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

== CCB8 Ecosystem services and Nature’s Contributions to People, and their relation to the land–climate system ==

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Pamela McElwee (The United States of America), Jagdish Krishnaswamy (India), Lindsay Stringer (United Kingdom)

This Cross-Chapter Box describes the concepts of ''ecosystem services'' (ES) and ''Nature’s Contributions to People'' (NCP), and their importance to land–climate interactions. ES have become a useful concept to describe the benefits that humans obtain from ecosystems and have strong relevance to sustainable land management (SLM) decisions and their outcomes, while NCP is a new approach championed by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) (explained below). It is timely that this SRCCL report includes attention to ES/NCP, as the previous Special Report on land-use, land-use change and forestry (LULUCF) did not make use of these concepts and focused mostly on carbon fluxes in land–climate interactions (IPCC 2000 <sup>[[#fn:r1014|1014]]</sup> ). The broader mandate of SRCCL is to address climate, but also land degradation, desertification and food security issues, all of which are closely linked to the provisioning of various ES/NCP, and the decision and outline for SRCCL explicitly request an examination of how desertification and degradation ‘impacts on ecosystem services (e.g., water, soil and soil carbon and biodiversity that underpins them)’. Attention to ES/NCP is particularly important in discussing co-benefits, trade-offs and adverse side effects of potential climate change mitigation, land management, or food security response options, as many actions may have positive impacts on climate mitigation or food production, but may also come with a decline in ES provisioning, or adversely impact on biodiversity (Section 6.4.3). This box considers the importance of the ES/NCP concepts, how definitions have changed over time, continuing debates over operationalisation and use of these ideas. It concludes by looking at how ES/NCP are treated in various chapters in this report.

While the first uses of the term ‘ecosystem services’ appeared in the 1980s (Lele et al. 2013 <sup>[[#fn:r1015|1015]]</sup> ; Mooney and Ehrlich 1997 <sup>[[#fn:r1016|1016]]</sup> ), the roots of interest in ES extend back to the late 1960s and the extinction crisis, with concern that species decline might cause loss of valuable benefits to humankind (King 1966 <sup>[[#fn:r1017|1017]]</sup> ; Helliwell 1969 <sup>[[#fn:r1018|1018]]</sup> ; Westman 1977 <sup>[[#fn:r1019|1019]]</sup> ). While concern over extinction was explicitly linked to biodiversity loss, later ideas beyond biodiversity have animated interest in ES, including the multi-functional nature of ecosystems. A seminal paper by Costanza et al. (1997) <sup>[[#fn:r1020|1020]]</sup> attempted to put an economic value on the stocks of global ES and natural capital on which humanity relied. Attention to ES expanded rapidly after the Millennium Ecosystem Assessment (MA, 2005), and the linkages between ES and economic valuation of these functions were addressed by the Economics of Ecosystems and Biodiversity study (TEEB 2009 <sup>[[#fn:r1021|1021]]</sup> ). The ES approach has increasingly been used in global and national environmental assessments, including the UK National Ecosystem Assessment (Watson et al. 2011 <sup>[[#fn:r1022|1022]]</sup> ), and recent and ongoing regional and global assessments organised by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) (Díaz et al. 2015 <sup>[[#fn:r1023|1023]]</sup> ). IPBES has recently completed an assessment on land degradation and restoration that addresses a range of ES issues of relevance to the SRCCL report (IPBES 2018 <sup>[[#fn:r1024|1024]]</sup> ).

