management, CAT bonds, risk layering, contingency funds {7.4.3}, agriculture business risk portfolios {7.4.8}<br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1266 2026-05-04T10:32:15Z

<p>Design: /* Table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> ==== Table ====<br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |-<br /> | rowspan=&quot;7&quot; | Land management in all other ecosystems<br /> | Fire management<br /> | Fire suppression, prescribed fire management, mechanical treatments {7.4.3}<br /> |-<br /> | Reduced landslides and natural hazards<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Reduced pollution – acidification<br /> | Environmental regulations, climate mitigation (carbon pricing) {7.4.4}<br /> |-<br /> | Management of invasive species/encroachment<br /> | Invasive species regulations, trade regulations {5.7.2, 7.4.6}<br /> |-<br /> | Restoration and reduced conversion of coastal wetlands<br /> | Flood zone mapping {7.4.3}, land-use zoning {7.4.6}<br /> |-<br /> | Restoration and reduced conversion of peatlands<br /> | Payment for ES {7.4.6; 7.5.3}, standards and certification programmes {7.4.6}, land-use moratoriums<br /> |-<br /> | Biodiversity conservation<br /> | Conservation regulations, protected areas policies<br /> |-<br /> | rowspan=&quot;2&quot; | Carbon dioxide removal (CDR) land management<br /> | Enhanced weathering of minerals<br /> | No data<br /> |-<br /> | Bioenergy and bioenergy with carbon capture and storage (BECCS)<br /> | Standards and certification for sustainability of biomass and land use {7.4.6}<br /> |-<br /> | rowspan=&quot;2&quot; | Demand management<br /> | Dietary change<br /> | Awareness campaigns/education, changing food choices through nudges, synergies with health insurance and policy {5.7.2}<br /> |-<br /> | Reduced post-harvest losses<br /> Reduced food waste (consumer or retailer), material substitution<br /> | Agricultural business risk programmes {7.4.8}; regulations to reduce and taxes on food waste, improved shelf life, circularising the economy to produce substitute goods, carbon pricing, sugar/fat taxes {5.7.2}<br /> |-<br /> | rowspan=&quot;4&quot; | Supply management<br /> | Sustainable sourcing<br /> | Food labelling, innovation to switch to food with lower environmental footprint, public procurement policies {5.7.2}, standards and certification programmes {7.4.6}<br /> |-<br /> | Management of supply chains<br /> | Liberalised international trade {5.7.2}, food purchasing and storage policies of governments, standards and certification programmes {7.4.6}, regulations on speculation in food systems<br /> |-<br /> | Enhanced urban food systems<br /> | Buy local policies; land-use zoning to encourage urban agriculture, nature-based solutions and green infrastructure in cities; incentives for technologies like vertical farming<br /> |-<br /> | Improved food processing and retailing, improved energy use in food systems<br /> | Agriculture emission trading {7.4.4}; investment in R&amp;D for new technologies; certification<br /> |-<br /> | rowspan=&quot;4&quot; | Risk management<br /> | Management of urban sprawl<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Livelihood diversification<br /> | Climate-smart agriculture policies, adaptation policies, extension services {7.5.6}<br /> |-<br /> | Disaster risk management<br /> | Disaster risk reduction {7.5.4; 7.4.3}, adaptation planning<br /> |-<br /> | Risk-sharing instruments<br /> | Insurance, iterative risk management, CAT bonds, risk layering, contingency funds {7.4.3}, agriculture business risk portfolios {7.4.8}<br /> <br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1265 2026-05-04T10:31:44Z

<p>Design: /* Table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> ==== Table ====<br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |-<br /> | rowspan=&quot;7&quot; | Land management in all other ecosystems<br /> | Fire management<br /> | Fire suppression, prescribed fire management, mechanical treatments {7.4.3}<br /> |-<br /> | Reduced landslides and natural hazards<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Reduced pollution – acidification<br /> | Environmental regulations, climate mitigation (carbon pricing) {7.4.4}<br /> |-<br /> | Management of invasive species/encroachment<br /> | Invasive species regulations, trade regulations {5.7.2, 7.4.6}<br /> |-<br /> | Restoration and reduced conversion of coastal wetlands<br /> | Flood zone mapping {7.4.3}, land-use zoning {7.4.6}<br /> |-<br /> | Restoration and reduced conversion of peatlands<br /> | Payment for ES {7.4.6; 7.5.3}, standards and certification programmes {7.4.6}, land-use moratoriums<br /> |-<br /> | Biodiversity conservation<br /> | Conservation regulations, protected areas policies<br /> |-<br /> | rowspan=&quot;2&quot; | Carbon dioxide removal (CDR) land management<br /> | Enhanced weathering of minerals<br /> | No data<br /> |-<br /> | Bioenergy and bioenergy with carbon capture and storage (BECCS)<br /> | Standards and certification for sustainability of biomass and land use {7.4.6}<br /> |-<br /> | rowspan=&quot;2&quot; | Demand management<br /> | Dietary change<br /> | Awareness campaigns/education, changing food choices through nudges, synergies with health insurance and policy {5.7.2}<br /> |-<br /> | Reduced post-harvest losses<br /> Reduced food waste (consumer or retailer), material substitution<br /> | Agricultural business risk programmes {7.4.8}; regulations to reduce and taxes on food waste, improved shelf life, circularising the economy to produce substitute goods, carbon pricing, sugar/fat taxes {5.7.2}<br /> |-<br /> | rowspan=&quot;4&quot; | Supply management<br /> | Sustainable sourcing<br /> | Food labelling, innovation to switch to food with lower environmental footprint, public procurement policies {5.7.2}, standards and certification programmes {7.4.6}<br /> |-<br /> | Management of supply chains<br /> | Liberalised international trade {5.7.2}, food purchasing and storage policies of governments, standards and certification programmes {7.4.6}, regulations on speculation in food systems<br /> |-<br /> | Enhanced urban food systems<br /> | Buy local policies; land-use zoning to encourage urban agriculture, nature-based solutions and green infrastructure in cities; incentives for technologies like vertical farming<br /> |-<br /> | Improved food processing and retailing, improved energy use in food systems<br /> | Agriculture emission trading {7.4.4}; investment in R&amp;D for new technologies; certification<br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1264 2026-05-04T10:31:03Z

<p>Design: /* Table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> ==== Table ====<br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |-<br /> | rowspan=&quot;7&quot; | Land management in all other ecosystems<br /> | Fire management<br /> | Fire suppression, prescribed fire management, mechanical treatments {7.4.3}<br /> |-<br /> | Reduced landslides and natural hazards<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Reduced pollution – acidification<br /> | Environmental regulations, climate mitigation (carbon pricing) {7.4.4}<br /> |-<br /> | Management of invasive species/encroachment<br /> | Invasive species regulations, trade regulations {5.7.2, 7.4.6}<br /> |-<br /> | Restoration and reduced conversion of coastal wetlands<br /> | Flood zone mapping {7.4.3}, land-use zoning {7.4.6}<br /> |-<br /> | Restoration and reduced conversion of peatlands<br /> | Payment for ES {7.4.6; 7.5.3}, standards and certification programmes {7.4.6}, land-use moratoriums<br /> |-<br /> | Biodiversity conservation<br /> | Conservation regulations, protected areas policies<br /> |-<br /> | rowspan=&quot;2&quot; | Carbon dioxide removal (CDR) land management<br /> | Enhanced weathering of minerals<br /> | No data<br /> |-<br /> | Bioenergy and bioenergy with carbon capture and storage (BECCS)<br /> | Standards and certification for sustainability of biomass and land use {7.4.6}<br /> |-<br /> | rowspan=&quot;2&quot; | Demand management<br /> | Dietary change<br /> | Awareness campaigns/education, changing food choices through nudges, synergies with health insurance and policy {5.7.2}<br /> |-<br /> | Reduced post-harvest losses<br /> Reduced food waste (consumer or retailer), material substitution<br /> | Agricultural business risk programmes {7.4.8}; regulations to reduce and taxes on food waste, improved shelf life, circularising the economy to produce substitute goods, carbon pricing, sugar/fat taxes {5.7.2}<br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1263 2026-05-04T10:30:24Z

<p>Design: /* Table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> ==== Table ====<br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |-<br /> | rowspan=&quot;7&quot; | Land management in all other ecosystems<br /> | Fire management<br /> | Fire suppression, prescribed fire management, mechanical treatments {7.4.3}<br /> |-<br /> | Reduced landslides and natural hazards<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Reduced pollution – acidification<br /> | Environmental regulations, climate mitigation (carbon pricing) {7.4.4}<br /> |-<br /> | Management of invasive species/encroachment<br /> | Invasive species regulations, trade regulations {5.7.2, 7.4.6}<br /> |-<br /> | Restoration and reduced conversion of coastal wetlands<br /> | Flood zone mapping {7.4.3}, land-use zoning {7.4.6}<br /> |-<br /> | Restoration and reduced conversion of peatlands<br /> | Payment for ES {7.4.6; 7.5.3}, standards and certification programmes {7.4.6}, land-use moratoriums<br /> |-<br /> | Biodiversity conservation<br /> | Conservation regulations, protected areas policies<br /> |-<br /> | rowspan=&quot;2&quot; | Carbon dioxide removal (CDR) land management<br /> | Enhanced weathering of minerals<br /> | No data<br /> |-<br /> | Bioenergy and bioenergy with carbon capture and storage (BECCS)<br /> | Standards and certification for sustainability of biomass and land use {7.4.6}<br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1262 2026-05-04T10:29:48Z

<p>Design: /* Table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> ==== Table ====<br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |-<br /> | rowspan=&quot;7&quot; | Land management in all other ecosystems<br /> | Fire management<br /> | Fire suppression, prescribed fire management, mechanical treatments {7.4.3}<br /> |-<br /> | Reduced landslides and natural hazards<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Reduced pollution – acidification<br /> | Environmental regulations, climate mitigation (carbon pricing) {7.4.4}<br /> |-<br /> | Management of invasive species/encroachment<br /> | Invasive species regulations, trade regulations {5.7.2, 7.4.6}<br /> |-<br /> | Restoration and reduced conversion of coastal wetlands<br /> | Flood zone mapping {7.4.3}, land-use zoning {7.4.6}<br /> |-<br /> | Restoration and reduced conversion of peatlands<br /> | Payment for ES {7.4.6; 7.5.3}, standards and certification programmes {7.4.6}, land-use moratoriums<br /> |-<br /> | Biodiversity conservation<br /> | Conservation regulations, protected areas policies<br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1261 2026-05-04T10:29:12Z

<p>Design: /* Table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> ==== Table ====<br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |<br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1260 2026-05-04T10:28:21Z

<p>Design: /* Table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> ==== Table ====<br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1259 2026-05-04T10:27:24Z

<p>Design: /* Table */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> ==== Table ====<br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1258 2026-05-04T10:26:47Z

<p>Design: /* TS.7 Risk management and decision making in relation to sustainable development */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> ==== Table ====<br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | rowspan=&quot;8&quot; | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | rowspan=&quot;7&quot; | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in all other ecosystems<br /> | Fire management<br /> | Fire suppression, prescribed fire management, mechanical treatments {7.4.3}<br /> |-<br /> | Reduced landslides and natural hazards<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Reduced pollution – acidification<br /> | Environmental regulations, climate mitigation (carbon pricing) {7.4.4}<br /> |-<br /> | Management of invasive species/encroachment<br /> | Invasive species regulations, trade regulations {5.7.2, 7.4.6}<br /> |-<br /> | Restoration and reduced conversion of coastal wetlands<br /> | Flood zone mapping {7.4.3}, land-use zoning {7.4.6}<br /> |-<br /> | Restoration and reduced conversion of peatlands<br /> | Payment for ES {7.4.6; 7.5.3}, standards and certification programmes {7.4.6}, land-use moratoriums<br /> |-<br /> | Biodiversity conservation<br /> | Conservation regulations, protected areas policies<br /> |-<br /> | rowspan=&quot;2&quot; | Carbon dioxide removal (CDR) land management<br /> | Enhanced weathering of minerals<br /> | No data<br /> |-<br /> | Bioenergy and bioenergy with carbon capture and storage (BECCS)<br /> | Standards and certification for sustainability of biomass and land use {7.4.6}<br /> |-<br /> | rowspan=&quot;3&quot; | Demand management<br /> | Dietary change<br /> | Awareness campaigns/education, changing food choices through nudges, synergies with health insurance and policy {5.7.2}<br /> |-<br /> | Reduced post-harvest losses<br /> Reduced food waste (consumer or retailer), material substitution<br /> | Agricultural business risk programmes {7.4.8}; regulations to reduce and taxes on food waste, improved shelf life, circularising the economy to produce substitute goods, carbon pricing, sugar/fat taxes {5.7.2}<br /> |-<br /> | rowspan=&quot;3&quot; | Supply management<br /> | Sustainable sourcing<br /> | Food labelling, innovation to switch to food with lower environmental footprint, public procurement policies {5.7.2}, standards and certification programmes {7.4.6}<br /> |-<br /> | Management of supply chains<br /> | Liberalised international trade {5.7.2}, food purchasing and storage policies of governments, standards and certification programmes {7.4.6}, regulations on speculation in food systems<br /> |-<br /> | Enhanced urban food systems<br /> | Buy local policies; land-use zoning to encourage urban agriculture, nature-based solutions and green infrastructure in cities; incentives for technologies like vertical farming<br /> |-<br /> | Improved food processing and retailing, improved energy use in food systems<br /> | Agriculture emission trading {7.4.4}; investment in R&amp;D for new technologies; certification<br /> |-<br /> | rowspan=&quot;2&quot; | Risk management<br /> | Management of urban sprawl<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Livelihood diversification<br /> | Climate-smart agriculture policies, adaptation policies, extension services {7.5.6}<br /> |-<br /> | Disaster risk management<br /> | Disaster risk reduction {7.5.4; 7.4.3}, adaptation planning<br /> |-<br /> | Risk-sharing instruments<br /> | Insurance, iterative risk management, CAT bonds, risk layering, contingency funds {7.4.3}, agriculture business risk portfolios {7.4.8}<br /> |}<br /> <br /> ==== End table ====<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1257 2026-05-04T10:23:40Z

