Editing IPCC:AR6/SRCCL/Chapter-6 (section)

== CCB9 Climate and land pathways ==

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Katherine Calvin (The United States of America), Edouard Davin (France/Switzerland), Margot Hurlbert (Canada), Jagdish Krishnaswamy (India), Alexander Popp (Germany), Prajal Pradhan (Nepal/Germany)

Future development of socio-economic factors and policies influence the evolution of the land–climate system, among others, in terms of the land used for agriculture and forestry. Climate mitigation policies can also have a major impact on land use, especially in scenarios consistent with the climate targets of the Paris Agreement. This includes the use of bio-energy or CDR, such as bioenergy with carbon capture and storage (BECCS) and afforestation. Land-based mitigation options have implications for GHG fluxes, desertification, land degradation, food insecurity, ecosystem services and other aspects of sustainable development.

'''Shared Socio-economic Pathways'''

The five pathways are based on the Shared Socio-economic Pathways (SSPs) (O’Neill et al. 2014 <sup>[[#fn:r1174|1174]]</sup> ; Popp et al. 2017 <sup>[[#fn:r1175|1175]]</sup> ; Riahi et al. 2017 <sup>[[#fn:r1176|1176]]</sup> ; Rogelj et al. 2018b <sup>[[#fn:r1177|1177]]</sup> ) (Cross-Chapter Box 1 in Chapter 1). SSP1 is a scenario with a broad focus on sustainability, including human development, technological development, nature conservation, globalised economy, economic convergence and early international cooperation (including moderate levels of trade). The scenario includes a peak and decline in population, relatively high agricultural yields and a move towards food produced in low-GHG emission systems (Van Vuuren et al. 2017b). Dietary change and reductions in food waste reduce agricultural demands, and effective land-use regulation enables reforestation and/or afforestation. SSP2 is a scenario in which production and consumption patterns, as well as technological development, follows historical patterns (Fricko et al. 2017 <sup>[[#fn:r1178|1178]]</sup> ). Land-based CDR is achieved through bioenergy and BECCS and, to a lesser degree, by afforestation and reforestation. SSP3 is a scenario with slow rates of technological change and limited land-use regulation. Agricultural demands are high due to material-intensive consumption and production, and barriers to trade lead to reduced flows for agricultural goods. In SSP3, forest mitigation activities and abatement of agricultural GHG emissions are limited due to major implementation barriers such as low institutional capacities in developing countries and delays as a consequence of low international cooperation (Fujimori et al. 2017 <sup>[[#fn:r1179|1179]]</sup> ). Emissions reductions are achieved primarily through the energy sector, including the use of bioenergy and BECCS.

'''Policies in the Pathways'''

SSPs are complemented by a set of shared policy assumptions (Kriegler et al. 2014 <sup>[[#fn:r1180|1180]]</sup> ), indicating the types of policies that may be implemented in each future world. Integrated Assessment Models (IAMs) represent the effect of these policies on the economy, energy system, land use and climate with the caveat that they are assumed to be effective or, in some cases, the policy goals (e.g., dietary change) are imposed rather than explicitly modelled. In the real world, there are various barriers that can make policy implementation more difficult (Section 7.4.9). These barriers will be generally higher in SSP3 than SSP1.

'''SSP1:''' A number of policies could support SSP1 in future, including: effective carbon pricing, emission trading schemes (including net CO <sub>2</sub> emissions from agriculture), carbon taxes, regulations limiting GHG emissions and air pollution, forest conservation (mix of land sharing and land sparing) through participation, incentives for ecosystem services and secure tenure, and protecting the environment, microfinance, crop and livelihood insurance, agriculture extension services, agricultural production subsidies, low export tax and import tariff rates on agricultural goods, dietary awareness campaigns, taxes on and regulations to reduce food waste, improved shelf life, sugar/fat taxes, and instruments supporting sustainable land management, including payment for ecosystem services, land-use zoning, REDD+, standards and certification for sustainable biomass production practices, legal reforms on land ownership and access, legal aid, legal education, including reframing these policies as entitlements for women and small agricultural producers (rather than sustainability) (Van Vuuren et al. 2017b; O’Neill et al. 2017 <sup>[[#fn:r1181|1181]]</sup> ) (Section 7.4).

