IPCC:AR6/SRCCL/TS

Technical Summary

TS.0 Introduction

This Technical Summary to the IPCC Special Report on Climate Change and Land (SRCCL)1 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.

TS.1 Framing and context

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}

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}

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 CO2, 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}

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– 1.3.6, Cross-Chapter Box 1 in Chapter 1}

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}

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 CO2 emissions from deforestation, CH4 emissions from rice and ruminant livestock and N2O 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}

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}

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}

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} 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}

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}

TS.2 Land–climate interactions

Implications of climate change, variability and extremes for land systems

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}

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}

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., CO2 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}

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}

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}

Terrestrial greenhouse gas fluxes on unmanaged and managed lands

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 (CO2), methane (CH4) and nitrous oxide (N2O) combined as CO2 equivalents in 2007–2016 (medium confidence). AFOLU results in both emissions and removals of CO2, CH4 and N2O 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}

The total net land-atmosphere flux of CO2 on both managed and unmanaged lands very likely provided a global net removal from 2007 to 2016 according to models (-6.0 ± 3.7 GtCO2 yr–1, likely range). This net removal is comprised of two major components: (i) modelled net anthropogenic emissions from AFOLU are 5.2 ± 2.6 GtCO2 yr–1 (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 CO2) (medium confidence), and (ii) modelled net removals due to non-anthropogenic processes are 11.2 ± 2.6 GtCO2 yr–1 (likely range) on managed and unmanaged lands, driven by environmental changes such as increasing CO2, nitrogen deposition and changes in climate (accounting for a removal of 29% of the CO2 emitted from all anthropogenic activities (fossil fuel, industry and AFOLU) (medium confidence). {2.3.1}

Global models and national GHG inventories use different methods to estimate anthropogenic CO2 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 GtCO2 yr–1, while the mean of two global bookkeeping models is 5.1 ± 2.6 GtCO2yr–1 (likely range). {Table SPM.1}

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 CO2 from AFOLU is composed of two opposing gross fluxes: (i) gross emissions (20 GtCO2 yr–1) from deforestation, cultivation of soils and oxidation of wood products, and (ii) gross removals (–14 GtCO2 yr–1), largely from forest growth following wood harvest and agricultural abandonment (medium confidence). (Figure TS.4) {2.3.1}

Land is a net source of CH4, accounting for 44% of anthropogenic CH4 emissions for the 2006–2017 period (medium confidence). The pause in the rise of atmospheric CH4 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 CH4 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 CH4 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 CH4 in the atmosphere (very high confidence). {2.3.2}

AFOLU is the main anthropogenic source of N2O primarily due to nitrogen application to soils (high confidence). In croplands, the main driver of N2O 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 MtN2O-N yr–1 (medium confidence). Because the response of N2O 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 N2O 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}

While managed pastures make up only one-quarter of grazing lands, they contributed more than three-quarters of N2O 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 N2O 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} Increased emissions from vegetation and soils due to climate change in the future are expected to counteract potential sinks due to CO2 fertilisation (low confidence). Responses of vegetation and soil organic carbon (SOC) to rising atmospheric CO2 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 CO2 (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 CO2 and CH4 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}

Biophysical and biogeochemical land forcing and feedbacks to the climate system

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 CO2, CH4 and N2O 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}

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}

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}

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}

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}

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}

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}

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}

Consequences for the climate system of land-based adaptation and mitigation options, including carbon dioxide removal (negative emissions)

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 GtCO2 y–1 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}

Several mitigation response options have technical potential for >3 GtCO2-eq yr–1 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 GtCO2-eq yr–1) (high confidence), a shift towards plant-based diets (0.7–8.0 GtCO2-eq yr–1) (high confidence) and reduced food and agricultural waste (0.8–4.5 CO2-eq yr–1) (high confidence). Agriculture measures combined could mitigate 0.3–3.4 GtCO2-eq yr–1 (medium confidence). The options with largest potential for CDR are afforestation/reforestation (0.5–10.1 CO2-eq yr–1) (medium confidence), soil carbon sequestration in croplands and grasslands (0.4–8.6 CO2-eq yr–1) (high confidence) and Bioenergy with Carbon Capture and Storage (BECCS) (0.4–11.3 CO2-eq yr–1) (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}

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 CO2 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}

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 GtCO2yr–1 for scenarios RCP4.5, RCP2.6 and RCP1.9 respectively) and BECCS (–6.5, –11 and –14.9 GtCO2 yr–1 respectively). Emissions of CH4 and N2O 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 MtCH4 yr–1; and 7.4, 6.1 and 4.5 MtN2O yr–1 for the same set of scenarios in 2100 (high confidence). High levels of bioenergy crop production can result in increased N2O 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}

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 Mkm2 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 Mkm2 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}

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}