<p>Design: /* TS.7 Risk management and decision making in relation to sustainable development */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> {| class=&quot;wikitable&quot; style=&quot;border-collapse:collapse; width:100%;&quot;<br /> |-<br /> ! Category<br /> ! Integrated Response Option<br /> ! Policy instrument supporting response option<br /> |-<br /> | rowspan=&quot;5&quot; | Land management in agriculture<br /> | Increased food productivity<br /> | Investment in agricultural research for crop and livestock improvement, agricultural technology transfer, inland capture fisheries and aquaculture {7.4.7}, agricultural policy reform and trade liberalisation<br /> |-<br /> | Improved cropland, grazing and livestock management<br /> | Environmental farm programs/agri-environment schemes, water efficiency requirements and water transfer {3.8.5}, extension services<br /> |-<br /> | Agroforestry<br /> | Payment for ecosystem services (ES) {7.4.6}<br /> |-<br /> | Agricultural diversification<br /> | Elimination of agriculture subsidies {5.7.1}, environmental farm programs, agri-environmental payments {7.5.6}, rural development programmes<br /> |-<br /> | Reduced grassland conversion to cropland<br /> | Elimination of agriculture subsidies, remove insurance incentives, ecological restoration {7.4.6}<br /> |-<br /> | Integrated water management<br /> | Integrated governance {7.6.2}, multi-level instruments {7.4.1}<br /> |-<br /> | rowspan=&quot;8&quot; | Land management in forests<br /> | Forest management, reduced deforestation and degradation, reforestation and forest restoration, afforestation<br /> | REDD+, forest conservation regulations, payments for ES, recognition of forest rights and land tenure {7.4.6}, adaptive management of forests {7.5.4}, land-use moratoriums, reforestation programmes and investment {4.9.1}<br /> |-<br /> | rowspan=&quot;7&quot; | Land management of soils<br /> | Increased soil organic carbon content, reduced soil erosion, reduced soil salinisation, reduced soil compaction, biochar addition to soil<br /> | Land degradation neutrality (LDN) {7.4.5}, drought plans, flood plans, flood zone mapping {7.4.3}, technology transfer {7.4.4}, land-use zoning {7.4.6}, ecological service mapping and stakeholder-based quantification {7.5.3}, environmental farm programmes/agri-environment schemes, water-efficiency requirements and water transfer {3.7.5}<br /> |-<br /> | rowspan=&quot;6&quot; | Land management in all other ecosystems<br /> | Fire management<br /> | Fire suppression, prescribed fire management, mechanical treatments {7.4.3}<br /> |-<br /> | Reduced landslides and natural hazards<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Reduced pollution – acidification<br /> | Environmental regulations, climate mitigation (carbon pricing) {7.4.4}<br /> |-<br /> | Management of invasive species/encroachment<br /> | Invasive species regulations, trade regulations {5.7.2, 7.4.6}<br /> |-<br /> | Restoration and reduced conversion of coastal wetlands<br /> | Flood zone mapping {7.4.3}, land-use zoning {7.4.6}<br /> |-<br /> | Restoration and reduced conversion of peatlands<br /> | Payment for ES {7.4.6; 7.5.3}, standards and certification programmes {7.4.6}, land-use moratoriums<br /> |-<br /> | Biodiversity conservation<br /> | Conservation regulations, protected areas policies<br /> |-<br /> | rowspan=&quot;2&quot; | Carbon dioxide removal (CDR) land management<br /> | Enhanced weathering of minerals<br /> | No data<br /> |-<br /> | Bioenergy and bioenergy with carbon capture and storage (BECCS)<br /> | Standards and certification for sustainability of biomass and land use {7.4.6}<br /> |-<br /> | rowspan=&quot;3&quot; | Demand management<br /> | Dietary change<br /> | Awareness campaigns/education, changing food choices through nudges, synergies with health insurance and policy {5.7.2}<br /> |-<br /> | Reduced post-harvest losses<br /> Reduced food waste (consumer or retailer), material substitution<br /> | Agricultural business risk programmes {7.4.8}; regulations to reduce and taxes on food waste, improved shelf life, circularising the economy to produce substitute goods, carbon pricing, sugar/fat taxes {5.7.2}<br /> |-<br /> | rowspan=&quot;3&quot; | Supply management<br /> | Sustainable sourcing<br /> | Food labelling, innovation to switch to food with lower environmental footprint, public procurement policies {5.7.2}, standards and certification programmes {7.4.6}<br /> |-<br /> | Management of supply chains<br /> | Liberalised international trade {5.7.2}, food purchasing and storage policies of governments, standards and certification programmes {7.4.6}, regulations on speculation in food systems<br /> |-<br /> | Enhanced urban food systems<br /> | Buy local policies; land-use zoning to encourage urban agriculture, nature-based solutions and green infrastructure in cities; incentives for technologies like vertical farming<br /> |-<br /> | Improved food processing and retailing, improved energy use in food systems<br /> | Agriculture emission trading {7.4.4}; investment in R&amp;D for new technologies; certification<br /> |-<br /> | rowspan=&quot;2&quot; | Risk management<br /> | Management of urban sprawl<br /> | Land-use zoning {7.4.6}<br /> |-<br /> | Livelihood diversification<br /> | Climate-smart agriculture policies, adaptation policies, extension services {7.5.6}<br /> |-<br /> | Disaster risk management<br /> | Disaster risk reduction {7.5.4; 7.4.3}, adaptation planning<br /> |-<br /> | Risk-sharing instruments<br /> | Insurance, iterative risk management, CAT bonds, risk layering, contingency funds {7.4.3}, agriculture business risk portfolios {7.4.8}<br /> |}<br /> <br /> <br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1256 2026-05-04T10:20:08Z

<p>Design: /* Technical Summary */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt; by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1255 2026-05-04T10:12:49Z

<p>Design: /* TS.7 Risk management and decision making in relation to sustainable development */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''&lt;br&gt;<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1254 2026-05-04T10:12:15Z

<p>Design: /* TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).'''&lt;br&gt;<br /> '''Figure TS.13 (continued):''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1253 2026-05-04T10:11:10Z

<p>Design: /* Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1252 2026-05-04T10:10:55Z

<p>Design: /* Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).'''&lt;br&gt;<br /> '''Figure TS.5 (continued):''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1251 2026-05-04T10:09:52Z

<p>Design: /* TS.1 Framing and context */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''&lt;br&gt;<br /> '''Figure TS.2 (continued):''' Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1250 2026-05-04T10:07:16Z

<p>Design: /* TS.7 Risk management and decision making in relation to sustainable development */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''<br /> Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''&lt;br&gt;<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs) &lt;sup&gt;[[#fn:2|2]]&lt;/sup&gt; which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM) &lt;sup&gt;[[#fn:3|3]]&lt;/sup&gt; results for SSP1, SSP2 and SSP5 at RCP1.9. &lt;sup&gt;[[#fn:4|4]]&lt;/sup&gt; For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1249 2026-05-04T10:05:31Z

<p>Design: /* TS.7 Risk management and decision making in relation to sustainable development */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''<br /> Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> '''Table TS.1 | Selection of Policies/Programmes/Instruments that support response options.'''<br /> <br /> [[File:FigureTS15a???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel A).'''<br /> <br /> [[File:FigureTS15b???.jpg]]<br /> <br /> '''Figure TS.15 | Pathways linking socioeconomic development, mitigation responses and land (Panel B).'''<br /> '''Figure TS.15 (continued):''' Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land. The SSPs span a range of different socioeconomic assumptions (Box SPM.1). They are combined with Representative Concentration Pathways (RCPs)2 which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’. Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. '''Panel A:''' This panel shows integrated assessment model (IAM)3 results for SSP1, SSP2 and SSP5 at RCP1.9.4 For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2 and SSP5 results are from five, four and two IAMs respectively. '''Panel B:''' Land use and land cover change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1248 2026-05-04T10:03:04Z

<p>Design: /* TS.7 Risk management and decision making in relation to sustainable development */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''<br /> Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> [[File:FigureTS14???.jpg]]<br /> <br /> '''Figure TS.14 | Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation choices.'''<br /> '''Figure TS.14 (continued):''' As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with the SSP pathways as described below. '''Panel A:''' Risks to selected elements of the land system as a function of global mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly consistent with an SSP2 pathway. {Table SM7.4}. '''Panel B:''' Risks associated with desertification, land degradation and food security due to climate change and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multi-round elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary Material.<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1247 2026-05-04T10:00:36Z

<p>Design: /* TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''<br /> Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. '''Magnitude of potential:''' For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. '''Levels of confidence:''' Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. '''Cost ranges:''' Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. '''Supporting evidence:''' Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1246 2026-05-04T09:59:30Z

<p>Design: /* TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''<br /> Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'').''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> [[File:FigureTS12???.jpg]]<br /> <br /> '''Figure TS.12 | Potential deployment area of land management responses (see Table 6.1) across land-use types (or anthromes, see Section 6.3), when selecting responses having only co-benefits for local challenges and for climate change mitigation and no large adverse side effects on global food security.''' See Figure 6.2 for the criteria used to map challenges considered (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality). No response option was identified for barren lands.<br /> <br /> [[File:FigureTS13a???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel A).'''<br /> <br /> [[File:FigureTS13b???.jpg]]<br /> <br /> '''Figure TS.13 | Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and enhancing food security (Panel B).''' This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. Magnitude of potential: For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr–1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished. The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable intensification rather than through injudicious application of additional external inputs such as agrochemicals. Levels of confidence: Confidence in the magnitude category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude of response. Cost ranges: Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B, cost estimates are not provided for best practice implementation. One coin indicates low cost (&lt;USD10 tCO2-eq–1 or &lt;USD20 ha–1), two coins indicate medium cost (USD10–USD100 tCO2-eq–1 or USD20–USD200 ha–1), and three coins indicate high cost (&gt;USD100 tCO2-eq–1 or USD200 ha–1). Thresholds in USD ha–1 are chosen to be comparable, but precise conversions will depend on the response option. Supporting evidence: Supporting evidence for the magnitude of the quantitative potential for land management-based response options can be found as follows: for mitigation Tables 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Tables 6.21 to 6.28; for combating desertification Tables 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58, Section 6.3.5.1.3, and Box 6.1c.<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1245 2026-05-04T09:56:27Z

<p>Design: /* TS.5 Food security */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''<br /> Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> [[File:FigureTS11???.jpg]]<br /> <br /> '''Figure TS.11 | Response options related to food system and their potential impacts on mitigation and adaptation.''' Many response options offer significant potential for both mitigation and adaptation.<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'')''.''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1244 2026-05-04T09:55:32Z

<p>Design: /* TS.5 Food security */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''<br /> Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> [[File:FigureTS10???.jpg]]<br /> <br /> '''Figure TS.10 | AgMIP median yield changes (%) for RCP8.5''' (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMsfour Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5° grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014).<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'')''.''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design https://ckg.semanticclimate.org/index.php?title=IPCC:AR6/SRCCL/TS&diff=1243 2026-05-04T09:54:29Z