The MA defined ES as ‘the benefits that ecosystems provide to people,’ and identified four broad groupings of ES: ''provisioning services'' such as food, water, or timber; ''regulating services'' that have impacts on climate, diseases or water quality, among others; ''cultural services'' that provide recreational, aesthetic, and spiritual benefits; and ''supporting services'' such as soil formation, photosynthesis, and nutrient cycling (MA 2005). The MA emphasised that people are components of ecosystems engaged in dynamic interactions, and particularly assessed how changes in ES might impact human well-being, such as access to basic materials for living (shelter, clothing, energy); health (clean air and water); social relations (including community cohesion); security (freedom from natural disasters); and freedom of choice (the opportunity to achieve) (MA 2005). Upon publication of the MA, incorporation of ES into land-use change assessments increased dramatically, including studies on how to maximise provisioning of ES alongside human well-being (Carpenter et al. 2009 <sup>[[#fn:r1025|1025]]</sup> ); how intensive food production to feed growing populations required trading off a number of important ES (Foley et al. 2005 <sup>[[#fn:r1026|1026]]</sup> ); and how including ES in general circulation models indicated increasing vulnerability to ES change or loss in future climate scenarios (Schröter et al. 2005 <sup>[[#fn:r1027|1027]]</sup> ).

Starting in 2015, IPBES introduced a new related concept to ES, that of ''Nature’s Contributions to People'' (NCP), which are defined as ‘all the contributions, both positive and negative, of living nature (i.e., diversity of organisms, ecosystems and their associated ecological and evolutionary processes) to the quality of life of people’ (Díaz et al. 2018 <sup>[[#fn:r1028|1028]]</sup> ). NCP are divided into regulating NCP, non-material NCP, and material NCP, a different approach than used by the MA (see Figure 1). However, IPBES has stressed that NCP are a particular ''way to think'' of ES, rather than a replacement for ES. The concept of NCP is proposed to be a broader umbrella to engage a wider range of scholarship – particularly from the social sciences and humanities – and a wider range of values, from intrinsic to instrumental to relational – particularly those held by indigenous peoples and local communities (Redford and Adams 2009 <sup>[[#fn:r1029|1029]]</sup> ; Schröter et al. 2014 <sup>[[#fn:r1030|1030]]</sup> ; Pascual et al. 2017 <sup>[[#fn:r1031|1031]]</sup> ; Díaz et al. 2018 <sup>[[#fn:r1032|1032]]</sup> ). The differences between the MA and IPBES approaches can be seen in Table 1.

While there are many similarities between ES and NCP, as seen above, the IPBES’s decision to use the NCP concept has been controversial, with some people arguing that an additional term is superfluous; that it incorrectly associates ES with economic

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valuation; and that the NCP concept is not useful for policy uptake (Braat 2018 <sup>[[#fn:r1033|1033]]</sup> ; Peterson et al. 2018 <sup>[[#fn:r1034|1034]]</sup> ). Others have argued that the MA’s approach is outdated, does not explicitly address biodiversity, and confuses different concepts, like economic goods, ecosystem functions, and general benefits (Boyd and Banzhaf 2007 <sup>[[#fn:r1035|1035]]</sup> ). Moreover, for both ES and NCP approaches, it has been difficult to make complex ecological processes and functions amenable to assessments that can be used and compared across wider landscapes, different policy actors, and multiple stakeholders (de Groot et al. 2002; Naeem et al. 2015 <sup>[[#fn:r1036|1036]]</sup> ; Seppelt et al. 2011 <sup>[[#fn:r1037|1037]]</sup> ). There remain competing categorisation schemes for ES, as well as competing metrics on how most ES might be measured (Wallace 2007; Potschin and Haines-Young 2011 <sup>[[#fn:r1038|1038]]</sup> ; Danley and Widmark 2016 <sup>[[#fn:r1039|1039]]</sup> ; Nahlik et al. 2012 <sup>[[#fn:r1040|1040]]</sup> ). The implications of these discussions for this SRCCL report is that many areas of uncertainty remain with regard to much ES/NCP measurement and valuation, which will have ramifications for choosing response options and policies.

This report addresses ES/NCP in multiple ways. Individual chapters have used the term ‘ES’ in most cases, especially since the preponderance of existing literature uses the ES terminology. For example, Chapter 2 discusses CO2 fluxes, nutrients and water budgets as important ES deriving from land–climate interactions. Chapters 3 and 4 discuss issues such as biomass production, soil erosion, biodiversity loss, and other ES affected by land-use change. Chapter 5 discusses both ES and NCP issues surrounding food system provisioning and trade-offs.