'''SSP2:''' The same policies that support SSP1 could support SSP2 but may be less effective and only moderately successful. Policies may be challenged by adaptation limits (Section 7.4.9), inconsistency in formal and informal institutions in decision-making (Section 7.5.1) or result in maladaptation (Section 7.4.7). Moderately successful sustainable land management policies result in some land competition. Land degradation neutrality is moderately successful. Successful policies include those supporting bioenergy and BECCS (Rao et al. 2017b <sup>[[#fn:r1182|1182]]</sup> ; Fricko et al. 2017 <sup>[[#fn:r1183|1183]]</sup> ; Riahi et al. 2017 <sup>[[#fn:r1184|1184]]</sup> ) (Section 7.4.6).

'''SSP3:''' Policies that exist in SSP1 may or may not exist in SSP3, and are ineffective (O’Neill et al. 2014 <sup>[[#fn:r1185|1185]]</sup> ). There are challenges to implementing these policies, as in SSP2. In addition, ineffective sustainable land management policies result in competition for land between agriculture and mitigation. Land degradation neutrality is not achieved (Riahi et al. 2017 <sup>[[#fn:r1186|1186]]</sup> ). Successful policies include those supporting bioenergy and BECCS (Kriegler et al. 2017 <sup>[[#fn:r1187|1187]]</sup> ; Fujimori et al. 2017 <sup>[[#fn:r1188|1188]]</sup> ; Rao et al. 2017b <sup>[[#fn:r1189|1189]]</sup> ) (Section 7.4.6). Demand-side food policies are absent and supply-side policies predominate. There is no success in advancing land ownership and access policies for agricultural producer livelihood (Section 7.6.5).

'''Land-use and land-cover change'''

In SSP1, sustainability in land management, agricultural intensification, production and consumption patterns result in reduced need for agricultural land, despite increases in per capita food consumption. This land can instead be used for reforestation, afforestation and bioenergy. In contrast, SSP3 has high population and strongly declining rates of crop yield growth over time, resulting in increased agricultural land area. SSP2 falls somewhere in between, with societal as well as technological development following historical patterns. Increased demand for land mitigation options such as bioenergy, reduced deforestation or afforestation decreases availability of agricultural land for food, feed and fibre. In the climate policy scenarios consistent with the Paris Agreement, bioenergy/BECCS and reforestation/afforestation play an important role in SSP1 and SSP2. The use of these options, and the impact on land, is larger in scenarios that limit radiative forcing in 2100 to 1.9 W m <sup>–2</sup> than in the 4.5 W m <sup>–2</sup> scenarios. In SSP3, the expansion of land for agricultural production implies that the use of land-related mitigation options is very limited, and the scenario is characterised by continued deforestation.

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'''Cross-Chapter Box 9 Figure 1'''

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'''Changes in agriculture land (left), bioenergy cropland (middle) and forest (right) under three different SSPs (colours) and two different warming levels (rows). Agricultural land includes both pasture and cropland. Colours indicate SSPs, with SSP1 shown in green, SSP2 in yellow, and SSP3 in red. For each pathway, the shaded areas show the range across all […]'''
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[[File:c84f26a66e05ce728644c2d4c23402b5 Cross-Chapter-Box-9-Figure-1-1024x607.jpg]]

Changes in agriculture land (left), bioenergy cropland (middle) and forest (right) under three different SSPs (colours) and two different warming levels (rows). Agricultural land includes both pasture and cropland. Colours indicate SSPs, with SSP1 shown in green, SSP2 in yellow, and SSP3 in red. For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. There is no SSP3 in the top row, as 1.9 W m <sup>–2</sup> is infeasible in this world. Data is from an update of the Integrated Assessment Modelling Consortium (IAMC) Scenario Explorer developed for the SR15 (Huppmann et al. 2018 <sup>[[#fn:r1285|1285]]</sup> ; Rogelj et al. 2018a <sup>[[#fn:r1286|1286]]</sup> ).

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'''Implications for mitigation and other land challenges'''

The combination of baseline emissions development, technology options, and policy support makes it much easier to reach the climate targets in the SSP1 scenario than in the SSP3 scenario. As a result, carbon prices are much higher in SSP3 than in SSP1. In fact, the 1.9 W m <sup>–2</sup> target was found to be infeasible in the SSP3 world (Table 1 in Cross-Chapter Box 9). Energy system CO <sub>2</sub> emissions reductions are greater in SSP3 than in SSP1 to compensate for the higher land-based CO <sub>2</sub> emissions.