<p>Design: /* TS.5 Food security */</p> <hr /> <div>= Technical Summary =<br /> <br /> '''Editors:'''<br /> <br /> Priyadarshi R. Shukla (India), Jim Skea (United Kingdom), Raphael Slade (United Kingdom) Renée van Diemen (The Netherlands/United Kingdom), Eamon Haughey (Ireland), Juliette Malley (United Kingdom), Minal Pathak (India), Joana Portugal Pereira (United Kingdom)<br /> <br /> '''Drafting Authors:'''<br /> <br /> Fahmuddin Agus (Indonesia), Almut Arneth (Germany), Paulo Artaxo (Brazil), Humberto Barbosa (Brazil), Luis G. Barioni (Brazil), Tim G. Benton (United Kingdom), Suruchi Bhadwal (India), Katherine Calvin (The United States of America), Eduardo Calvo (Peru), Donovan Campbell (Jamaica), Francesco Cherubini (Italy), Sarah Connors (France/United Kingdom), Annette Cowie (Australia), Edouard Davin (France/Switzerland), Kenel Delusca (Haiti), Fatima Denton (The Gambia), Aziz Elbehri (Morocco), Karlheinz Erb (Italy), Jason Evans (Australia), Dulce Flores-Renteria (Mexico), Felipe Garcia-Oliva (Mexico), Giacomo Grassi (Italy/European Union), Kathleen Hermans (Germany), Mario Herrero (Australia/Costa Rica), Richard Houghton (The United States of America), Joanna House (United Kingdom), Mark Howden (Australia), Margot Hurlbert (Canada), Ismail Abdel Galil Hussein (Egypt), Muhammad Mohsin Iqbal (Pakistan), Gensuo Jia (China), Esteban Jobbagy (Argentina), Francis X. Johnson (Sweden), Joyce Kimutai (Kenya), Kaoru Kitajima (Japan), Tony Knowles (South Africa), Vladimir Korotkov (The Russian Federation), Murukesan V. Krishnapillai (Micronesia/ India), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Anh Le Hoang (Viet Nam), Christopher Lennard (South Africa), Diqiang Li (China), Emma Liwenga (The United Republic of Tanzania), Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Valérie Masson-Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America), Carlos Fernando Mena (Ecuador), Francisco Meza (Chile), Alisher Mirzabaev (Germany/Uzbekistan), John Morton (United Kingdom), Wilfran Moufouma-Okia (France), Soojeong Myeong (The Republic of Korea), Dalila Nedjraoui (Algeria), Johnson Nkem (Cameroon), Ephraim Nkonya (The United Republic of Tanzania), Nathalie De Noblet-Ducoudré (France), Lennart Olsson (Sweden), Balgis Osman Elasha (Côte d’Ivoire), Jan Petzold (Germany), Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom), Alexander Popp (Germany), Hans-Otto Pörtner (Germany), Prajal Pradhan (Germany/Nepal), Mohammad Rahimi (Iran), Andy Reisinger (New Zealand), Marta G. Rivera-Ferre (Spain), Debra C. Roberts (South Africa), Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom), Nobuko Saigusa (Japan), Tek Sapkota (Canada/Nepal), Elena Shevliakova (The United States of America), Andrey Sirin (The Russian Federation), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Adrian Spence (Jamaica), Lindsay Stringer (United Kingdom), Raman Sukumar (India), Miguel Angel Taboada (Argentina), Fasil Tena (Ethiopia), Francesco N. Tubiello (The United States of America/Italy), Murat Türkeş (Turkey), Riccardo Valentini (Italy), Ranses José Vázquez Montenegro (Cuba), Louis Verchot (Colombia/The United States of America), David Viner (United Kingdom), Koko Warner (The United States of America), Mark Weltz (The United States of America), Nora M. Weyer (Germany), Anita Wreford (New Zealand), Jianguo Wu (China), Yinlong Xu (China), Noureddine Yassaa (Algeria), Sumaya Zakieldeen (Sudan), Panmao Zhai (China), Zinta Zommers (Latvia)<br /> <br /> '''Chapter Scientists:'''<br /> <br /> Yuping Bai (China), Aliyu Salisu Barau (Nigeria), Abdoul Aziz Diouf (Senegal), Baldur Janz (Germany), Frances Manning (United Kingdom), Erik Mencos Contreras (The United States of America/Mexico), Dorothy Nampanzira (Uganda), Chuck Chuan Ng (Malaysia), Helen Berga Paulos (Ethiopia), Xiyan Xu (China), Thobekile Zikhali (Zimbabwe)<br /> <br /> '''This Technical Summary should be cited as:'''<br /> <br /> P.R. Shukla, J. Skea, R. Slade, R. van Diemen, E. Haughey, J. Malley, M. Pathak, J. Portugal Pereira (eds.) Technical Summary, 2019. In: ''Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems'' [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M, Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.002<br /> <br /> == TS.0 Introduction ==<br /> <br /> This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL) &lt;sup&gt;[[#fn:1|1]]&lt;/sup&gt; comprises a compilation of the chapter executive summaries illustrated with figures from the report. It follows the structure of the SRCCL (Figure TS.1) and is presented in seven parts. TS.1 (Chapter 1) provides a synopsis of the main issues addressed in the Special Report, introducing key concepts and definitions and highlighting where the report builds on previous publications. TS.2 (Chapter 2) focuses on the dynamics of the land–climate system (Figure TS.2). It assesses recent progress towards understanding the impacts of climate change on land, and the feedbacks land has on climate and which arise from altered biogeochemical and biophysical fluxes between the atmosphere and the land surface. TS.3 (Chapter 3) examines how the world’s dryland populations are uniquely vulnerable to desertification and climate change, but also have significant knowledge in adapting to climate variability and addressing desertification. TS.4 (Chapter 4) assesses the urgency of tackling land degradation across all land ecosystems. Despite accelerating trends of land degradation, reversing these trends is attainable through restoration efforts and improved land management, which is expected to improve resilience to climate change, mitigate climate change, and ensure food security for generations to come. TS.5 (Chapter 5) focuses on food security, with an assessment of the risks and opportunities that climate change presents to food systems. It considers how mitigation and adaptation can contribute to both human and planetary health. TS.6 (Chapter 6) introduces options for responding to the challenges of desertification, land degradation and food security and evaluates the trade-offs for sustainable land management, climate adaptation and mitigation, and the sustainable development goals. TS.7 (Chapter 7) further assesses decision making and policy responses to risks in the climate-land-human system.<br /> <br /> == TS.1 Framing and context ==<br /> <br /> '''Land, including its water bodies, provides the basis for human livelihoods and well-being through primary productivity, the supply of food, freshwater, and multiple other ecosystem services (''high confidence'').''' Neither our individual or societal identities, nor the world’s economy would exist without the multiple resources, services and livelihood systems provided by land ecosystems and biodiversity. The annual value of the world’s total terrestrial ecosystem services has been estimated at 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (''medium confidence''). Land and its biodiversity also represent essential, intangible benefits to humans, such as cognitive and spiritual enrichment, sense of belonging and aesthetic and recreational values. Valuing ecosystem services with monetary methods often overlooks these intangible services that shape societies, cultures and quality of life and the intrinsic value of biodiversity. The Earth’s land area is finite. Using land resources sustainably is fundamental for human well-being (''high confidence''). {1.1.1}<br /> <br /> '''The current geographic spread of the use of land, the large appropriation of multiple ecosystem services and the loss of biodiversity are unprecedented in human history (''high confidence'').''' By 2015, about three-quarters of the global ice-free land surface was affected by human use. Humans appropriate one-quarter to one-third of global terrestrial potential net primary production (''high confidence''). Croplands cover 12–14% of the global ice-free surface. Since 1961, the supply of global per capita food calories increased by about one-third, with the consumption of vegetable oils and meat more than doubling. At the same time, the use of inorganic nitrogen fertiliser increased by nearly ninefold, and the use of irrigation water roughly doubled (''high confidence''). Human use, at varying intensities, affects about 60–85% of forests and 70–90% of other natural ecosystems (e.g., savannahs, natural grasslands) (''high confidence''). Land use caused global biodiversity to decrease by around 11–14% (''medium confidence''). (Figure TS.2). {1.1.2}<br /> <br /> [[File:FigureTS1???.jpg]]<br /> <br /> '''Figure TS.1 | Overview of the IPCC Special Report on Climate Change and Land (SRCCL).'''<br /> <br /> [[File:FigureTS2???.jpg]]<br /> <br /> '''Figure TS.2 | Land use and observed climate change: A representation of the principal land challenges and land–climate system processes covered in this assessment report.'''<br /> Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D–F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D–F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A:''' The warming curves are averages of four datasets {2.1; Figure 2.2; Table 2.1} '''B:''' N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O = 265; CH4 = 28). {see Table SPM.1, 1.1, 2.3} '''C:''' Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D:''' Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E:''' Overweight population is defined as having a body mass index (BMI) &gt;25 kg m-2; underweight is defined as BMI &lt;18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}<br /> <br /> '''Warming over land has occurred at a faster rate than the global mean and this has had observable impacts on the land system (''high confidence'').''' The average temperature over land for the period 2006–2015 was 1.53°C higher than for the period 1850–1900, and 0.66°C larger than the equivalent global mean temperature change. These warmer temperatures (with changing precipitation patterns) have altered the start and end of growing seasons, contributed to regional crop yield reductions, reduced freshwater availability, and put biodiversity under further stress and increased tree mortality (''high confidence''). Increasing levels of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;, have contributed to observed increases in plant growth as well as to increases in woody plant cover in grasslands and savannahs (''medium confidence''). {1.1.2}<br /> <br /> '''Urgent action to stop and reverse the over-exploitation of land resources would buffer the negative impacts of multiple pressures, including climate change, on ecosystems and society (''high confidence'').''' Socio-economic drivers of land use change such as technological development, population growth and increasing per capita demand for multiple ecosystem services are projected to continue into the future (''high confidence''). These and other drivers can amplify existing environmental and societal challenges, such as the conversion of natural ecosystems into managed land, rapid urbanisation, pollution from the intensification of land management and equitable access to land resources (''high confidence''). Climate change will add to these challenges through direct, negative impacts on ecosystems and the services they provide (''high confidence''). Acting immediately and simultaneously on these multiple drivers would enhance food, fibre and water security, alleviate desertification, and reverse land degradation, without compromising the non-material or regulating benefits from land (''high confidence''). {1.1.2, 1.2.1, 1.3.2–<br /> 1.3.6, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> '''Rapid reductions in anthropogenic greenhouse gas (GHG) emissions that restrict warming to “well-below” 2°C would greatly reduce the negative impacts of climate change on land ecosystems (''high confidence''). In the absence of rapid emissions reductions, reliance on large-scale, land-based, climate change mitigation is projected to increase, which would aggravate existing pressures on land (''high confidence'').''' Climate change mitigation efforts that require large land areas (e.g., bioenergy and afforestation/reforestation) are projected to compete with existing uses of land (''high confidence''). The competition for land could increase food prices and lead to further intensification (e.g., fertiliser and water use) with implications for water and air pollution, and the further loss of biodiversity (''medium confidence''). Such consequences would jeopardise societies’ capacity to achieve many Sustainable Development Goals (SDG) that depend on land (''high confidence''). {1.3.1, Cross-Chapter Box 2 in Chapter 1}<br /> <br /> '''Nonetheless, there are many land-related climate change mitigation options that do not increase the competition for land (''high confidence''). Many of these options have co-benefits for climate change adaptation (''medium confidence'').''' Land use contributes about one-quarter of global greenhouse gas emissions, notably CO&lt;sub&gt;2&lt;/sub&gt; emissions from deforestation, CH&lt;sub&gt;4&lt;/sub&gt; emissions from rice and ruminant livestock and N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertiliser use (''high confidence''). Land ecosystems also take up large amounts of carbon (''high confidence''). Many land management options exist to both reduce the magnitude of emissions and enhance carbon uptake. These options enhance crop productivity, soil nutrient status, microclimate or biodiversity, and thus, support adaptation to climate change (''high confidence''). In addition, changes in consumer behaviour, such as reducing the over-consumption of food and energy would benefit the reduction of GHG emissions from land (''high confidence''). The barriers to the implementation of mitigation and adaptation options include skills deficit, financial and institutional barriers, absence of incentives, access to relevant technologies, consumer awareness and the limited spatial scale at which the success of these practices and methods have been demonstrated. {1.2.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5, 1.3.6}<br /> <br /> '''Sustainable food supply and food consumption, based on nutritionally balanced and diverse diets, would enhance food security under climate and socio-economic changes (''high confidence'').'''Improving food access, utilisation, quality and safety to enhance nutrition, and promoting globally equitable diets compatible with lower emissions have demonstrable positive impacts on land use and food security (''high confidence''). Food security is also negatively affected by food loss and waste (estimated as 25–30% of total food produced) (''medium confidence''). Barriers to improved food security include economic drivers (prices, availability and stability of supply) and traditional, social and cultural norms around food eating practices. Climate change is expected to increase variability in food production and prices globally (''high confidence''), but the trade in food commodities can buffer these effects. Trade can provide embodied flows of water, land and nutrients (''medium confidence''). Food trade can also have negative environmental impacts by displacing the effects of overconsumption (''medium confidence''). Future food systems and trade patterns will be shaped as much by policies as by economics (''medium confidence''). {1.2.1, 1.3.3}<br /> <br /> '''A gender-inclusive approach offers opportunities to enhance the sustainable management of land (''medium confidence'').''' Women play a significant role in agriculture and rural economies globally. In many world regions, laws, cultural restrictions, patriarchy and social structures such as discriminatory customary laws and norms reduce women’s capacity in supporting the sustainable use of land resources (''medium confidence''). Therefore, acknowledging women’s land rights and bringing women’s land management knowledge into land-related decision-making would support the alleviation of land degradation, and facilitate the take-up of integrated adaptation and mitigation measures (''medium confidence''). {1.4.1, 1.4.2}<br /> <br /> '''Regional and country specific contexts affect the capacity to respond to climate change and its impacts, through adaptation and mitigation (''high confidence'').''' There is large variability in the availability and use of land resources between regions, countries and land management systems. In addition, differences in socio-economic conditions, such as wealth, degree of industrialisation, institutions and governance, affect the capacity to respond to climate change, food insecurity, land degradation and desertification. The capacity to respond is also strongly affected by local land ownership. Hence, climate change will affect regions and communities differently (''high confidence''). {1.3, 1.4}<br /> <br /> '''Cross-scale, cross-sectoral and inclusive governance can enable coordinated policy that supports effective adaptation and mitigation (''high confidence'').''' There is a lack of coordination across governance levels, for example, local, national, transboundary and international, in addressing climate change and sustainable land management challenges. Policy design and formulation is often strongly sectoral, which poses further barriers when integrating international decisions into relevant (sub)national policies. A portfolio of policy instruments that are inclusive of the diversity of governance actors would enable responses to complex land and climate challenges (''high confidence''). Inclusive governance that considers women’s and indigenous people’s rights to access and use land enhances the equitable sharing of land resources, fosters food security and increases the existing knowledge about land use, which can increase opportunities for adaptation and mitigation (''medium confidence''). {1.3.5, 1.4.1, 1.4.2, 1.4.3}<br /> <br /> '''Scenarios and models are important tools to explore the trade-offs and co-benefits of land management decisions under uncertain futures (''high confidence'').''' Participatory, co-creation processes with stakeholders can facilitate the use of scenarios in designing future sustainable development strategies (''medium confidence''). In addition to qualitative approaches, models are critical in quantifying scenarios, but uncertainties in models arise from, for example, differences in baseline datasets, land cover classes and modelling paradigms (''medium confidence''). Current scenario approaches are limited in quantifying time-dependent policy and management decisions that can lead from today to desirable futures or visions. Advances in scenario analysis and modelling are needed to better account for full environmental costs and non-monetary values as part of human decision-making processes. {1.2.2, Cross-Chapter Box 1 in Chapter 1}<br /> <br /> == TS.2 Land–climate interactions ==<br /> <br /> === Implications of climate change, variability and extremes for land systems ===<br /> <br /> '''It is certain that globally averaged land surface air temperature (LSAT) has risen faster than the global mean surface temperature (i.e., combined LSAT and sea surface temperature) from the preindustrial period (1850–1900) to the present day (1999–2018). According to the single longest and most extensive dataset, from 1850–1900 to 2006–2015 mean land surface air temperature has increased by 1.53°C (''very likely range ''from 1.38°C to 1.68°C) while global mean surface temperature has increased by 0.87°C (''likely range ''from 0.75°C to 0.99°C). For the 1881–2018 period, when four independently produced datasets exist, the LSAT increase was 1.41°C (1.31–1.51°C), where the range represents the spread in the datasets’ median estimates.''' Analyses of paleo records, historical observations, model simulations and underlying physical principles are all in agreement that LSATs are increasing at a higher rate than SST as a result of differences in evaporation, land–climate feedbacks and changes in the aerosol forcing over land (''very high confidence''). For the 2000–2016 period, the land-to-ocean warming ratio (about 1.6) is in close agreement between different observational records and the CMIP5 climate model simulations (the ''likely range ''of 1.54–1.81). {2.2.1}<br /> <br /> '''Anthropogenic warming has resulted in shifts of climate zones, primarily as an increase in dry climates and decrease of polar climates (''high confidence''). Ongoing warming is projected to result in new, hot climates in tropical regions and to shift climate zones poleward in the mid- to high latitude and upward in regions of higher elevation (''high confidence'').''' Ecosystems in these regions will become increasingly exposed to temperature and rainfall extremes beyond the climate regimes they are currently adapted to (''high confidence''), which can alter their structure, composition and functioning. Additionally, high-latitude warming is projected to accelerate permafrost thawing and increase disturbance in boreal forests through abiotic (e.g., drought, fire) and biotic (e.g., pests, disease) agents (''high confidence''). {2.2.1, 2.2.2, 2.5.3}<br /> <br /> '''Globally, greening trends (trends of increased photosynthetic activity in vegetation) have increased over the last 2–3 decades by 22–33%, particularly over China, India, many parts of Europe, central North America, southeast Brazil and southeast Australia (''high confidence'').''' This results from a combination of direct (i.e., land use and management, forest conservation and expansion) and indirect factors (i.e., CO&lt;sub&gt;2&lt;/sub&gt; fertilisation, extended growing season, global warming, nitrogen deposition, increase of diffuse radiation) linked to human activities (''high confidence''). Browning trends (trends of decreasing photosynthetic activity) are projected in many regions where increases in drought and heatwaves are projected in a warmer climate. There is ''low confidence ''in the projections of global greening and browning trends. {2.2.