In Chapter 6, the concept of NCP is used. For example, Tables 6.70 to 6.72, possible response options to respond to climate change, to address land degradation or desertification, and to ensure food security, are cross-referenced against the 18 NCPs identified by Díaz et al. (2018) <sup>[[#fn:r1041|1041]]</sup> to see where there are co-benefits and adverse side effects. For instance, while BECCS may deliver on climate mitigation, it results in a number of adverse side effects that are significant with regard to water provisioning, food and feed availability, and loss of supporting identities if BECCS competes against local land uses of cultural importance. Chapter 7 has Section 7.2.2.2, explicitly covering risks due to loss of biodiversity and ES, and Table 7.1 which includes policy responses to various land–climate–society hazards, some of which are likely to enhance risk of loss of biodiversity and ES. A case study on the impact of renewable energy on biodiversity and ES is also included. Chapter 7 also notes that, because there is no Sustainable Development Goal covering freshwater biodiversity and aquatic ecosystems, this policy gap may have adverse consequences for the future of rivers and associated ES.

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=== 6.4.3 Impacts of integrated response options on Nature’s Contributions to People (NCP) and the UN Sustainable Development Goals (SDGs) ===

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In addition to evaluating the importance of our response options for climate mitigation, adaptation, land degradation, desertification and food security, it is also necessary to pay attention to other co-benefits and trade-offs that may be associated with these responses. How the different options impact progress toward the Sustainable Development Goals (SDGs) can be a useful shorthand for looking at the social impacts of these response options. Similarly, looking at how these response options increase or decrease the supply of ecosystem services/Nature’s Contributions to People (NCP) (see Cross-Chapter Box 8 in Chapter 6) can be a useful shorthand for a more comprehensive environmental impact beyond climate and land. Such evaluations are important as response options may lead to unexpected trade-offs with social goals (or potential co-benefits) and impacts on important environmental indicators such as water or biodiversity. Similarly, there may be important synergies and co-benefits associated with some response options that may increase their cost-effectiveness or attractiveness. As we note in Section 6.4.4, many of these synergies are not automatic, and are dependent on well-implemented and coordinated activities in appropriate environmental contexts (Section 6.4.4.1), often requiring institutional and enabling conditions for success and participation of multiple stakeholders (Section 6.4.4.3).

In the following sections and tables, we evaluate each response option against 17 SDGs and 18 NCPs. Some of the SDG categories appear similar to each other, such as SDG 13 on ‘climate action’ and an NCP titled ‘climate regulation’. However, SDG 13 includes targets for both mitigation and adaptation, so options were weighed by whether they were useful for one or both. On the other hand, the NCP ‘regulation of climate’ does not include an adaptation component, and refers specifically to ‘positive or negative effects on emissions of GHGs and positive or negative effects on biophysical feedbacks from vegetation cover to atmosphere, such as those involving albedo, surface roughness, long-wave radiation, evapotranspiration (including moisture-recycling) and cloud formation or direct and indirect processes involving biogenic volatile organic compounds (BVOC), and regulation of aerosols and aerosol precursors by terrestrial plants and phytoplankton’ (Díaz et al. 2018 <sup>[[#fn:r1266|1266]]</sup> ).

In all tables, colours represent the direction of impact: positive (blue) or negative (brown), and the scale of the impact (dark colours for large impact and/or strong evidence to light colours for small impact and/ or less certain evidence). Supplementary tables show the values and references used to define the colour coding used in all tables. In cases where there is no evidence of an interaction, or at least no literature on such interactions, the cell is left blank. In cases where there are both positive and negative interactions and the literature is uncertain about the overall impact, a note appears in the box. In all cases, many of these interactions are contextual, or the literature only refers to certain co-benefits in specific regions or ecosystems, so readers are urged to consult the supplementary tables for the specific caveats that may apply.