Accounting for mitigation and socio-economics alone, food prices (an indicator of food insecurity) are higher in SSP3 than in SSP1 and higher in the 1.9 W m <sup>–2</sup> target than in the 4.5 W m <sup>–2</sup> target (Table 1 in Cross-Chapter Box 9). Forest cover is higher in SSP1 than SSP3 and higher in the 1.9 W m <sup>–2</sup> target than in the 4.5 W m <sup>–2</sup> target. Water withdrawals and water scarcity are, in general, higher in SSP3 than SSP1 (Hanasaki et al. 2013 <sup>[[#fn:r1192|1192]]</sup> ; Graham et al. 2018 <sup>[[#fn:r1193|1193]]</sup> ) and higher in scenarios with more bioenergy (Hejazi et al. 2014b <sup>[[#fn:r1194|1194]]</sup> ); however, these indicators have not been quantified for the specific SSP-representative concentration pathways (RCP) combinations discussed here.

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'''CCB9, Table 1'''

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'''Quantitative indicators for the pathways.'''

Each cell shows the mean, minimum, and maximum value across IAM models for each indicator and each pathway in 2050 and 2100. All IAMs that provided results for a particular pathway are included here. Note that these indicators exclude the implications of climate change. Data is from an update of the IAMC Scenario Explorer developed for the SR15 (Huppmann et al. 2018 <sup>[[#fn:r1195|1195]]</sup> ; Rogelj et al. 2018b <sup>[[#fn:r1196|1196]]</sup> ).
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Climate change results in higher impacts and risks in the 4.5 W m <sup>–2</sup> world than in the 1.9 W m <sup>–2</sup> world for a given SSP and these risks are exacerbated in SSP3 compared to SSP1 and SSP2 due to the population’s higher exposure and vulnerability. For example, the risk of fire is higher in warmer worlds; in the 4.5 W m <sup>–2</sup> world, the population living in fire prone regions is higher in SSP3 (646 million) than in SSP2 (560 million) (Knorr et al. 2016 <sup>[[#fn:r1197|1197]]</sup> ). Global exposure to multi-sector risk quadruples between 1.5°C <sup>[[#fn:|]]</sup>   and 3°C and is a factor of six higher in SSP3-3°C than in SSP1–1.5°C (Byers et al. 2018 <sup>[[#fn:r1198|1198]]</sup> ). Future risks resulting from desertification, land degradation and food insecurity are lower in SSP1 compared to SSP3 at the same level of warming. For example, the transition moderate-to-high risk of food insecurity occurs between 1.3 and 1.7°C for SSP3, but not until 2.5 to 3.5°C in SSP1 (Section 7.2).

'''Summary'''

Future pathways for climate and land use include portfolios of response and policy options. Depending on the response options included, policy portfolios implemented, and other underlying socio-economic drivers, these pathways result in different land-use consequences and their contribution to climate change mitigation. Agricultural area declines by more than 5 Mkm <sup>2</sup> in one SSP but increases by as much as 5 Mkm <sup>2</sup> in another. The amount of energy cropland ranges from nearly zero to 11 Mkm <sup>2</sup> , depending on the SSP and the warming target. Forest area declines in SSP3 but increases substantially in SSP1. Subsequently, these pathways have different implications for risks related to desertification, land degradation, food insecurity, and terrestrial GHG fluxes, as well as ecosystem services, biodiversity, and other aspects of sustainable development.

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=== 6.4.5 Potential consequences of delayed action ===

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Delayed action, in terms of overall GHG mitigation across both land and energy sectors, as well as delayed action in implementing the specific response options outlined in this chapter, will exacerbate the existing land challenges due to the continued impacts of climate change and socio-economic and other pressures. It can decrease the potential of response options and increase the costs of deployment, and will deprive communities of immediate co-benefits, among other pressures. The major consequences of delayed action are outlined below.

'''Delayed action exposes vulnerable people to continued and increasing climate impacts:''' Slower or delayed action in implementing response options exacerbates existing inequalities and impacts. This will increase the number of people vulnerable to climate change, due to population increases and increasing climate impacts (IPCC 2018 <sup>[[#fn:r1199|1199]]</sup> ; AR 5). Future climate change will lead to exacerbation of the existing land challenges, increased pressure on agricultural livelihoods, potential for rapid land degradation, and millions more people exposed to food insecurity (Schmidhuber and Tubiello 2007 <sup>[[#fn:r1200|1200]]</sup> ) (Chapters 3, 4 and 5). Delay can also bring political risks and significant social impacts, including risks to human settlements (particularly in coastal areas), large-scale migration, and conflict (Barnett and Adger 2007 <sup>[[#fn:r1201|1201]]</sup> ; Hsiang et al. 2013 <sup>[[#fn:r1202|1202]]</sup> ). Early action reducing vulnerability and exposure can create an opportunity for a virtual circle of benefits: increased resilient livelihoods, reduced degradation of land, and improved food security (Bohle et al. 1994 <sup>[[#fn:r1203|1203]]</sup> ).