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> [[File:FigureTS3???.jpg]]<br /> <br /> '''Figure TS.3 | The structure and functioning of managed and unmanaged ecosystems that affect local, regional and global climate.''' Land surface characteristics such as albedo and emissivity determine the amount of solar and long-wave radiation absorbed by land and reflected or emitted to the atmosphere. Surface roughness influences turbulent exchanges of momentum, energy, water and biogeochemical tracers. Land ecosystems modulate the atmospheric composition through emissions and removals of many GHGs and precursors of SLCFs, including biogenic volatile organic compounds (BVOCs) and mineral dust. Atmospheric aerosols formed from these precursors affect regional climate by altering the amounts of precipitation and radiation reaching land surfaces through their role in clouds physics.<br /> <br /> '''The frequency and intensity of some extreme weather and climate events have increased as a consequence of global warming and will continue to increase under medium and high emission scenarios (''high confidence'').''' Recent heat-related events, for example, heatwaves, have been made more frequent or intense due to anthropogenic GHG emissions in most land regions and the frequency and intensity of drought has increased in Amazonia, north-eastern Brazil, the Mediterranean, Patagonia, most of Africa and north-eastern China (''medium confidence''). Heatwaves are projected to increase in frequency, intensity and duration in most parts of the world (''high confidence'') and drought frequency and intensity is projected to increase in some regions that are already drought prone, predominantly in the Mediterranean, central Europe, the southern Amazon and southern Africa (''medium confidence''). These changes will impact ecosystems, food security and land processes including GHG fluxes (''high confidence''). {2.2.5}<br /> <br /> '''Climate change is playing an increasing role in determining wildfire regimes alongside human activity (''medium confidence''), with future climate variability expected to enhance the risk and severity of wildfires in many biomes such as tropical rainforests (''high confidence'').''' Fire weather seasons have lengthened globally between 1979 and 2013 (''low confidence''). Global land area burned has declined in recent decades, mainly due to less burning in grasslands and savannahs (''high confidence''). While drought remains the dominant driver of fire emissions, there has recently been increased fire activity in some tropical and temperate regions during normal to wetter than average years due to warmer temperatures that increase vegetation flammability (''medium confidence''). The boreal zone is also experiencing larger and more frequent fires, and this may increase under a warmer climate (''medium confidence''). {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> === Terrestrial greenhouse gas fluxes on unmanaged and managed lands ===<br /> <br /> '''Agriculture, forestry and other land use (AFOLU) is a significant net source of GHG emissions (''high confidence''), contributing to about 23% of anthropogenic emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), methane (CH&lt;sub&gt;4&lt;/sub&gt;) and nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) combined as CO&lt;sub&gt;2&lt;/sub&gt; equivalents in 2007–2016 (''medium confidence'').''' AFOLU results in both emissions and removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O to and from the atmosphere (''high confidence''). These fluxes are affected simultaneously by natural and human drivers, making it difficult to separate natural from anthropogenic fluxes (''very high confidence''). (Figure TS.3) {2.3}<br /> <br /> '''The total net land-atmosphere flux of CO&lt;sub&gt;2&lt;/sub&gt; on both managed and unmanaged lands ''very likely ''provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;, ''likely range'').''' This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range'') driven by land cover change, including deforestation and afforestation/reforestation, and wood harvesting (accounting for about 13% of total net anthropogenic emissions of CO&lt;sub&gt;2&lt;/sub&gt;) (''medium confidence''), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely'' range) on managed and unmanaged lands, driven by environmental changes such as increasing CO&lt;sub&gt;2&lt;/sub&gt;, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO&lt;sub&gt;2&lt;/sub&gt; emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (''medium confidence''). {2.3.1}<br /> <br /> '''Global models and national GHG inventories use different methods to estimate anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions and removals for the land sector. Consideration of differences in methods can enhance understanding of land sector net emission such as under the Paris Agreement’s global stocktake (''medium confidence'').''' Both models and inventories produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;(''likely range''). {Table SPM.1}<br /> <br /> '''The gross emissions from AFOLU (one-third of total global emissions) are more indicative of mitigation potential of reduced deforestation than the global net emissions (13% of total global emissions), which include compensating deforestation and afforestation fluxes (''high confidence'').''' The net flux of CO&lt;sub&gt;2&lt;/sub&gt; from AFOLU is composed of two opposing gross fluxes:<br /> (i) gross emissions (20 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;), largely from forest growth following wood harvest and agricultural abandonment (''medium confidence''). (Figure TS.4) {2.3.1}<br /> <br /> '''Land is a net source of CH&lt;sub&gt;4&lt;/sub&gt;, accounting for 44% of anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions for the 2006–2017 period (''medium confidence'').''' The pause in the rise of atmospheric CH&lt;sub&gt;4&lt;/sub&gt; concentrations between 2000 and 2006 and the subsequent renewed increase appear to be partially associated with land use and land use change. The recent depletion trend of the 13C isotope in the atmosphere indicates that higher biogenic sources explain part of the current CH&lt;sub&gt;4&lt;/sub&gt; increase and that biogenic sources make up a larger proportion of the source mix than they did before 2000 (''high confidence''). In agreement with the findings of AR5, tropical wetlands and peatlands continue to be important drivers of inter-annual variability and current CH&lt;sub&gt;4&lt;/sub&gt; concentration increases (''medium evidence, high agreement''). Ruminants and the expansion of rice cultivation are also important contributors to the current trend (''medium evidence, high agreement''). There is significant and ongoing accumulation of CH&lt;sub&gt;4&lt;/sub&gt; in the atmosphere (''very high confidence''). {2.3.2}<br /> <br /> [[File:FigureTS4???.jpg]]<br /> <br /> '''Figure TS.4 | Net and gross fluxes of CO2 from land (annual averages for 2008–2017).''' Left: The total net flux of CO2 between land and atmosphere (grey) is shown with its two component fluxes, (i) net AFOLU emissions (blue), and (ii) the net land sink (brown), due to indirect environmental effects and natural effects on managed and unmanaged lands. Middle: The gross emissions and removals contributing to the net AFOLU flux. Right: The gross emissions and removals contributing to the land sink.<br /> <br /> '''AFOLU is the main anthropogenic source of N&lt;sub&gt;2&lt;/sub&gt;O primarily due to nitrogen application to soils (''high confidence'').''' In croplands, the main driver of N&lt;sub&gt;2&lt;/sub&gt;O emissions is a lack of synchronisation between crop nitrogen demand and soil nitrogen supply, with approximately 50% of the nitrogen applied to agricultural land not taken up by the crop. Cropland soils emit over 3 MtN&lt;sub&gt;2&lt;/sub&gt;O-N yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Because the response of N&lt;sub&gt;2&lt;/sub&gt;O emissions to fertiliser application rates is non-linear, in regions of the world where low nitrogen application rates dominate, such as sub-Saharan Africa and parts of Eastern Europe, increases in nitrogen fertiliser use would generate relatively small increases in agricultural N&lt;sub&gt;2&lt;/sub&gt;O emissions. Decreases in application rates in regions where application rates are high and exceed crop demand for parts of the growing season will have very large effects on emissions reductions (''medium evidence, high agreement''). {2.3.3}<br /> <br /> '''While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N&lt;sub&gt;2&lt;/sub&gt;O emissions from grazing lands between 1961 and 2014 with rapid recent increases of nitrogen inputs resulting in disproportionate growth in emissions from these lands (''medium confidence'').''' Grazing lands (pastures and rangelands) are responsible for more than one-third of total anthropogenic N&lt;sub&gt;2&lt;/sub&gt;O emissions or more than one-half of agricultural emissions (''high confidence''). Emissions are largely from North America, Europe, East Asia, and South Asia, but hotspots are shifting from Europe to southern Asia (''medium confidence''). {2.3.3}<br /> <br /> '''Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO&lt;sub&gt;2&lt;/sub&gt; fertilisation (''low confidence'').''' Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration and climate change are not well constrained by observations (''medium confidence''). Nutrient (e.g., nitrogen, phosphorus) availability can limit future plant growth and carbon storage under rising CO&lt;sub&gt;2&lt;/sub&gt; (''high confidence''). However, new evidence suggests that ecosystem adaptation through plant-microbe symbioses could alleviate some nitrogen limitation (''medium evidence, high agreement''). Warming of soils and increased litter inputs will accelerate carbon losses through microbial respiration (''high confidence''). Thawing of high latitude/ altitude permafrost will increase rates of SOC loss and change the balance between CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions (''medium confidence''). The balance between increased respiration in warmer climates and carbon uptake from enhanced plant growth is a key uncertainty for the size of the future land carbon sink (''medium confidence''). {2.3.1, 2.7.2, Box 2.3}<br /> <br /> === Biophysical and biogeochemical land forcing and feedbacks to the climate system ===<br /> <br /> '''Changes in land conditions from human use or climate change in turn affect regional and global climate (''high confidence'').''' On the global scale, this is driven by changes in emissions or removals of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O by land (biogeochemical effects) and by changes in the surface albedo (''very high confidence''). Any local land changes that redistribute energy and water vapour between the land and the atmosphere influence regional climate (biophysical effects; ''high confidence''). However, there is ''no confidence ''in whether such biophysical effects influence global climate. {2.1, 2.3, 2.5.1, 2.5.2}<br /> <br /> '''Changes in land conditions modulate the likelihood, intensity and duration of many extreme events including heatwaves (''high confidence'') and heavy precipitation events (''medium confidence'').''' Dry soil conditions favour or strengthen summer heatwave conditions through reduced evapotranspiration and increased sensible heat. By contrast wet soil conditions, for example from irrigation or crop management practices that maintain a cover crop all year round, can dampen extreme warm events through increased evapotranspiration and reduced sensible heat. Droughts can be intensified by poor land management. Urbanisation increases extreme rainfall events over or downwind of cities (''medium confidence''). {2.5.1, 2.5.2, 2.5.3}<br /> <br /> '''Historical changes in anthropogenic land cover have resulted in a mean annual global warming of surface air from biogeochemical effects (''very high confidence''), dampened by a cooling from biophysical effects (''medium confidence'').''' Biogeochemical warming results from increased emissions of GHGs by land, with model-based estimates of +0.20 ± 0.05°C (global climate models) and +0.24 ± 0.12°C – dynamic global vegetation models (DGVMs) as well as an observation-based estimate of +0.25 ± 0.10°C. A net biophysical cooling of –0.10 ± 0.14°C has been derived from global climate models in response to the increased surface albedo and decreased turbulent heat fluxes, but it is smaller than the warming effect from land-based emissions. However, when both biogeochemical and biophysical effects are accounted for within the same global climate model, the models do not agree on the sign of the net change in mean annual surface air temperature. {2.3, 2.5.1, Box 2.1}<br /> <br /> '''The future projected changes in anthropogenic land cover that have been examined for AR5 would result in a biogeochemical warming and a biophysical cooling whose magnitudes depend on the scenario (''high confidence'').''' Biogeochemical warming has been projected for RCP8.5 by both global climate models (+0.20 ± 0.15°C) and DGVMs (+0.28 ± 0.11°C) (''high confidence''). A global biophysical cooling of 0.10 ± 0.14°C is estimated from global climate models and is projected to dampen the land-based warming (''low confidence''). For RCP4.5, the biogeochemical warming estimated from global climate models (+0.12 ± 0.17°C) is stronger than the warming estimated by DGVMs (+0.01 ± 0.04°C) but based on limited evidence, as is the biophysical cooling (–0.10 ± 0.21°C). {2.5.2}<br /> <br /> '''Regional climate change can be dampened or enhanced by changes in local land cover and land use (''high confidence'') but this depends on the location and the season (''high confidence'').''' In boreal regions, for example, where projected climate change will migrate the treeline northward, increase the growing season length and thaw permafrost, regional winter warming will be enhanced by decreased surface albedo and snow, whereas warming will be dampened during the growing season due to larger evapotranspiration (''high confidence''). In the tropics, wherever climate change will increase rainfall, vegetation growth and associated increase in evapotranspiration will result in a dampening effect on regional warming (''medium confidence''). {2.5.2, 2.5.3}<br /> <br /> '''According to model-based studies, changes in local land cover or available water from irrigation will affect climate in regions as far as few hundreds of kilometres downwind (''high confidence'').''' The local redistribution of water and energy following the changes on land affect the horizontal and vertical gradients of temperature, pressure and moisture, thus altering regional winds and consequently moisture and temperature advection and convection and subsequently, precipitation. {2.5.2, 2.5.4, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Future increases in both climate change and urbanisation will enhance warming in cities and their surroundings (urban heat island), especially during heatwaves (''high confidence'').''' Urban and peri-urban agriculture, and more generally urban greening, can contribute to mitigation (''medium confidence'') as well as to adaptation (''high confidence''), with co-benefits for food security and reduced soil-water-air pollution. {Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Regional climate is strongly affected by natural land aerosols (''medium confidence'') (e.g., mineral dust, black, brown and organic carbon), but there is ''low confidence'' in historical trends, inter-annual and decadal variability and future changes.''' Forest cover affects climate through emissions of biogenic volatile organic compounds (BVOC) and aerosols (''low confidence''). The decrease in the emissions of BVOC resulting from the historical conversion of forests to cropland has resulted in a positive radiative forcing through direct and indirect aerosol effects, a negative radiative forcing through the reduction in the atmospheric lifetime of methane and it has contributed to increased ozone concentrations in different regions (''low confidence''). {2.4, 2.5}<br /> <br /> === Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions) ===<br /> <br /> '''About one-quarter of the 2030 mitigation pledged by countries in their initial Nationally Determined Contributions (NDCs) under the Paris Agreement is expected to come from land-based mitigation options (''medium confidence'').''' Most of the NDCs submitted by countries include land-based mitigation, although many lack details. Several refer explicitly to reduced deforestation and forest sinks, while a few include soil carbon sequestration, agricultural management and bioenergy. Full implementation of NDCs (submitted by February 2016) is expected to result in net removals of 0.4–1.3 GtCO&lt;sub&gt;2&lt;/sub&gt; y&lt;sup&gt;–1 &lt;/sup&gt;in 2030 compared to the net flux in 2010, where the range represents low to high mitigation ambition in pledges, not uncertainty in estimates (''medium confidence''). {2.6.3}<br /> <br /> [[File:FigureTS5???.jpg]]<br /> <br /> '''Figure TS.5 | Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).''' Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO2-eq yr–1 (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2°C and 1.5°C scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’.<br /> <br /> <br /> '''Several mitigation response options have technical potential for &amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;sup&gt; &lt;/sup&gt;by 2050 through reduced emissions and Carbon Dioxide Removal (CDR) (''high confidence''), some of which compete for land and other resources, while others may reduce the demand for land (''high confidence'').''' Estimates of the technical potential of individual response options are not necessarily additive. The largest potential for reducing AFOLU emissions are through reduced deforestation and forest degradation (0.4–5.8 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence''), a shift towards plant-based diets (0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and reduced food and agricultural waste (0.8–4.5 CO&lt;sub&gt;2&lt;/sub&gt;-eq y&lt;sup&gt;r–1&lt;/sup&gt;) (''high confidence''). Agriculture measures combined could mitigate 0.3–3.