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==== 6.4.3.2 Impacts of integrated response options on the UNSDGs ====

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Tables 6.73–6.75 summarise the impact of the integrated response options on the UN SDGs. Some of the synergies between response options and SDGs in the literature include positive poverty eradication impacts (SDG 1) from activities like improved water management or improved management of supply chains, or positive gender impacts (SDG 5) from livelihood diversification or use of local seeds. Because many land management options only produce indirect or unclear effects on SDGs, we did not include these where there was no literature. Therefore, the value chain and governance options appear to offer more direct benefits for SDG.

However, it is noted that some SDG are internally difficult to assess because they contain many targets, not all of which could be evaluated (e.g., SDG 17 is about partnerships, but has targets ranging from foreign aid to debt restructuring, technology transfer to trade openness). Additionally, it is noted that some SDG contradict one another – for example, SDG 9 to increase industrialisation and infrastructure and SDG 15 to improve life on land. More industrialisation is likely to lead to increased resource demands with negative effects on habitats. Therefore, a positive association on one SDG measure might be directly correlated with a negative measure on another, and the table needs to be read with caution for that reason. The specific caveats on each of these interactions can be found in the supplementary material tables in the Chapter 6 Appendix.

Overall, several response options have co-benefits across 10 or more SDGs with no adverse side effects on any SDG: increased food production, improved grazing land management, agroforestry, integrated water management, reduced post-harvest losses, sustainable sourcing, livelihood diversification and disaster risk management. Other response options may have strengths in some SDGs but require trade-offs with others. For example, use of local seeds brings many positive benefits for poverty and hunger reduction, but may reduce international trade (SDG 17). Other response options like enhanced urban food systems, management of urban sprawl, or management of supply chains are generally positive for many SDGs but may trade-off with one, like clean water (SDG 6) or decent work (SDG 8), as they may increase water use or slow economic growth. Several response options, including avoidance of grassland conversion, reduced deforestation and forest degradation, reforestation and afforestation, biochar, restoration and avoided conversion of peatlands and coastlands, have trade-offs across multiple SDGs, primarily as they prioritise land health over food production and poverty eradication. Several response options such as bioenergy and BECCS and some risk-sharing instruments, such as crop insurance, trade-off over multiple SDG with potentially significant adverse consequences.

Overall, across categories of SDG and NCPs; 17 of 40 options deliver co-benefits or no adverse side effects for the full range of NCPs and SDGs.This includes 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. Only three options (afforestation, bioenergy and BECCS and some types of risk-sharing instruments, such as crop insurance) have potentially adverse side effects for five or more NCPs or SDGs.

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'''Table 6.75'''

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'''Impacts of integrated response options based on risk management on the UN SDGs.'''
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==== 6.4.3.1 Impacts of integrated response options on NCP ====

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Tables 6.70–6.72 summarise the impacts of the response options on NCP supply. Examples of synergies between response options and NCP include positive impacts on habitat maintenance (NCP 1) from activities like invasive species management and agricultural diversification. For the evaluation process, we considered that NCP are about ecosystems, therefore options which may have overall positive effects, but which are ''not'' ecosystem-based are not included; for example, improved food transport and distribution could reduce ground-level ozone and thus improve air quality, but this is not an ecosystem-based NCP. Similarly, energy-efficiency measures would increase energy availability, but the ‘energy’ NCP refers specifically to biomass-based fuel provisioning. This necessarily means that the land management options have more direct NCP effects than the value chain or governance options, which are less ecosystem focused.

In evaluating NCP, we have also tried to avoid ‘indirect’ effects – that is, a response option might increase household income which could then be invested in habitat-saving actions, or dietary change would lead to conservation of natural areas, which would then lead to increased water quality. Similarly, material substitution would increase wood demand, which in turn might lead to deforestation, which might have water regulation effects. These can all be considered ''indirect'' impacts on NCP, which were not evaluated. <sup>[[#fn:8|8]]</sup>   Instead, the assessment focuses as much as possible on ''direct'' effects only: for example, local seeds policies preserve local landraces, which ''directly'' contribute to ‘maintenance of genetic options’ for the future. Therefore, this NCP table is a conservative estimation of NCP effects; there are likely many more secondary effects, but they are too difficult to assess, or the literature is not yet complete or conclusive.