'''Delayed action increases requirements for adaptation:''' Failure to mitigate climate change will increase requirements for adaptation. For example, it is likely that by 2100 with no mitigation or adaptation, 31 '''–''' 69 million people world-wide could be exposed to flooding (Rasmussen et al. 2017 <sup>[[#fn:r1204|1204]]</sup> ; IPCC SR15) (Chapter 3); such outcomes could be prevented with investments in both mitigation and adaptation now. Some specific response options (e.g., reduced deforestation and forest degradation, reduced peatland and wetland conversion) 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 biodiversity and ecosystem services (Section 6.2). Response options aimed at land restoration and rehabilitation can serve as adaptation mechanisms for communities facing climatic stresses like precipitation variability and changes in land quality, as well as provide benefits in terms of mitigation.

'''Delayed action increases response costs and reduces economic growth:''' Early action on reducing emissions through mitigation is estimated to result in smaller temperature increases as well as lower mitigation costs than delayed action (Sanderson et al. 2016 <sup>[[#fn:r1205|1205]]</sup> ; Luderer et al. 2013, 2018; Rose et al. 2017 <sup>[[#fn:r1206|1206]]</sup> ; Van Soest et al. 2017; Fujimori et al. 2017 <sup>[[#fn:r1207|1207]]</sup> ). The cost of inaction to address mitigation, adaptation, and sustainable land use exceeds the cost of immediate action in most countries, depending on how damage functions and the social cost of carbon are calculated (Dell et al. 2012 <sup>[[#fn:r1208|1208]]</sup> ; Moore and Diaz 2015 <sup>[[#fn:r1209|1209]]</sup> ). Costs of acting now would be one to two orders of magnitude lower than economic damages from delayed action, including damage to assets from climate impacts, as well as potentially reduced economic growth, particularly in developing countries (Luderer et al. 2016 <sup>[[#fn:r1210|1210]]</sup> ; Moore and Diaz 2015 <sup>[[#fn:r1211|1211]]</sup> ; Luderer et al. 2013 <sup>[[#fn:r1212|1212]]</sup> ). Increased health costs and costs of energy (e.g., to run air-conditioners to combat increased heat waves) in the US by the end of the century alone are estimated to range from 10–58% of US GDP in 2010 (Deschênes and Greenstone 2011).

Delay also increases the costs of both mitigation and adaptation actions at later dates. In models of climate-economic interactions, deferral of emissions reduction now requires trade-offs leading to higher costs of several orders of magnitude and risks of higher temperatures in the longer term (Luderer et al. 2013 <sup>[[#fn:r1213|1213]]</sup> ). Further, the cost of action is likely to increase over time due to the increased severity of challenges in future scenarios.

Conversely, timely implementation of response options brings economic benefits. Carbon pricing is one economic component to encourage adoption of response options (Jakob et al. 2016 <sup>[[#fn:r1214|1214]]</sup> ), but carbon pricing alone can induce higher risk in comparison to other scenarios and pathways that include additional targeted sustainability measures, such as promotion of less material- and energy-intensive lifestyles and healthier diets, as noted in our response options (Bertram et al. 2018 <sup>[[#fn:r1215|1215]]</sup> ). While the short-term costs of deployment of actions may increase, better attainment of a broad set of sustainability targets can be achieved through these combined measures (Bertram et al. 2018 <sup>[[#fn:r1216|1216]]</sup> ).

There are also investments now that can lead to immediate savings in terms of avoided damages; for example, for each dollar spent on disaster risk management, countries accrue avoided disaster-related economic losses of 4 USD or more (Mechler 2016 <sup>[[#fn:r1217|1217]]</sup> ). While they can require upfront investment, the economic benefits of actions to ensure sustainable land management, such as increased soil organic carbon, can more than double the economic value of rangelands and improve crop yields (Chapter 4 and Section 6.2).