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''high confidence'') and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;) (''medium confidence''). While some estimates include sustainability and cost considerations, most do not include socio-economic barriers, the impacts of future climate change or non-GHG climate forcings. {2.6.1}<br /> <br /> '''Response options intended to mitigate global warming will also affect the climate locally and regionally through biophysical effects (''high confidence'').''' Expansion of forest area, for example, typically removes CO&lt;sub&gt;2&lt;/sub&gt; from the atmosphere and thus dampens global warming (biogeochemical effect, ''high confidence''), but the biophysical effects can dampen or enhance regional warming depending on location, season and time of day. During the growing season, afforestation generally brings cooler days from increased evapotranspiration, and warmer nights (''high confidence''). During the dormant season, forests are warmer than any other land cover, especially in snow-covered areas where forest cover reduces albedo (''high confidence''). At the global level, the temperature effects of boreal afforestation/reforestation run counter to GHG effects, while in the tropics they enhance GHG effects. In addition, trees locally dampen the amplitude of heat extremes (''medium confidence''). {2.5.2, 2.5.4, 2.7, Cross-Chapter Box 4 in Chapter 2}<br /> <br /> '''Mitigation response options related to land use are a key element of most modelled scenarios that provide strong mitigation, alongside emissions reduction in other sectors (''high confidence''). More stringent climate targets rely more heavily on land-based mitigation options, in particular, CDR (''high confidence'').''' Across a range of scenarios in 2100, CDR is delivered by both afforestation (median values of –1.3, –1.7 and –2.4 GtCO&lt;sub&gt;2&lt;/sub&gt;yr&lt;sup&gt;–1 &lt;/sup&gt;for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;respectively). Emissions of CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O are reduced through improved agricultural and livestock management as well as dietary shifts away from emission-intensive livestock products by 133.2, 108.4 and 73.5 MtCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;; and 7.4, 6.1 and 4.5 MtN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;for the same set of scenarios in 2100 (''high confidence''). High levels of bioenergy crop production can result in increased N&lt;sub&gt;2&lt;/sub&gt;O emissions due to fertiliser use. The Integrated Assessment Models that produce these scenarios mostly neglect the biophysical effects of land-use on global and regional warming. {2.5, 2.6.2}<br /> <br /> '''Large-scale implementation of mitigation response options that limit warming to 1.5 or 2°C would require conversion of large areas of land for afforestation/reforestation and bioenergy crops, which could lead to short-term carbon losses (''high confidence).''' The change of global forest area in mitigation pathways ranges from about –0.2 to +7.2 Mkm&lt;sup&gt;2 &lt;/sup&gt;between 2010 and 2100 (median values across a range of models and scenarios: RCP4.5, RCP2.6, RCP1.9), and the land demand for bioenergy crops ranges from about 3.2 to 6.6 Mkm&lt;sup&gt;2 &lt;/sup&gt;in 2100 (''high confidence''). Large-scale land-based CDR is associated with multiple feasibility and sustainability constraints. In high carbon lands such as forests and peatlands, the carbon benefits of land protection are greater in the short-term than converting land to bioenergy crops for BECCS, which can take several harvest cycles to ‘pay-back’ the carbon emitted during conversion (carbon-debt), from decades to over a century (''medium confidence''). (Figure TS.5) {2.6.2, Chapters 6, 7}<br /> <br /> '''It is possible to achieve climate change targets with low need for land-demanding CDR such as BECCS, but such scenarios rely more on rapidly reduced emissions or CDR from forests, agriculture and other sectors.''' Terrestrial CDR has the technical potential to balance emissions that are difficult to eliminate with current technologies (including food production). Scenarios that achieve climate change targets with less need for terrestrial CDR rely on agricultural demand-side changes (diet change, waste reduction), and changes in agricultural production such as agricultural intensification. Such pathways that minimise land use for bioenergy and BECCS are characterised by rapid and early reduction of GHG emissions in all sectors, as well as earlier CDR in through afforestation. In contrast, delayed mitigation action would increase reliance on land-based CDR (''high confidence''). {2.6.2}<br /> <br /> == TS.3 Desertification ==<br /> <br /> '''Desertification is land degradation in arid, semi-arid, and dry sub-humid areas, collectively known as drylands, resulting from many factors, including human activities and climatic variations. The range and intensity of desertification have increased in some dryland areas over the past several decades (''high confidence'').''' Drylands currently cover about 46.2% (±0.8%) of the global land area and are home to 3 billion people. The multiplicity and complexity of the processes of desertification make its quantification difficult. Desertification hotspots, as identified by a decline in vegetation productivity between the 1980s and 2000s, extended to about 9.2% of drylands (±0.5%), affecting about 500 (±120) million people in 2015. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa and the Middle East including the Arabian Peninsula (''low confidence''). Other dryland regions have also experienced desertification. Desertification has already reduced agricultural productivity and incomes (''high confidence'') and contributed to the loss of biodiversity in some dryland regions (''medium confidence''). In many dryland areas, spread of invasive plants has led to losses in ecosystem services (''high confidence''), while over-extraction is leading to groundwater depletion (''high confidence''). Unsustainable land management, particularly when coupled with droughts, has contributed to higher dust-storm activity, reducing human well-being in drylands and beyond (''high confidence''). Dust storms were associated with global cardiopulmonary mortality of about 402,000 people in 2005. Higher intensity of sand storms and sand dune movements are causing disruption and damage to transportation and solar and wind energy harvesting infrastructures (''high confidence''). (Figure TS.6) {3.1.1, 3.1.4, 3.2.1, 3.3.1, 3.4.1, 3.4.2, 3.4.2, 3.7.3, 3.7.4}<br /> <br /> '''Attribution of desertification to climate variability and change, and to human activities, varies in space and time (''high confidence'').''' Climate variability and anthropogenic climate change, particularly through increases in both land surface air temperature and evapotranspiration, and decreases in precipitation, are likely to have played a role, in interaction with human activities, in causing desertification in some dryland areas. The major human drivers of desertification interacting with climate change are expansion of croplands, unsustainable land management practices and increased pressure on land from population and income growth. Poverty is limiting both capacities to adapt to climate change and availability of financial resources to invest in sustainable land management (SLM) (''high confidence''). {3.1.4, 3.2.2, 3.4.2}<br /> <br /> '''Climate change will exacerbate several desertification processes (''medium confidence'').''' Although CO&lt;sub&gt;2&lt;/sub&gt; fertilisation effect is enhancing vegetation productivity in drylands (''high confidence''), decreases in water availability have a larger effect than CO&lt;sub&gt;2&lt;/sub&gt; fertilisation in many dryland areas. There is ''high confidence ''that aridity will increase in some places, but no evidence for a projected global trend in dryland aridity (''medium confidence''). The area at risk of salinisation is projected to increase in the future (''limited evidence'', ''high agreement''). Future climate change is projected to increase the potential for water driven soil erosion in many dryland areas (''medium confidence''), leading to soil organic carbon decline in some dryland areas. {3.1.1, 3.2.2, 3.5.1, 3.5.2, 3.7.1, 3.7.3}<br /> <br /> '''Risks from desertification are projected to increase due to climate change (''high confidence'').''' Under shared socio-economic pathway SSP2 (‘Middle of the Road’) at 1.5°C, 2°C and 3°C of global warming, the number of dryland population exposed (vulnerable) to various impacts related to water, energy and land sectors (e.g. water stress, drought intensity, habitat degradation) is projected to reach 951 (178) million, 1152 (220) million and 1285 (277) million, respectively. While at global warming of 2°C, under SSP1 (‘Sustainability’), the exposed (vulnerable) dryland population is 974 (35) million, and under SSP3 (‘Fragmented World’) it is 1267 (522) million. Around half of the vulnerable population is in South Asia, followed by Central Asia, West Africa and East Asia. {2.2, 3.1.1, 3.2.2, 3.5.1, 3.5.2, 7.2.2}<br /> <br /> '''Desertification and climate change, both individually and in combination, will reduce the provision of dryland ecosystem services and lower ecosystem health, including losses in biodiversity (''high confidence'').''' Desertification and changing climate are projected to cause reductions in crop and livestock productivity (''high confidence''), modify the composition of plant species and reduce biological diversity across drylands (''medium confidence''). Rising CO&lt;sub&gt;2&lt;/sub&gt; levels will favour more rapid expansion of some invasive plant species in some regions. A reduction in the quality and quantity of resources available to herbivores can have knock-on consequences for predators, which can potentially lead to disruptive ecological cascades (''limited evidence, low agreement''). Projected increases in temperature and the severity of drought events across some dryland areas can increase chances of wildfire occurrence (''medium confidence''). {3.1.4, 3.4.1, 3.5.2, 3.7.3}<br /> <br /> '''Increasing human pressures on land, combined with climate change, will reduce the resilience of dryland populations and constrain their adaptive capacities (''medium confidence'').''' The combination of pressures coming from climate variability, anthropogenic climate change and desertification will contribute to poverty, food insecurity, and increased disease burden (''high confidence''), as well as potentially to conflicts (''low confidence''). Although strong impacts of climate change on migration in dryland areas are disputed (''medium evidence, low agreement''), in some places, desertification under changing climate can provide an added incentive to migrate (''medium confidence''). Women will be impacted more than men by environmental degradation, particularly in those areas with higher dependence on agricultural livelihoods (''medium evidence, high agreement''). {3.4.2, 3.6.2}<br /> <br /> '''Desertification exacerbates climate change through several mechanisms such as changes in vegetation cover, sand and dust aerosols and greenhouse gas fluxes (''high confidence''). The extent of areas in which dryness (rather than temperature) controls CO&lt;sub&gt;2&lt;/sub&gt; exchange has increased by 6% between 1948 and 2012, and is projected to increase by at least another 8% by 2050 if the expansion continues at the same rate. In these areas, net carbon uptake is about 27% lower than in other areas (''low confidence'').''' Desertification also tends to increase albedo, decreasing the energy available at the surface and associated surface temperatures, producing a negative feedback on climate change (''high confidence''). Through its effect on vegetation and soils, desertification changes the absorption and release of associated greenhouse gases (GHGs). Vegetation loss and drying of surface cover due to desertification increases the frequency of dust storms (''high confidence''). Arid ecosystems could be an important global carbon sink, depending on soil water availability (''medium evidence, high agreement''). {3.3.3, 3.4.1, 3.5.2}<br /> <br /> [[File:FigureTS6???.jpg]]<br /> <br /> '''Figure TS.6 | Geographical distribution of drylands, delimited based on the aridity index (AI).''' The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).<br /> <br /> '''Site and regionally-specific technological solutions, based both on new scientific innovations and indigenous and local knowledge (ILK), are available to avoid, reduce and reverse desertification, simultaneously contributing to climate change mitigation and adaptation (''high confidence'').''' SLM practices in drylands increase agricultural productivity and contribute to climate change adaptation with mitigation co-benefits (''high confidence''). Integrated crop, soil and water management measures can be employed to reduce soil degradation and increase the resilience of agricultural production systems to the impacts of climate change (''high confidence''). These measures include crop diversification and adoption of drought-resilient econogically appropriate plants, reduced tillage, adoption of improved irrigation techniques (e.g. drip irrigation) and moisture conservation methods (e.g. rainwater harvesting using indigenous and local practices), and maintaining vegetation and mulch cover. Conservation agriculture increases the capacity of agricultural households to adapt to climate change (''high confidence'') and can lead to increases in soil organic carbon over time, with quantitative estimates of the rates of carbon sequestration in drylands following changes in agricultural practices ranging between 0.04 and 0.4 t ha&lt;sup&gt;–1 &lt;/sup&gt;(''medium confidence''). Rangeland management systems based on sustainable grazing and re-vegetation increase rangeland productivity and the flow of ecosystem services (''high confidence''). The combined use of salt-tolerant crops, improved irrigation practices, chemical remediation measures and appropriate mulch and compost is effective in reducing the impact of secondary salinisation (''medium confidence''). Application of sand dune stabilisation techniques contributes to reducing sand and dust storms (''high confidence''). Agroforestry practices and shelterbelts help reduce soil erosion and sequester carbon. Afforestation programmes aimed at creating windbreaks in the form of ‘green walls’ and ‘green dams’ can help stabilise and reduce dust storms, avert wind erosion, and serve as carbon sinks, particularly when done with locally adapted native and other climate resilient tree species (''high confidence''). {3.4.2, 3.6.1, 3.7.2}<br /> <br /> '''Investments into SLM, land restoration and rehabilitation in dryland areas have positive economic returns (''high confidence'').''' Each USD invested into land restoration can have social returns of about 3–6 USD over a 30-year period. Most SLM practices can become financially profitable within 3 to 10 years (''medium evidence, high agreement''). Despite their benefits in addressing desertification, mitigating and adapting to climate change, and increasing food and economic security, many SLM practices are not widely adopted due to insecure land tenure, lack of access to credit and agricultural advisory services, and insufficient incentives for private land-users (''robust evidence, high agreement''). {3.6.3}<br /> <br /> '''Indigenous and local knowledge often contributes to enhancing resilience against climate change and combating desertification (''medium confidence'').''' Dryland populations have developed traditional agroecological practices which are well adapted to resource-sparse dryland environments. However, there is ''robust evidence'' documenting losses of traditional agroecological knowledge. Traditional agroecological practices are also increasingly unable to cope with growing demand for food. Combined use of ILK and new SLM technologies can contribute to raising the resilience to the challenges of climate change and desertification (''high confidence''). {3.1.3, 3.6.1, 3.6.2}<br /> <br /> '''Policy frameworks promoting the adoption of SLM solutions contribute to addressing desertification as well as mitigating and adapting to climate change, with co-benefits for poverty eradication and food security among dryland populations (''high confidence''). Implementation of Land Degradation Neutrality (LDN) policies allows populations to avoid, reduce and reverse desertification, thus contributing to climate change adaptation with mitigation co-benefits (''high confidence'').''' Strengthening land tenure security is a major factor contributing to the adoption of soil conservation measures in croplands (''high confidence''). On-farm and off-farm livelihood diversification strategies increase the resilience of rural households against desertification and extreme weather events, such as droughts (''high confidence''). Strengthening collective action is important for addressing causes and impacts of desertification, and for adapting to climate change (''medium confidence''). A greater emphasis on understanding gender-specific differences over land use and land management practices can help make land restoration projects more successful (''medium confidence''). Improved access to markets raises agricultural profitability and motivates investment into climate change adaptation and SLM (''medium confidence''). Payments for ecosystem services give additional incentives to land users to adopt SLM practices (''medium confidence''). Expanding access to rural advisory services increases the knowledge on SLM and facilitates their wider adoption (''medium confidence''). Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to reducing desertification and mitigating climate change through decreasing the use of fuelwood and crop residues for energy (''medium confidence''). Policy responses to droughts based on proactive drought preparedness and drought risk mitigation are more efficient in limiting drought-caused damages than reactive drought relief efforts (''high confidence''). {3.4.2, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> '''The knowledge on limits of adaptation to the combined effects of climate change and desertification is insufficient. However, the potential for residual risks and maladaptive outcomes is high (''high confidence'').''' Empirical evidence on the limits to adaptation in dryland areas is limited. Potential limits to adaptation include losses of land productivity due to irreversible forms of desertification. Residual risks can emerge from the inability of SLM measures to fully compensate for yield losses due to climate change impacts. They also arise from foregone reductions in ecosystem services due to soil fertility loss even when applying SLM measures could revert land to initial productivity after some time. Some activities favouring agricultural intensification in dryland areas can become maladaptive due to their negative impacts on the environment (''medium confidence'') Even when solutions are available, social, economic and institutional constraints could pose barriers to their implementation (''medium confidence'') {3.6.4}.<br /> <br /> '''Improving capacities, providing higher access to climate services, including local-level early warning systems, and expanding the use of remote sensing technologies are high-return investments for enabling effective adaptation and mitigation responses that help address desertification (''high confidence'').''' Reliable and timely climate services, relevant to desertification, can aid the development of appropriate adaptation and mitigation options reducing, the impact of desertification on human and natural systems (''high confidence''), with quantitative estimates showing that every USD invested in strengthening hydro-meteorological and early warning services in developing countries can yield between 4 and 35 USD (''low confidence''). Knowledge and flow of knowledge on desertification is currently fragmented. Improved knowledge and data exchange and sharing will increase the effectiveness of efforts to achieve LDN (''high confidence''). Expanded use of remotely sensed information for data collection helps in measuring progress towards achieving LDN (''low evidence, high agreement''). {3.2.1, 3.6.2, 3.6.3, Cross-Chapter Box 5 in Chapter 3}<br /> <br /> == TS.4 Land degradation ==<br /> <br /> '''Land degradation affects people and ecosystems throughout the planet and is both affected by climate change and contributes to it.''' In this report, land degradation is defined as a ''negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity, or value to humans. ''Forest degradation is land degradation that occurs in forest land. Deforestation is the conversion of forest to non-forest land and can result in land degradation. {4.1.3}<br /> <br /> '''Land degradation adversely affects people’s livelihoods (''very high confidence'') and occurs over a quarter of the Earth’s ice-free land area (''medium confidence''). The majority of the 1.3 to 3.2 billion affected people (''low confidence'') are living in poverty in developing countries (''medium confidence'').''' Land-use changes and unsustainable land management are direct human causes of land degradation (''very high confidence''), with agriculture being a dominant sector driving degradation (''very high confidence''). Soil loss from conventionally tilled land exceeds the rate of soil formation by &amp;gt;2 orders of magnitude (''medium confidence''). Land degradation affects humans in multiple ways, interacting with social, political, cultural and economic aspects, including markets, technology, inequality and demographic change (''very high confidence''). Land degradation impacts extend beyond the land surface itself, affecting marine and freshwater systems, as well as people and ecosystems far away from the local sites of degradation (''very high confidence''). {4.1.6, 4.2.1, 4.2.3, 4.3, 4.6.1, 4.7, Table 4.1}<br /> <br /> '''Climate change exacerbates the rate and magnitude of several ongoing land degradation processes and introduces new degradation patterns (''high confidence'').''' Human-induced global warming has already caused observed changes in two drivers of land degradation: increased frequency, intensity and/or amount of heavy precipitation (''medium confidence''); and increased heat stress (''high confidence''). In some areas sea level rise has exacerbated coastal erosion (''medium confidence''). Global warming beyond present day will further exacerbate ongoing land degradation processes through increasing floods (''medium confidence''), drought frequency and severity (''medium confidence''), intensified cyclones (''medium confidence''), and sea level rise (''very high confidence''), with outcomes being modulated by land management (''very high confidence''). Permafrost thawing due to warming (''high confidence''), and coastal erosion due to sea level rise and impacts of changing storm paths (''low confidence''), are examples of land degradation affecting places where it has not typically been a problem. Erosion of coastal areas because of sea level rise will increase worldwide (''high confidence''). In cyclone prone areas, the combination of sea level rise and more intense cyclones will cause land degradation with serious consequences for people and livelihoods (''very high confidence''). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1}<br /> <br /> '''Land degradation and climate change, both individually and in combination, have profound implications for natural resource-based livelihood systems and societal groups (''high confidence'').''' The number of people whose livelihood depends on degraded lands has been estimated to be about 1.5 billion worldwide (''very low confidence''). People in degraded areas who directly depend on natural resources for subsistence, food security and income, including women and youth with limited adaptation options, are especially vulnerable to land degradation and climate change (''high confidence''). Land degradation reduces land productivity and increases the workload of managing the land, affecting women disproportionally in some regions. Land degradation and climate change act as threat multipliers for already precarious livelihoods (''very high confidence''), leaving them highly sensitive to extreme climatic events, with consequences such as poverty and food insecurity (''high confidence'') and, in some cases, migration, conflict and loss of cultural heritage (''low confidence''). Changes in vegetation cover and distribution due to climate change increase the risk of land degradation in some areas (''medium confidence''). Climate change will have detrimental effects on livelihoods, habitats and infrastructure through increased rates of land degradation (''high confidence'') and from new degradation patterns (''low evidence, high agreement''). {4.1.6, 4.2.1, 4.7}<br /> <br /> '''Land degradation is a driver of climate change through emission of greenhouse gases (GHGs) and reduced rates of carbon uptake (''very high confidence'').''' Since 1990, globally the forest area has decreased by 3% (''low confidence'') with net decreases in the tropics and net increases outside the tropics (''high confidence''). Lower carbon density in re-growing forests compared, to carbon stocks before deforestation, results in net emissions from land-use change (''very high confidence''). Forest management that reduces carbon stocks of forest land also leads to emissions, but global estimates of these emissions are uncertain. Cropland soils have lost 20–60% of their organic carbon content prior to cultivation, and soils under conventional agriculture continue to be a source of GHGs (''medium confidence''). Of the land degradation processes, deforestation, increasing wildfires, degradation of peat soils, and permafrost thawing contribute most to climate change through the release of GHGs and the reduction in land carbon sinks following deforestation (''high confidence''). Agricultural practices also emit non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs from soils and these emissions are exacerbated by climate change (''medium confidence''). Conversion of primary to managed forests, illegal logging and unsustainable forest management result in GHG emissions (''very high confidence'') and can have additional physical effects on the regional climate including those arising from albedo shifts (''medium confidence''). These interactions call for more integrative climate impact assessments. {4.2.2, 4.3, 4.5.4, 4.6}<br /> <br /> '''Large-scale implementation of dedicated biomass production for bioenergy increases competition for land with potentially serious consequences for food security and land degradation (''high confidence'').''' Increasing the extent and intensity of biomass production, for example, through fertiliser additions, irrigation or monoculture energy plantations, can result in local land degradation. Poorly implemented intensification of land management contributes to land degradation (e.g., salinisation from irrigation) and disrupted livelihoods (''high confidence''). In areas where afforestation and reforestation occur on previously degraded lands, opportunities exist to restore and rehabilitate lands with potentially significant co-benefits (''high confidence'') that depend on whether restoration involves natural or plantation forests. The total area of degraded lands has been estimated at 10–60 Mkm&lt;sup&gt;2 &lt;/sup&gt;(''very low confidence''). The extent of degraded and marginal lands suitable for dedicated biomass production is highly uncertain and cannot be established without due consideration of current land use and land tenure. Increasing the area of dedicated energy crops can lead to land degradation elsewhere through indirect land-use change (''medium confidence''). Impacts of energy crops can be reduced through strategic integration with agricultural and forestry systems (''high confidence'') but the total quantity of biomass that can be produced through synergistic production systems is unknown. {4.1.6, 4.4.2, 4.5, 4.7.1, 4.8.1, 4.8.3, 4.8.4, 4.9.3}<br /> <br /> '''Reducing unsustainable use of traditional biomass reduces land degradation and emissions of CO&lt;sub&gt;2&lt;/sub&gt; while providing social and economic co-benefits (''very high confidence'').''' Traditional biomass in the form of fuelwood, charcoal and agricultural residues remains a primary source of energy for more than one-third of the global population, leading to unsustainable use of biomass resources and forest degradation and contributing around 2% of global GHG emissions (''low confidence''). Enhanced forest protection, improved forest and agricultural management, fuel-switching and adoption of efficient cooking and heating appliances can promote more sustainable biomass use and reduce land degradation, with co-benefits of reduced GHG emissions, improved human health, and reduced workload especially for women and youth (''very high confidence''). {4.1.6, 4.5.4}<br /> <br /> [[File:FigureTS7???.jpg]]<br /> <br /> '''Figure TS.7 | Conceptual figure illustrating that climate change impacts interact with land management to determine sustainable or degraded outcome.''' Climate change can exacerbate many degradation processes (Table 4.1) and introduce novel ones (e.g., permafrost thawing or biome shifts), hence management needs to respond to climate impacts in order to avoid, reduce or reverse degradation. The types and intensity of human land-use and climate change impacts on lands affect their carbon stocks and their ability to operate as carbon sinks. In managed agricultural lands, degradation typically results in reductions of soil organic carbon stocks, which also adversely affects land productivity and carbon sinks. In forest land, reduction in biomass carbon stocks alone is not necessarily an indication of a reduction in carbon sinks. Sustainably managed forest landscapes can have a lower biomass carbon density but the younger forests can have a higher growth rate, and therefore contribute stronger carbon sinks, than older forests. Ranges of carbon sinks in forest and agricultural lands are overlapping. In some cases, climate change impacts may result in increased productivity and carbon stocks, at least in the short term.<br /> <br /> [[File:FigureTS8???.jpg]]<br /> <br /> '''Figure TS.8 | Interaction of human and climate drivers can exacerbate desertification and land degradation. Figure shows key desertification and land degradation issues, how they impact climate change, and the key drivers, with potential solutions.''' Climate change exacerbates the rate and magnitude of several ongoing land degradation and desertification processes. Human drivers of land degradation and desertification include expanding agriculture, agricultural practices and forest management. In turn, land degradation and desertification are also drivers of climate change through GHG emissions, reduced rates of carbon uptake, and reduced capacity of ecosystems to act as carbon sinks into the future. Impacts on climate change are either warming (in red) or cooling (in blue).<br /> <br /> '''Land degradation can be avoided, reduced or reversed by implementing sustainable land management, restoration and rehabilitation practices that simultaneously provide many co-benefits, including adaptation to and mitigation of climate change (''high confidence'').''' Sustainable land management involves a comprehensive array of technologies and enabling conditions, which have proven to address land degradation at multiple landscape scales, from local farms (''very high confidence'') to entire watersheds (''medium confidence''). Sustainable forest management can prevent deforestation, maintain and enhance carbon sinks and can contribute towards GHG emissions-reduction goals. Sustainable forest management generates socio-economic benefits, and provides fibre, timber and biomass to meet society’s growing needs. While sustainable forest management sustains high carbon sinks, the conversion from primary forests to sustainably managed forests can result in carbon emission during the transition and loss of biodiversity (''high confidence''). Conversely, in areas of degraded forests, sustainable forest management can increase carbon stocks and biodiversity (''medium confidence''). Carbon storage in long-lived wood products and reductions of emissions from use of wood products to substitute for emissions-intensive materials also contribute to mitigation objectives. (Figure TS.8) {4.8, 4.9, Table 4.2}<br /> <br /> '''Lack of action to address land degradation will increase emissions and reduce carbon sinks and is inconsistent with the emissions reductions required to limit global warming to 1.5°C or 2°C. (''high confidence'').''' Better management of soils can offset 5–20% of current global anthropogenic GHG emissions (''medium confidence''). Measures to avoid, reduce and reverse land degradation are available but economic, political, institutional, legal and socio-cultural barriers, including lack of access to resources and knowledge, restrict their uptake (''very high confidence''). Proven measures that facilitate implementation of practices that avoid, reduce, or reverse land degradation include tenure reform, tax incentives, payments for ecosystem services, participatory integrated land-use planning, farmer networks and rural advisory services. Delayed action increases the costs of addressing land degradation, and can lead to irreversible biophysical and human outcomes (''high confidence''). Early actions can generate both site-specific and immediate benefits to communities affected by land degradation, and contribute to long-term global benefits through climate change mitigation (''high confidence''). (Figure TS.7) {4.1.5, 4.1.6, 4.7.1, 4.8, Table 4.2}<br /> <br /> '''Even with adequate implementation of measures to avoid, reduce and reverse land degradation, there will be residual degradation in some situations (''high confidence'').''' Limits to adaptation are dynamic, site specific and determined through the interaction of biophysical changes with social and institutional conditions. Exceeding the limits of adaptation will trigger escalating losses or result in undesirable changes, such as forced migration, conflicts, or poverty. Examples of potential limits to adaptation due to climate-change-induced land degradation are coastal erosion (where land disappears, collapsing infrastructure and livelihoods due to thawing of permafrost), and extreme forms of soil erosion. {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}<br /> <br /> '''Land degradation is a serious and widespread problem, yet key uncertainties remain concerning its extent, severity, and linkages to climate change (''very high confidence'').''' Despite the difficulties of objectively measuring the extent and severity of land degradation, given its complex and value-based characteristics, land degradation represents – along with climate change – one of the biggest and most urgent challenges for humanity (''very high confidence''). The current global extent, severity and rates of land degradation are not well quantified. There is no single method by which land degradation can be measured objectively and consistently over large areas because it is such a complex and value-laden concept (''very high confidence''). However, many existing scientific and locally based approaches, including the use of ILK, can assess different aspects of land degradation or provide proxies. Remote sensing, corroborated by other data, can generate geographically explicit and globally consistent data that can be used as proxies over relevant time scales (several decades). Few studies have specifically addressed the impacts of proposed land-based negative emission technologies on land degradation. Much research has tried to understand how livelihoods and ecosystems are affected by a particular stressor – for example, drought, heat stress, or waterlogging. Important knowledge gaps remain in understanding how plants, habitats and ecosystems are affected by the cumulative and interacting impacts of several stressors, including potential new stressors resulting from large-scale implementation of negative emission technologies. {4.10}<br /> <br /> == TS.5 Food security ==<br /> <br /> '''The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people.''' Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability). (Figure TS.9) {5.1.1, 5.1.2}<br /> <br /> '''Observed climate change is already affecting food security through increasing temperatures, changing precipitation patterns, and greater frequency of some extreme events (''high confidence'').''' Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades. Warming compounded by drying has caused large negative effects on yields in parts of the Mediterranean. Based on ILK, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America. (Figure TS.10) {5.2.2}<br /> <br /> '''Food security will be increasingly affected by projected future climate change (''high confidence'').''' Across SSPs 1, 2, and 3, global crop and economic models projected a 1–29% cereal price increase in 2050 due to climate change (RCP 6.0), which would impact consumers globally through higher food prices; regional effects will vary (''high confidence''). Low-income consumers are particularly at risk, with models projecting increases of 1–183 million additional people at risk of hunger across the SSPs compared to a no climate change scenario (''high confidence''). While increased CO&lt;sub&gt;2&lt;/sub&gt; is projected to be beneficial for crop productivity at lower temperature increases, it is projected to lower nutritional quality (''high confidence'') (e.g., wheat grown at 546–586 ppm CO&lt;sub&gt;2&lt;/sub&gt; has 5.9–12.7% less protein, 3.7–6.5% less zinc, and 5.2–7.5% less iron). Distributions of pests and diseases will change, affecting production negatively in many regions (''high confidence''). Given increasing extreme events and interconnectedness, risks of food system disruptions are growing (''high confidence''). {5.2.3, 5.2.4}<br /> <br /> '''Vulnerability of pastoral systems to climate change is very high (''high confidence'').''' Pastoralism is practiced in more than 75% of countries by between 200 and 500 million people, including nomadic communities, transhumant herders, and agropastoralists. Impacts in pastoral systems in Africa include lower pasture and animal productivity, damaged reproductive function, and biodiversity loss. Pastoral system vulnerability is exacerbated by non-climate factors (land tenure, sedentarisation, changes in traditional institutions, invasive species, lack of markets, and conflicts). {5.2.2}<br /> <br /> [[File:FigureTS9???.jpg]]<br /> <br /> '''Figure TS.9 | Global trends in (a)''' yields of maize, rice, and wheat (FAOSTAT 2018) – the top three crops grown in the world; '''(b)''' production of crop and animal calories and use of crop calories as livestock feed (FAOSTAT 2018); '''(c)''' production from marine and aquaculture fisheries (FishStat 2019); '''(d)''' land used for agriculture (FAOSTAT 2018); '''(e)''' food trade in calories (FAOSTAT 2018); '''(f)''' food supply and required food (i.e., based on human energy requirements for medium physical activities) from 1961–2012 (FAOSTAT 2018; Hiç et al. 2016); '''(g)''' prevalence of overweight, obesity and underweight from 1975–2015 (Abarca-Gómez et al. 2017); and '''(h)''' GHG emissions for the agriculture sector, excluding land-use change (FAOSTAT 2018). For figures (b) and (e), data provided in mass units were converted into calories using nutritive factors (FAO 2001b). Data on emissions due to burning of savanna and cultivation of organic soils is provided only after 1990 (FAOSTAT 2018).<br /> <br /> '''Fruit and vegetable production, a key component of healthy diets, is also vulnerable to climate change (''medium evidence, high agreement'').''' Declines in yields and crop suitability are projected under higher temperatures, especially in tropical and semi-tropical regions. Heat stress reduces fruit set and speeds up development of annual vegetables, resulting in yield losses, impaired product quality, and increasing food loss and waste. Longer growing seasons enable a greater number of plantings to be cultivated and can contribute to greater annual yields. However, some fruits and vegetables need a period of cold accumulation to produce a viable harvest, and warmer winters may constitute a risk. {5.2.2}<br /> <br /> '''Food security and climate change have strong gender and equity dimensions (''high confidence'').''' Worldwide, women play a key role in food security, although regional differences exist. Climate change impacts vary among diverse social groups depending on age, ethnicity, gender, wealth, and class. Climate extremes have immediate and long-term impacts on livelihoods of poor and vulnerable communities, contributing to greater risks of food insecurity that can be a stress multiplier for internal and external migration (''medium confidence''). Empowering women and rights-based approaches to decision-making can create synergies among household food security, adaptation, and mitigation. {5.2.6, 5.6.4}<br /> <br /> '''Many practices can be optimised and scaled up to advance adaptation throughout the food system (''high confidence'').''' Supply-side options include increased soil organic matter and erosion control, improved cropland, livestock, grazing land management, and genetic improvements for tolerance to heat and drought. Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources, and heterogeneous diets) is a key strategy to reduce risks (''medium confidence''). Demand-side adaptation, such as adoption of healthy and sustainable diets, in conjunction with reduction in food loss and waste, can contribute to adaptation through reduction in additional land area needed for food production and associated food system vulnerabilities. ILK can contribute to enhancing food system resilience (''high confidence''). {5.3, 5.6.3 Cross-Chapter Box 6 in Chapter 5}.