Further, many NCPs trade-off with one another (Rodríguez et al. 2006 <sup>[[#fn:r1043|1043]]</sup> ), so supply of one might lead to less availability of another – for example, use of ecosystems to produce bioenergy will likely lead to decreases in water availability if mono-cropped high-intensity plantations are used (Gasparatos et al. 2011 <sup>[[#fn:r1044|1044]]</sup> ).

Overall, several response options stand out as having co-benefits across 10 or more NCP with no adverse impacts, including: improved cropland management, agroforestry, forest management and forest restoration, increased soil organic content, fire management, restoration and avoided conversion of coastal wetlands, and use of local seeds. Other response options may have strengths in some NCP but require trade-offs with others. For example, reforestation and afforestation bring many positive benefits for climate and water quality but may trade-off with food production (Table 6.70). Several response options, including increased food productivity, bioenergy and BECCS, and some risk-sharing instruments, like crop insurance, have significant negative consequences across multiple NCPs.

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'''Impacts on Nature’s Contributions to People (NCP) of integrated response options based on land management.'''
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'''Impacts on NCP of integrated response options based on value chain management.'''
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'''Table 6.72'''

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'''Impacts on NCP of integrated response options based on risk management.'''
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=== 6.4.4 Opportunities for implementing integrated response options ===

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==== 6.4.4.1 Where can the response options be applied? ====

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As shown in Section 6.1.3, a large part of the land area is exposed to overlapping land challenges, especially in villages, croplands and rangelands. The deployment of land management responses may vary with local exposure to land challenges. For instance, with croplands exposed to a combination of land degradation, food insecurity and climate change adaptation challenges, maximising the co-benefits of land management responses would require selecting responses having only co-benefits for these three overlapping challenges, as well as for climate change mitigation, which is a global challenge. Based on these criteria, Figure 6.6 shows the potential deployment area of land management responses across land-use types (or anthromes).

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'''Figure 6.6'''

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'''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 […]'''
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[[File:4fd4631001809290324c74e55f09660a Figure-6.6-1024x599.jpg]]

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.

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Land management responses having co-benefits across the range of challenges, including climate change mitigation, could be deployed between one land-use type (coastal wetlands, peatlands, forest management and restoration, reforestation) and five (increased soil organic carbon) or six (fire management) land-use types (Figure 6.6). Fire management and increased soil organic carbon have a large potential since they could be deployed with mostly co-benefits and few adverse effects over 76% and 58% of the ice-free land area. In contrast, other responses have a limited area-based potential due to biophysical constraints (e.g., limited extent of organic soils and of coastal wetlands for conservation and restoration responses), or due to the occurrence of adverse effects. Despite strong co-benefits for climate change mitigation, the deployment of bioenergy and BECCS would have co-benefits on only 9% of the ice-free land area (Figure 6.6), given adverse effects of this response option for food security, land degradation, climate change adaptation and desertification (Tables 6.62–6.69).

Without including the global climate change mitigation challenge, there are up to five overlapping challenges on lands that are not barren (Figure 6.7A, calculated from the overlay of individual challenges shown in Figure 6.2) and up to nine land management response options having only co-benefits for these challenges and for climate change mitigation (Figure 6.7B). Across countries, the mean number of land management response options with mostly co-benefits declines ( ''p'' &lt;0.001, Spearman rank order correlation) with the mean number of land challenges. Hence, the higher the number of land challenges per country, the fewer the land management response options having only co-benefits for the challenges encountered.

