Editing Test:SRCCL/Chapter-1 (section)

== 1.1.1 Objectives and scope of the assessment ==

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Land, including its water bodies, provides the basis for our livelihoods through basic processes such as net primary production that fundamentally sustain the supply of food, bioenergy and freshwater, and the delivery of multiple other ecosystem services and biodiversity (Hoekstra and Wiedmann 2014 <sup>[[#fn:r1|1]]</sup> ; Mace et al. 2012 <sup>[[#fn:r2|2]]</sup> ; Newbold et al. 2015 <sup>[[#fn:r3|3]]</sup> ; Runting et al. 2017 <sup>[[#fn:r4|4]]</sup> ; Isbell et al. 2017 <sup>[[#fn:r5|5]]</sup> ) (Cross-Chapter Box 8 in Chapter 6). The annual value of the world’s total terrestrial ecosystem services has been estimated to be about 75 trillion USD in 2011, approximately equivalent to the annual global Gross Domestic Product (based on USD2007 values) (Costanza et al. 2014 <sup>[[#fn:r6|6]]</sup> ; IMF 2018 <sup>[[#fn:r7|7]]</sup> ). Land also supports non-material ecosystem services such as cognitive and spiritual enrichment and aesthetic values (Hernández-Morcillo et al. 2013 <sup>[[#fn:r8|8]]</sup> ; Fish et al. 2016 <sup>[[#fn:r9|9]]</sup> ), intangible services that shape societies, cultures and human well-being. Exposure of people living in cities to (semi-)natural environments has been found to decrease mortality, cardiovascular disease and depression (Rook 2013 <sup>[[#fn:r10|10]]</sup> ; Terraube et al. 2017 <sup>[[#fn:r11|11]]</sup> ). Non-material and regulating ecosystem services have been found to decline globally and rapidly, often at the expense of increasing material services (Fischer et al. 2018 <sup>[[#fn:r12|12]]</sup> ; IPBES 2018a <sup>[[#fn:r13|13]]</sup> ). Climate change will exacerbate diminishing land and freshwater resources, increase biodiversity loss, and will intensify societal vulnerabilities, especially in regions where economies are highly dependent on natural resources. Enhancing food security and reducing malnutrition, whilst also halting and reversing desertification and land degradation, are fundamental societal challenges that are increasingly aggravated by the need to both adapt to and mitigate climate change impacts without compromising the non-material benefits of land (Kongsager et al. 2016 <sup>[[#fn:r14|14]]</sup> ; FAO et al. 2018 <sup>[[#fn:r15|15]]</sup> ).

Annual emissions of GHGs and other climate forcers continue to increase unabatedly. ''Confidence'' is ''very high'' that the window of opportunity, the period when significant change can be made, for limiting climate change within tolerable boundaries is rapidly narrowing (Schaeffer et al. 2015 <sup>[[#fn:r16|16]]</sup> ; Bertram et al. 2015 <sup>[[#fn:r17|17]]</sup> ; Riahi et al. 2015 <sup>[[#fn:r18|18]]</sup> ; Millar et al. 2017 <sup>[[#fn:r19|19]]</sup> ; Rogelj et al.   2018a <sup>[[#fn:r20|20]]</sup> ). The Paris Agreement formulates the goal of limiting global warming this century to well below 2°C above pre-industrial levels, for which rapid actions are required across the energy, transport, infrastructure and agricultural sectors, while factoring in the need for these sectors to accommodate a growing human population (Wynes and Nicholas 2017 <sup>[[#fn:r21|21]]</sup> ; Le Quere et al. 2018 <sup>[[#fn:r22|22]]</sup> ). Conversion of natural land, and land management, are significant net contributors to GHG emissions and climate change, but land ecosystems are also a GHG sink (Smith et al. 2014 <sup>[[#fn:r23|23]]</sup> ; Tubiello et al. 2015 <sup>[[#fn:r24|24]]</sup> ; Le Quere et al. 2018 <sup>[[#fn:r25|25]]</sup> ; Ciais et al. 2013a <sup>[[#fn:r26|26]]</sup> ). It is not surprising, therefore, that land plays a prominent role in many of the Nationally Determined Contributions (NDCs) of the parties to the Paris Agreement (Rogelj et al. 2018a <sup>[[#fn:r27|27]]</sup> ,b <sup>[[#fn:r28|28]]</sup> ; Grassi et al. 2017 <sup>[[#fn:r29|29]]</sup> ; Forsell et al. 2016 <sup>[[#fn:r30|30]]</sup> ), and land-measures will be part of the NDC review by 2023.