<br /> <br /> '''About 21–37% of total greenhouse gas (GHG) emissions are attributable to the food system. These are from agriculture and land use, storage, transport, packaging, processing, retail, and consumption (''medium confidence'').''' This estimate includes emissions of 9–14% from crop and livestock activities within the farm gate and 5–14% from land use and land-use change including deforestation and peatland degradation (''high confidence''); 5–10% is from supply chain activities (''medium confidence''). This estimate includes GHG emissions from food loss and waste. Within the food system, during the period 2007–2016, the major sources of emissions from the supply side were agricultural production, with crop and livestock activities within the farm gate generating respectively 142 ± 42 TgCH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;–1 &lt;/sup&gt;(''high confidence'') and 8.0 ± 2.5 TgN&lt;sub&gt;2&lt;/sub&gt;O yr&lt;sup&gt;–1 &lt;/sup&gt;(high confidence), and CO&lt;sub&gt;2&lt;/sub&gt; emissions linked to relevant land-use change dynamics such as deforestation and peatland degradation, generating 4.9 ± 2.5 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–1&lt;/sup&gt;. Using 100-year GWP values (no climate feedback) from the IPCC AR5, this implies that total GHG emissions from agriculture were 6.2 ± 1.4 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1&lt;/sup&gt;, increasing to 11.1 ± 2.9 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;including relevant land use. Without intervention, these are likely to increase by about 30–40% by 2050, due to increasing demand based on population and income growth and dietary change (''high confidence''). {5.4}<br /> <br /> '''Supply-side practices can contribute to climate change mitigation by reducing crop and livestock emissions, sequestering carbon in soils and biomass, and by decreasing emissions intensity within sustainable production systems (''high confidence'').''' Total technical mitigation potential from crop and livestock activities and agroforestry is estimated as 2.3–9.6 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). Options with large potential for GHG mitigation in cropping systems include soil carbon sequestration (at decreasing rates over time), reductions in N&lt;sub&gt;2&lt;/sub&gt;O emissions from fertilisers, reductions in CH&lt;sub&gt;4&lt;/sub&gt; emissions from paddy rice, and bridging of yield gaps. Options with large potential for mitigation in livestock systems include better grazing land management, with increased net primary production and soil carbon stocks, improved manure management, and higher-quality feed. Reductions in GHG emissions intensity (emissions per unit product) from livestock can support reductions in absolute emissions, provided appropriate governance to limit total production is implemented at the same time (''medium confidence''). {5.5.1}<br /> <br /> '''Consumption of healthy and sustainable diets presents major opportunities for reducing GHG emissions from food systems and improving health outcomes (''high confidence'').''' Examples of healthy and sustainable diets are high in coarse grains, pulses, fruits and vegetables, and nuts and seeds; low in energy-intensive animal-sourced and discretionary foods (such as sugary beverages); and with a carbohydrate threshold. Total technical mitigation potential of dietary changes is estimated as 0.7–8.0 GtCO&lt;sub&gt;2&lt;/sub&gt;-eq yr&lt;sup&gt;–1 &lt;/sup&gt;by 2050 (''medium confidence''). This estimate includes reductions in emissions from livestock and soil carbon sequestration on spared land, but co-benefits with health are not taken into account. Mitigation potential of dietary change may be higher, but achievement of this potential at broad scales depends on consumer choices and dietary preferences that are guided by social, cultural, environmental, and traditional factors, as well as income growth. Meat analogues such as imitation meat (from plant products), cultured meat, and insects may help in the transition to more healthy and sustainable diets, although their carbon footprints and acceptability are uncertain. {5.5.2, 5.6.5}<br /> <br /> '''Reduction of food loss and waste could lower GHG emissions and improve food security (''medium confidence'').''' Combined food loss and waste amount to 25–30% of total food produced (''medium confidence''). During 2010–2016, global food loss and waste equalled 8–10% of total anthropogenic GHG emissions (''medium confidence''); and cost about 1 trillion USD2012 per year (''low confidence''). Technical options for reduction of food loss and waste include improved harvesting techniques, on-farm storage, infrastructure, and packaging. Causes of food loss (e.g., lack of refrigeration) and waste (e.g., behaviour) differ substantially in developed and developing countries, as well as across regions (''robust evidence, medium agreement''). {5.5.2}<br /> <br /> '''Agriculture and the food system are key to global climate change responses. Combining supply-side actions such as efficient production, transport, and processing with demand-side interventions such as modification of food choices, and reduction of food loss and waste, reduces GHG emissions and enhances food system resilience (''high confidence'').''' Such combined measures can enable the implementation of large-scale land-based adaptation and mitigation strategies without threatening food security from increased competition for land for food production and higher food prices. Without combined food system measures in farm management, supply chains, and demand, adverse effects would include increased numbers of malnourished people and impacts on smallholder farmers (''medium evidence, high agreement''). Just transitions are needed to address these effects. (Figure TS.11) {5.5, 5.6, 5.7}<br /> <br /> '''For adaptation and mitigation throughout the food system, enabling conditions need to be created through policies, markets, institutions, and governance (''high confidence'').''' For adaptation, resilience to increasing extreme events can be accomplished through risk sharing and transfer mechanisms such as insurance markets and index-based weather insurance (''high confidence''). Public health policies to improve nutrition – such as school procurement, health insurance incentives, and awareness-raising campaigns – can potentially change demand, reduce healthcare costs, and contribute to lower GHG emissions (''limited evidence, high agreement''). Without inclusion of comprehensive food system responses in broader climate change policies, the mitigation and adaptation potentials assessed in Chapter 5 will not be realised and food security will be jeopardised (''high confidence''). {5.7.5}<br /> <br /> == TS.6 Interlinkages between desertification, land degradation, food security and GHG fluxes: Synergies, trade-offs and integrated response options ==<br /> <br /> '''The land challenges, in the context of this report, are climate change mitigation, adaptation, desertification, land degradation, and food security.''' The chapter also discusses implications for Nature’s Contributions to People (NCP), including biodiversity and water, and sustainable development, by assessing intersections with the Sustainable Development Goals (SDGs). The chapter assesses response options that could be used to address these challenges. These response options were derived from the previous chapters and fall into three broad categories: land management, value chain, and risk management.<br /> <br /> '''The land challenges faced today vary across regions; climate change will increase challenges in the future, while socio-economic development could either increase or decrease challenges (''high confidence'').''' Increases in biophysical impacts from climate change can worsen desertification, land degradation, and food insecurity (''high confidence''). Additional pressures from socio-economic development could further exacerbate these challenges; however, the effects are scenario dependent. Scenarios with increases in income and reduced pressures on land can lead to reductions in food insecurity; however, all assessed scenarios result in increases in water demand and water scarcity (''medium confidence''). {6.1}<br /> <br /> '''The applicability and efficacy of response options are region and context specific; while many value chain and risk management options are potentially broadly applicable, many land management options are applicable on less than 50% of the ice-free land surface (''high confidence'').''' Response options are limited by land type, bioclimatic region, or local food system context (''high confidence''). Some response options produce adverse side effects only in certain regions or contexts; for example, response options that use freshwater may have no adverse side effects in regions where water is plentiful, but large adverse side effects in regions where water is scarce (''high confidence''). Response options with biophysical climate effects (e.g., afforestation, reforestation) may have different effects on local climate, depending on where they are implemented (''medium confidence''). Regions with more challenges have fewer response options available for implementation (''medium confidence''). {6.1, 6.2, 6.3, 6.4}<br /> <br /> '''Nine options deliver medium-to-large benefits for all five land challenges (''high confidence'').''' The options with medium-to-large benefits for all challenges are increased food productivity, improved cropland management, improved grazing land management, improved livestock management, agroforestry, forest management, increased soil organic carbon content, fire management and reduced post-harvest losses. A further two options, dietary change and reduced food waste, have no global estimates for adaptation but have medium-to-large benefits for all other challenges (''high confidence''). {6.3, 6.4}<br /> <br /> '''Five options have large mitigation potential (&amp;gt;3 GtCO&lt;sub&gt;2&lt;/sub&gt;e yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) without adverse impacts on the other challenges (''high confidence'').''' These are: increased food productivity; reduced deforestation and forest degradation; increased soil organic carbon content; fire management; and reduced post-harvest losses. Two further options with large mitigation potential, dietary change and reduced food waste, have no global estimates for adaptation but show no negative impacts across the other challenges. Five options: improved cropland management; improved grazing land managements; agroforestry; integrated water management; and forest management, have moderate mitigation potential, with no adverse impacts on the other challenges (''high confidence''). {6.3.6}<br /> <br /> '''Sixteen response options have large adaptation potential (more than 25 million people benefit), without adverse side effects on other land challenges (''high confidence'').''' These are increased food productivity, improved cropland management, agroforestry, agricultural diversification, forest management, increased soil organic carbon content, reduced landslides and natural hazards, restoration and reduced conversion of coastal wetlands, reduced post-harvest losses, sustainable sourcing, management of supply chains, improved food processing and retailing, improved energy use in food systems, livelihood diversification, use of local seeds, and disaster risk management (''high confidence''). Some options (such as enhanced urban food systems or management of urban sprawl) may not provide large global benefits but may have significant positive local effects without adverse effects (''high confidence''). (Figure TS.13) {6.3, 6.4}<br /> <br /> '''Seventeen of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs; only three options (afforestation, BECCS), and some types of risk sharing instruments, such as insurance) have potentially adverse side effects for five or more NCPs or SDGs (''medium confidence'').''' The 17 options with co-benefits and no adverse side effects include most agriculture- and soil-based land management options, many ecosystem-based land management options, forest management, reduced post-harvest losses, sustainable sourcing, improved energy use in food systems, and livelihood diversification (''medium confidence''). Some of the synergies between response options and SDGs include positive poverty eradication impacts from activities like improved water management or improved management of supply chains. Examples of synergies between response options and NCPs include positive impacts on habitat maintenance from activities like invasive species management and agricultural diversification. However, many of these synergies are not automatic, and are dependent on well-implemented activities requiring institutional and enabling conditions for success. {6.4}<br /> <br /> '''Most response options can be applied without competing for available land; however, seven options result in competition for land (''medium confidence'').''' A large number of response options do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at scale: afforestation, reforestation, and land used to provide feedstock for BECCS or biochar, with three further options: reduced grassland conversion to croplands, restoration and reduced conversion of peatlands and restoration, and reduced conversion of coastal wetlands having smaller or variable impacts on competition for land. Other options such as reduced deforestation and forest degradation, restrict land conversion for other options and uses. Expansion of the current area of managed land into natural ecosystems could have negative consequences for other land challenges, lead to the loss of biodiversity, and adversely affect a range of NCPs (''high confidence''). {6.3.6, 6.4}<br /> <br /> '''Some options, such as bioenergy and BECCS, are scale dependent. The climate change mitigation potential for bioenergy and BECCS is large (up to 11 GtCO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;–&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;); however, the effects of bioenergy production on land degradation, food insecurity, water scarcity, GHG emissions, and other environmental goals are scale- and context-specific (''high confidence'').''' These effects depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon stocks, climatic region and management regime (''high confidence''). Large areas of monoculture bioenergy crops that displace other land uses can result in land competition, with adverse effects for food production, food consumption, and thus food security, as well as adverse effects for land degradation, biodiversity, and water scarcity (''medium confidence''). However, integration of bioenergy into sustainably managed agricultural landscapes can ameliorate these challenges (''medium confidence''). {6.2, 6.3, 6.4, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Response options are interlinked; some options (e.g., land sparing and sustainable land management options) can enhance the co-benefits or increase the potential for other options (''medium confidence'').''' Some response options can be more effective when applied together (''medium confidence''); for example, dietary change and waste reduction expand the potential to apply other options by freeing as much as 5.8 Mkm&lt;sup&gt;2 &lt;/sup&gt;(0.8–2.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for dietary change; about 2 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced post-harvest losses, and 1.4 Mkm&lt;sup&gt;2 &lt;/sup&gt;for reduced food waste) of land (''low confidence''). Integrated water management and increased soil organic carbon can increase food productivity in some circumstances. {6.4}<br /> <br /> '''Other response options (e.g., options that require land) may conflict; as a result, the potentials for response options are not all additive, and a total potential from the land is currently unknown (''high confidence'').''' Combining some sets of options (e.g., those that compete for land) may mean that maximum potentials cannot be realised, for example, reforestation, afforestation, and bioenergy and BECCS, all compete for the same finite land resource so the combined potential is much lower than the sum of potentials of each individual option, calculated in the absence of alternative uses of the land (''high confidence''). Given the interlinkages among response options and that mitigation potentials for individual options assume that they are applied to all suitable land, the total mitigation potential is much lower than the sum of the mitigation potential of the individual response options (''high confidence''). (Figure TS.12) {6.4}<br /> <br /> '''The feasibility of response options, including those with multiple co-benefits, is limited due to economic, technological, institutional, socio-cultural, environmental and geophysical barriers (''high confidence'').''' A number of response options (e.g., most agriculture-based land management options, forest management, reforestation and restoration) have already been implemented widely to date (''high confidence''). There is ''robust evidence ''that many other response options can deliver co-benefits across the range of land challenges, yet these are not being implemented. This limited application is evidence that multiple barriers to implementation of response options exist (''high confidence''). {6.3, 6.4}<br /> <br /> '''Coordinated action is required across a range of actors, including business, producers, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions for adoption of response options (''high confidence'').''' The response options assessed face a variety of barriers to implementation (economic, technological, institutional, socio-cultural, environmental and geophysical) that require action across multiple actors to overcome (''high confidence''). There are a variety of response options available at different scales that could form portfolios of measures applied by different stakeholders – from farm to international scales. For example, agricultural diversification and use of local seeds by smallholders can be particularly useful poverty eradication and biodiversity conservation measures, but are only successful when higher scales, such as national and international markets and supply chains, also value these goods in trade regimes, and consumers see the benefits of purchasing these goods. However, the land and food sectors face particular challenges of institutional fragmentation, and often suffer from a lack of engagement between stakeholders at different scales (''medium confidence''). {6.3, 6.4}<br /> <br /> '''Delayed action will result in an increased need for response to land challenges and a decreased potential for land-based response options due to climate change and other pressures (''high confidence'').''' For example, failure to mitigate climate change will increase requirements for adaptation and may reduce the efficacy of future land-based mitigation options (''high confidence''). The potential for some land management options decreases as climate change increases; for example, climate alters the sink capacity for soil and vegetation carbon sequestration, reducing the potential for increased soil organic carbon (''high confidence''). Other options (e.g., reduced deforestation and forest degradation) prevent further detrimental effects to the land surface; delaying these options could lead to increased deforestation, conversion, or degradation, serving as increased sources of GHGs and having concomitant negative impacts on NCPs (''medium confidence''). Carbon dioxide removal (CDR) options – such as reforestation, afforestation, bioenergy and BECCS – are used to compensate for unavoidable emissions in other sectors; delayed action will result in larger and more rapid deployment later (''high confidence''). Some response options will not be possible if action is delayed too long; for example, peatland restoration might not be possible after certain thresholds of degradation have been exceeded, meaning that peatlands could not be restored in certain locations (''medium confidence'') {6.2, 6.3, 6.4}.