'''Delayed action reduces future policy space and decreases efficacy of some response options:''' The potential for some response 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, afforestation and reforestation (Section 6.4.2). Additionally, climate change affects the productivity of bioenergy crops, influencing the potential mitigation of bioenergy and BECCS (Section 6.4.4).

For response options in the supply chain, demand-side management, and risk management, while the consequences of delayed action are apparent in terms of continued GHG emissions from drivers, the tools for response options are not made more difficult by delay and could be deployed at any time. Additionally, given increasing pressures on land as a consequence of delay, some policy response options may become more cost-effective while others become costlier. For example, over time, land-based mitigation measures like forest and ecosystem protection are likely to increase land scarcity, leading to higher food prices; while demand-side measures, like reduced-impact diets and reducing waste, are less likely to raise food prices in economic models (Stevanović et al. 2017 <sup>[[#fn:r1218|1218]]</sup> ).

For risk management, some response options provide timely and rapidly deployable solutions for preventing further problems, such as disaster risk management and risk-sharing instruments. For example, early warning systems serve multiple roles in protecting lives and property and helping people adapt to longer-term climate changes, and can be used immediately.

'''Delaying action can also result in problems of irreversibility of biophysical impacts and tipping points:''' Early action provides a potential way to avoid irreversibility – such as degradation of ecosystems that cannot be restored to their original baseline – and tipping points, whereby ecological or climate systems abruptly shift to a new state. Ecosystems, such as peatlands, are particularly vulnerable to irreversibility because of the difficulties of rewetting to original states (Section 6.2), and dryland grazing systems are vulnerable to tipping points when ground cover falls below 50%, after which productivity falls, infiltration declines, and erosion increases (Chapters 3 and 4). Further, tipping points can be especially challenging for human populations to adapt to, given the lack of prior experience with such system shifts (Kates et al. 2012 <sup>[[#fn:r1219|1219]]</sup> ; Nuttall 2012 <sup>[[#fn:r1220|1220]]</sup> ).

'''Policy responses require lead time for implementation; delay makes this worse:''' For all the response options, particularly those that need to be deployed through policy implementation, there are unavoidable lags in this cycle. ‘Policy lags’, by which implementation is delayed by the slowness of the policy implementation cycle, are significant across many land-based, response options (Brown et al. 2019 <sup>[[#fn:r1221|1221]]</sup> ). Further, the behavioural change necessary to achieve some demand-side and risk management response options often takes a long time, and delay only lengthens this process (Stern 1992 <sup>[[#fn:r1222|1222]]</sup> ; Steg and Vlek 2009 <sup>[[#fn:r1223|1223]]</sup> ). For example, actively promoting the need for healthier and more sustainable diets through individual dietary decisions is an important underpinning and enabling step for future changes, but is likely to be a slow-moving process, and delay in beginning will only exacerbate this.

'''Delay can lead to lock-in:''' Delay in implementation can cause ‘lock-in’ as decisions made today can constrain future development and pathways. For example, decisions made now on where to build infrastructure, make investments and deploy technologies, will have longer-term (decades-long) ramifications due to the inertia of capital stocks (Van Soest et al. 2017). In tandem, the vulnerability of the poor is likely to be exacerbated by climate change, creating a vicious circle of lock in whereby an increasing share of the dwindling carbon budget may be needed to assist with improved energy use for the poorest (Lamb and Rao 2015 <sup>[[#fn:r1224|1224]]</sup> ).

'''Delay can increase the need for widespread deployment of land-based mitigation (afforestation, BECCS)''' (IPCC 2018 <sup>[[#fn:r1225|1225]]</sup> ; Strefler et al. 2018 <sup>[[#fn:r1226|1226]]</sup> ): Further delays in mitigation could result in an increased need for carbon dioxide removal (CDR) options later; for example, delayed mitigation requires a 10% increase in cumulative CDR over the century (IPCC 2018 <sup>[[#fn:r1227|1227]]</sup> ). Similarly, strengthening near-term mitigation effort can reduce the CDR requirements in 2100 by a factor of 2 to 8 (Strefler et al. 2018 <sup>[[#fn:r1228|1228]]</sup> ). Conversely, scenarios with limited CDR require earlier emissions reductions (Van Vuuren et al. 2017b) and may make more stringent mitigation scenarios, like the 1.5°C, infeasible (Kriegler et al. 2018a,b).

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