A range of different climate change mitigation and adaptation options on land exist, which differ in terms of their environmental and societal implications (Meyfroidt 2018 <sup>[[#fn:r31|31]]</sup> ; Bonsch et al. 2016 <sup>[[#fn:r32|32]]</sup> ; Crist et al. 2017 <sup>[[#fn:r|]]</sup> 33 ; Humpenoder et al. 2014 <sup>[[#fn:r34|34]]</sup> ; Harvey and Pilgrim 2011 <sup>[[#fn:r35|35]]</sup> ; Mouratiadou et al. 2016 <sup>[[#fn:r36|36]]</sup> ; Zhang et al. 2015 <sup>[[#fn:r37|37]]</sup> ; Sanz-Sanchez et al. 2017 <sup>[[#fn:r38|38]]</sup> ; Pereira et al. 2010 <sup>[[#fn:r39|39]]</sup> ; Griscom et al. 2017 <sup>[[#fn:r40|40]]</sup> ; Rogelj et al. 2018a <sup>[[#fn:r41|41]]</sup> ) (Chapters 4–6). The Special Report on climate change, desertification, land degradation, sustainable land management, food security, and GHG fluxes in terrestrial ecosystems (SRCCL) synthesises the current state of scientific knowledge on the issues specified in the report’s title (Figure 1.1 and Figure 1.2). This knowledge is assessed in the context of the Paris Agreement, but many of the SRCCL issues concern other international conventions such as the United Nations Convention on Biodiversity (UNCBD), the UN Convention to Combat Desertification (UNCCD), the UN Sendai Framework for Disaster Risk Reduction (UNISDR) and the UN Agenda 2030 and its Sustainable Development Goals (SDGs). The SRCCL is the first report in which land is the central focus since the IPCC Special Report on land use, land-use change and forestry (Watson et al. 2000 <sup>[[#fn:r42|42]]</sup> ) (Box 1.1). The main objectives of the SRCCL are to:

# Assess the current state of the scientific knowledge on the impacts of socio-economic drivers and their interactions with climate change on land, including degradation, desertification and food security;
# Evaluate the feasibility of different land-based response options to GHG mitigation, and assess the potential synergies and trade-offs with ecosystem services and sustainable development;
# Examine adaptation options under a changing climate to tackle land degradation and desertification and to build resilient food systems, as well as evaluating the synergies and trade-offs between mitigation and adaptation;
# Delineate the policy, governance and other enabling conditions to support climate mitigation, land ecosystem resilience and food security in the context of risks, uncertainties and remaining knowledge gaps.

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====== Figure 1.1 ======

<span id="a-representation-of-the-principal-land-challenges-and-land-climate-system-processes-covered-in-this-assessment-report.-a.-the-warming-curves-are-averages-of-four-datasets-section-2.1-figure-2.2-and-table-2.1.-b.-n2o-and-ch4-from-agriculture-are-from-faostat-net-land-use-change-emissions-of-co2-from-forestry-and-other-land-use-including-emissions"></span>
==== A representation of the principal land challenges and land-climate system processes covered in this assessment report. A. The warming curves are averages of four datasets (Section 2.1, Figure 2.2 and Table 2.1). B. N2O and CH4 from agriculture are from FAOSTAT; Net land-use change emissions of CO2 from forestry and other land use (including emissions […] ====

[[File:aeba7138efe27065c988fdc1705a6e24 SPM1-approval-v7-USletter-791x1024.png|thumb|400x300px]]

A representation of the principal land challenges and land-climate system processes covered in this assessment report.<br />
'''A''' . The warming curves are averages of four datasets (Section 2.1, Figure 2.2 and Table 2.1). '''B''' . N <sub>2</sub> O and CH <sub>4</sub> from agriculture are from FAOSTAT; Net land-use change emissions of CO <sub>2</sub> from forestry and other land use (including emissions from peatland fires since 1997) are from the annual Global Carbon Budget, using the mean of two bookkeeping models. All values expressed in units of CO <sub>2</sub> -eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N <sub>2</sub> O = 265; CH <sub>4</sub> = 28) (Table SPM.1 and Section 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 percentage 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. (Section 1.2, Table 1.1, Figure 1.3). '''D''' . Note that fertiliser use is shown on a split axis (source: International Fertiliser Industry Association, www.ifastat.org/databases). 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 <sup>–2</sup> (source: Abarca-Gómez et al. 2017 <sup>[[#fn:r43|43]]</sup> ); underweight is defined as BMI &lt;18.5 kg m <sup>–2</sup> . (Population density, source: United Nations, Department of Economic and Social Affairs 2017 <sup>[[#fn:r44|44]]</sup> ) (Sections 5.1 and 5.2). '''F''' . Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018 <sup>[[#fn:r45|45]]</sup> ) to identify areas where the Aridity Index is below 0.65. Areas experiencing human caused desertification, after accounting for precipitation variability and CO <sub>2</sub> fertilisation, are identified in Le et al. 2016. Population data for these areas were extracted from the gridded historical population database HYDE3.2 (Goldewijk et al. 2017 <sup>[[#fn:r46|46]]</sup> ). Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index (Ziese et al. 2014 <sup>[[#fn:r47|47]]</sup> ). The area in drought was calculated for each month (Drought Index below –1), and the mean over the year was used to calculate the percentage of drylands in drought that year. 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 (Dixon et al. 2016 <sup>[[#fn:r48|48]]</sup> ; Darrah et al. 2019 <sup>[[#fn:r49|49]]</sup> ) (Sections 3.1, 4.2 and 4.6).

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