<br /> <br /> '''Early action, however, has challenges including technological readiness, upscaling, and institutional barriers (''high confidence'').''' Some of the response options have technological barriers that may limit their wide-scale application in the near term (''high confidence''). Some response options, for example, BECCS, have only been implemented at small-scale demonstration facilities; challenges exist with upscaling these options to the levels discussed in Chapter 6 (''medium confidenc''e). Economic and institutional barriers, including governance, financial incentives and financial resources, limit the near-term adoption of many response options, and ‘policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many options (''medium confidence''). Even some actions that initially seemed like ‘easy wins’ have been challenging to implement, with stalled policies for reducing emissions from deforestation and forest degradation and fostering conservation (REDD+) providing clear examples of how response options need sufficient funding, institutional support, local buy-in, and clear metrics for success, among other necessary enabling conditions. {6.2, 6.4}<br /> <br /> '''Some response options reduce the consequences of land challenges, but do not address underlying drivers (''high confidence'').''' For example, management of urban sprawl can help reduce the environmental impact of urban systems; however, such management does not address the socio-economic and demographic changes driving the expansion of urban areas. By failing to address the underlying drivers, there is a potential for the challenge to re-emerge in the future (''high confidence''). {6.4}<br /> <br /> '''Many response options have been practised in many regions for many years; however, there is limited knowledge of the efficacy and broader implications of other response options (''high confidence'')''.''' For the response options with a large evidence base and ample experience, further implementation and upscaling would carry little risk of adverse side effects (''high confidence''). However, for other options, the risks are larger as the knowledge gaps are greater; for example, uncertainty in the economic and social aspects of many land response options hampers the ability to predict their effects (''medium confidence''). Furthermore, Integrated Assessment Models, like those used to develop the pathways in the IPCC Special Report on Global Warming of 1.5°C (SR15), omit many of these response options and do not assess implications for all land challenges (''high confidence''). {6.4}<br /> <br /> == TS.7 Risk management and decision making in relation to sustainable development ==<br /> <br /> '''Increases in global mean surface temperature are projected to result in continued permafrost degradation and coastal degradation (''high confidence''), increased wildfire, decreased crop yields in low latitudes, decreased food stability, decreased water availability, vegetation loss (''medium confidence''), decreased access to food and increased soil erosion (''low confidence''). There is ''high agreement ''and ''high evidence ''that increases in global mean temperature will result in continued increase in global vegetation loss, coastal degradation, as well as decreased crop yields in low latitudes, decreased food stability, decreased access to food and nutrition, and ''medium confidence'' in continued permafrost degradation and water scarcity in drylands.''' Impacts are already observed across all components (''high confidence''). Some processes may experience irreversible impacts at lower levels of warming than others. There are high risks from permafrost degradation, and wildfire, coastal degradation, stability of food systems at 1.5°C while high risks from soil erosion, vegetation loss and changes in nutrition only occur at higher temperature thresholds due to increased possibility for adaptation (''medium confidence''). {7.2.2.1, 7.2.2.2, 7.2.2.3; 7.2.2.4; 7.2.2.5; 7.2.2.6; 7.2.2.7; Figure 7.1}<br /> <br /> '''These changes result in compound risks to food systems, human and ecosystem health, livelihoods, the viability of infrastructure, and the value of land (''high confidence'').''' The experience and dynamics of risk change over time as a result of both human and natural processes (''high confidence''). There is ''high confidence ''that climate and land changes pose increased risks at certain periods of life (i.e. to the very young and ageing populations) as well as sustained risk to those living in poverty. Response options may also increase risks. For example, domestic efforts to insulate populations from food price spikes associated with climatic stressors in the mid-2000s inadequately prevented food insecurity and poverty, and worsened poverty globally. (Figure TS.14) {7.2.1, 7.2.2, 7.3, Table 7.1}<br /> <br /> '''There is significant regional heterogeneity in risks: tropical regions, including Sub-Saharan Africa, Southeast Asia and Central and South America are particularly vulnerable to decreases in crop yield (''high confidence'').''' Yield of crops in higher latitudes may initially benefit from warming as well as from higher carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) concentrations. But temperate zones, including the Mediterranean, North Africa, the Gobi desert, Korea and western United States are susceptible to disruptions from increased drought frequency and intensity, dust storms and fires (''high confidence''). {7.2.2}<br /> <br /> '''Risks related to land degradation, desertification and food security increase with temperature and can reverse development gains in some socio-economic development pathways (''high confidence''). SSP1 reduces the vulnerability and exposure of human and natural systems and thus limits risks resulting from desertification, land degradation and food insecurity compared to SSP3 (''high confidence'').''' SSP1 is characterized by low population growth, reduced inequalities, land-use regulation, low meat consumption, increased trade and few barriers to adaptation or mitigation. SSP3 has the opposite characteristics. Under SSP1, only a small fraction of the dryland population (around 3% at 3°C for the year 2050) will be exposed and vulnerable to water stress. However under SSP3, around 20% of dryland populations (for the year 2050) will be exposed and vulnerable to water stress by 1.5°C and 24% by 3°C. Similarly under SSP1, at 1.5°C, 2 million people are expected to be exposed and vulnerable to crop yield change. Over 20 million are exposed and vulnerable to crop yield change in SSP3, increasing to 854 million people at 3°C (''low confidence''). Livelihoods deteriorate as a result of these impacts, livelihood migration is accelerated, and strife and conflict is worsened (''medium confidence''). {Cross-Chapter Box 9 in Chapter 6, 7.2.2, 7.3.2, Table 7.1, Figure 7.2}<br /> <br /> '''Land-based adaptation and mitigation responses pose risks associated with the effectiveness and potential adverse side-effects of measures chosen (''medium confidence'').''' Adverse side-effects on food security, ecosystem services and water security increase with the scale of BECCS deployment. In a SSP1 future, bioenergy and BECCS deployment up to 4 million km&lt;sup&gt;2 &lt;/sup&gt;is compatible with sustainability constraints, whereas risks are already high in a SSP3 future for this scale of deployment. {7.2.3}<br /> <br /> '''There is ''high confidence'' that policies addressing vicious cycles of poverty, land degradation and greenhouse gas (GHG) emissions implemented in a holistic manner can achieve climate-resilient sustainable development. Choice and implementation of policy instruments determine future climate and land pathways (''medium confidence'').''' Sustainable development pathways (described in SSP1) supported by effective regulation of land use to reduce environmental trade-offs, reduced reliance on traditional biomass, low growth in consumption and limited meat diets, moderate international trade with connected regional markets, and effective GHG mitigation instruments can result in lower food prices, fewer people affected by floods and other climatic disruptions, and increases in forested land (''high agreement, limited evidence'') (SSP1). A policy pathway with limited regulation of land use, low technology development, resource intensive consumption, constrained trade, and ineffective GHG mitigation instruments can result in food price increases, and significant loss of forest (''high agreement, limited evidence'') (SSP3). {3.7.5, 7.2.2, 7.3.4, 7.5.5, 7.5.6, Table 7.1, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Delaying deep mitigation in other sectors and shifting the burden to the land sector, increases the risk associated with adverse effects on food security and ecosystem services (''high confidence'').''' The consequences are an increased pressure on land with higher risk of mitigation failure and of temperature overshoot and a transfer of the burden of mitigation and unabated climate change to future generations. Prioritising early decarbonisation with minimal reliance on CDR decreases the risk of mitigation failure (''high confidence''). {2.5, 6.2, 6.4, 7.2.1, 7.2.2, 7.2.3, 7.5.6, 7.5.7, Cross-Chapter Box 9 in Chapter 6}<br /> <br /> '''Trade-offs can occur between using land for climate mitigation or Sustainable Development Goal (SDG) 7 (affordable clean energy) with biodiversity, food, groundwater and riverine ecosystem services (''medium confidence'').''' There is ''medium confidence ''that trade-offs currently do not figure into climate policies and decision making. Small hydro power installations (especially in clusters) can impact downstream river ecological connectivity for fish (''high agreement, medium evidence''). Large scale solar farms and wind turbine installations can impact endangered species and disrupt habitat connectivity (''medium agreement, medium evidence''). Conversion of rivers for transportation can disrupt fisheries and endangered species (through dredging and traffic) (''medium agreement, low evidence''). {7.5.6}<br /> <br /> '''The full mitigation potential assessed in this report will only be realised if agricultural emissions are included in mainstream climate policy (''high agreement, high evidence'').''' Carbon markets are theoretically more cost-effective than taxation but challenging to implement in the land-sector (''high confidence'') Carbon pricing (through carbon markets or carbon taxes) has the potential to be an effective mechanism to reduce GHG emissions, although it remains relatively untested in agriculture and food systems. Equity considerations can be balanced by a mix of both market and non-market mechanisms (''medium evidence, medium agreement''). Emissions leakage could be reduced by multi-lateral action (''high agreement, medium evidence''). {7.4.6, 7.5.5, 7.5.6, Cross Chapter Box 9 in Chapter 6}<br /> <br /> '''A suite of coherent climate and land policies advances the goal of the Paris Agreement and the land-related SDG targets on poverty, hunger, health, sustainable cities and communities, responsible consumption and production, and life on land. There is ''high confidence'' that acting early will avert or minimise risks, reduce losses and generate returns on investment.''' The economic costs of action on sustainable land management (SLM), mitigation, and adaptation are less than the consequences of inaction for humans and ecosystems (''medium confidence''). Policy portfolios that make ecological restoration more attractive, people more resilient – expanding financial inclusion, flexible carbon credits, disaster risk and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, and universal access to early warning systems – could save 100 billion USD a year, if implemented globally. {7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter Box 10 in Chapter 7}<br /> <br /> '''Coordination of policy instruments across scales, levels, and sectors advances co-benefits, manages land and climate risks, advances food security, and addresses equity concerns (''medium confidence'').''' Flood resilience policies are mutually reinforcing and include flood zone mapping, financial incentives to move, and building restrictions, and insurance. Sustainability certification, technology transfer, land-use standards and secure land tenure schemes, integrated with early action and preparedness, advance response options. SLM improves with investment in agricultural research, environmental farm practices, agri-environmental payments, financial support for sustainable agricultural water infrastructure (including dugouts), agriculture emission trading, and elimination of agricultural subsidies (''medium confidence''). Drought resilience policies (including drought preparedness planning, early warning and monitoring, improving water use efficiency), synergistically improve agricultural producer livelihoods and foster SLM. (Figure TS.15) {3.7.5, Cross-Chapter Box 5 in Chapter 3, 7.4.3, 7.4.6, 7.5.6, 7.4.8, 7.5.6, 7.6.3}<br /> <br /> '''Technology transfer in land use sectors offers new opportunities for adaptation, mitigation, international cooperation, R&amp;amp;D collaboration, and local engagement (''medium confidence'').''' International cooperation to modernise the traditional biomass sector will free up both land and labour for more productive uses. Technology transfer can assist the measurement and accounting of emission reductions by developing countries. {7.4.4, 7.4.6, Cross-Chapter Box 12 in Chapter 7}<br /> <br /> '''Measuring progress towards goals is important in decision-making and adaptive governance to create common understanding and advance policy effectiveness (''high agreement, medium evidence'').''' Measurable indicators, selected with the participation of people and supporting data collection, are useful for climate policy development and decision-making. Indicators include the SDGs, nationally determined contributions (NDCs), land degradation neutrality (LDN) core indicators, carbon stock measurement, measurement and monitoring for REDD+, metrics for measuring biodiversity and ecosystem services, and governance capacity. {7.5.5, 7.5.7, 7.6.4, 7.6.6}<br /> <br /> '''The complex spatial, cultural and temporal dynamics of risk and uncertainty in relation to land and climate interactions and food security, require a flexible, adaptive, iterative approach to assessing risks, revising decisions and policy instruments (''high confidence'').''' Adaptive, iterative decision-making moves beyond standard economic appraisal techniques to new methods such as dynamic adaptation pathways with risks identified by trigger points through indicators. Scenarios can provide valuable information at all planning stages in relation to land, climate and food; adaptive management addresses uncertainty in scenario planning with pathway choices made and reassessed to respond to new information and data as it becomes available. {3.7.5, 7.4.4, 7.5.2, 7.5.3, 7.5.4, 7.5.7, 7.6.1, 7.6.3}<br /> <br /> '''ILK can play a key role in understanding climate processes and impacts, adaptation to climate change, SLM across different ecosystems, and enhancement of food security (''high confidence'').''' ILK is context-specific, collective, informally transmitted, and multi-functional, and can encompass factual information about the environment and guidance on management of resources and related rights and social behaviour. ILK can be used in decision-making at various scales and levels, and exchange of experiences with adaptation and mitigation that include ILK is both a requirement and an entry strategy for participatory climate communication and action. Opportunities exist for integration of ILK with scientific knowledge. {7.4.1, 7.4.5, 7.4.6, 7.6.4, Cross-Chapter Box 13 in Chapter 7}<br /> <br /> '''Participation of people in land and climate decision making and policy formation allows for transparent effective solutions and the implementation of response options that advance synergies, reduce trade-offs in sustainable land management (''high confidence''), and overcomes barriers to adaptation and mitigation (''high confidence'').''' Improvements to sustainable land management are achieved by: (1) engaging people in citizen science by mediating and facilitating landscape conservation planning, policy choice, and early warning systems (''medium confidence''); (2) involving people in identifying problems (including species decline, habitat loss, land use change in agriculture, food production and forestry), selection of indicators, collection of climate data, land modelling, agricultural innovation opportunities. When social learning is combined with collective action, transformative change can occur addressing tenure issues and changing land use practices (''medium confidence''). Meaningful participation overcomes barriers by opening up policy and science surrounding climate and land decisions to inclusive discussion that promotes alternatives. {3.8.5, 7.5.1, 7.5.9; 7.6.1, 7.6.4, 7.6.5, 7.6.7, 7.7.4, 7.7.6}<br /> <br /> '''Empowering women can bolster synergies among household food security and sustainable land management (''high confidence'').''' This can be achieved with policy instruments that account for gender differences. The overwhelming presence of women in many land-based activities including agriculture provides opportunities to mainstream gender policies, overcome gender barriers, enhance gender equality, and increase sustainable land management and food security (''high confidence''). Policies that address barriers include gender qualifying criteria and gender appropriate delivery, including access to financing, information, technology, government transfers, training, and extension may be built into existing women’s programs, structures (civil society groups) including collective micro enterprise (''medium confidence''). {Cross-Chapter Box 11 in Chapter 7}<br /> <br /> '''The significant social and political changes required for sustainable land use, reductions in demand and land-based mitigation efforts associated with climate stabilisation require a wide range of governance mechanisms.''' The expansion and diversification of land use and biomass systems and markets requires hybrid governance: public-private partnerships, transnational, polycentric, and state governance to insure opportunities are maximised, trade-offs are managed equitably, and negative impacts are minimised (''medium confidence''). {7.5.6, 7.7.2, 7.7.3, Cross-Chapter Box 7 in Chapter 6}<br /> <br /> '''Land tenure systems have implications for both adaptation and mitigation, which need to be understood within specific socio-economic and legal contexts, and may themselves be impacted by climate change and climate action (''limited evidence, high agreement'').''' Land policy (in a diversity of forms beyond focus on freehold title) can provide routes to land security and facilitate or constrain climate action, across cropping, rangeland, forest, fresh-water ecosystems and other systems. Large-scale land acquisitions are an important context for the relations between tenure security and climate change, but their scale, nature and implications are imperfectly understood. There is ''medium confidence ''that land titling and recognition programs, particularly those that authorise and respect indigenous and communal tenure, can lead to improved management of forests, including for carbon storage. Strong public coordination (government and public administration) can integrate land policy with national policies on adaptation and reduce sensitivities to climate change. {7.7.2; 7.7.3; 7.7.4, 7.7.5}<br /> <br /> '''Significant gaps in knowledge exist when it comes to understanding the effectiveness of policy instruments and institutions related to land use management, forestry, agriculture and bioenergy.''' Interdisciplinary research is needed on the impacts of policies and measures in land sectors. Knowledge gaps are due in part to the highly contextual and local nature of land and climate measures and the long time periods needed to evaluate land use change in its socio-economic frame, as compared to technological investments in energy or industry that are somewhat more comparable. Significant investment is needed in monitoring, evaluation and assessment of policy impacts across different sectors and levels. {7.8}<br /> <br /> == Footnotes ==<br /> <br /> # &lt;span id=&quot;fn:1&quot;&gt;The full title of the report is the ''IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems''&lt;/span&gt;<br /> # &lt;span id=&quot;fn:2&quot;&gt;Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of GHGs and aerosols and chemically active gases, as well as land use/land cover.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:3&quot;&gt;Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages between economic, social and technological development and the evolution of the climate system.&lt;/span&gt;<br /> # &lt;span id=&quot;fn:4&quot;&gt;The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming during the 21st century by &gt;0.1°C.&lt;/span&gt;</div>

Design