Enabling conditions (see Section 6.1.2.2) for the implementation of land management responses partly depend on human development (economics, health and education) as estimated by a country scale composite index, the Human Development Index (HDI) (UNDP 2018 <sup>[[#fn:r1045|1045]]</sup> ) (Figure 6.7C). Across countries, HDI is negatively correlated ( ''p'' &lt;0.001, Spearman rank order correlation) with the mean number of land challenges. Therefore, on a global average, the higher the number of local challenges faced, the fewer the land management responses having only co-benefits, and the lower the human development (Figure 6.7) that could favour the implementation of these responses.

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'''Figure 6.7'''

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'''Global distributions of: (a) number of overlapping land challenges (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality (Figure 6.2); (b) number of land management responses providing medium-to-large co-benefits and no adverse side effects (see Figure 6.6) across challenges; (c) Human Development Index (HDI) by country. The HDI (UNDP 2018) […]'''
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[[File:6a2f22452096530aa3c0d13de8dbfd63 Figure-6.7-512x1024.jpg]]

Global distributions of: (a) number of overlapping land challenges (desertification, land degradation, climate change adaptation, chronic undernourishment, biodiversity, groundwater stress and water quality (Figure 6.2); (b) number of land management responses providing medium-to-large co-benefits and no adverse side effects (see Figure 6.6) across challenges; (c) Human Development Index (HDI) by country. The HDI (UNDP 2018 <sup>[[#fn:r1267|1267]]</sup> ) is a country-based composite statistical index measuring average achievement in three basic dimensions of human development: a long and healthy life (estimated from life expectancy at birth), knowledge (estimated from years of schooling), and a decent standard of living (estimated from gross national income per capita).

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<div id="section-6-4-4-2-interlinkages-and-response-options-in-future-scenarios"></div>

<span id="interlinkages-and-response-options-in-future-scenarios"></span>
==== 6.4.4.2 Interlinkages and response options in future scenarios ====

<div id="section-6-4-4-2-interlinkages-and-response-options-in-future-scenarios-block-1"></div>

This section assesses more than 80 articles quantifying the effect of various response options in the future, covering a variety of response options and land-based challenges. These studies cover spatial scales ranging from global (Popp et al. 2017 <sup>[[#fn:r1046|1046]]</sup> ; Fujimori et al. 2019 <sup>[[#fn:r1047|1047]]</sup> ) to regional (Calvin et al. 2016a <sup>[[#fn:r1048|1048]]</sup> ; Frank et al. 2015 <sup>[[#fn:r1049|1049]]</sup> ) to country level (Gao and Bryan 2017; Pedercini et al. 2018 <sup>[[#fn:r1050|1050]]</sup> ). This section focuses on models that can quantify interlinkages between response options, including agricultural economic models, land system models, and Integrated Assessment Models (IAMs). The IAM and non-IAM literature, however, is also categorised separately to elucidate what is and is not included in global mitigation scenarios, like those included in the SR15. Results from bottom-up studies and models (e.g., Griscom et al. 2017 <sup>[[#fn:r1274|1274]]</sup> ) are assessed in Sections 6.2–6.3.

''Response options in future scenarios''

More than half of the 40 land-based response options discussed in this chapter are represented in global IAMs models used to develop and analyse future scenarios, either implicitly or explicitly (Table 6.76). For example, all IAMs include improved cropland management, either explicitly through technologies that improve nitrogen use efficiency (Humpenöder et al. 2018 <sup>[[#fn:r1051|1051]]</sup> ) or implicitly through marginal abatement cost curves that link reductions in nitrous oxide emissions from crop production to carbon prices (most other models).

However, the literature discussing the effect of these response options on land-based challenges is more limited (Table 6.76). There are 57 studies (43 IAM studies) that articulate the effect of response options on mitigation, with most including bioenergy and BECCS or a combination of reduced deforestation, reforestation, and afforestation; 37 studies (21 IAM studies) discuss the implications of response options on food security, usually using food price as a metric. While a small number of non-IAM studies examine the effects of response options on desertification (three studies) and land degradation (five studies), no IAM studies were identified. However, some studies quantify these challenges indirectly using IAMs, either via climate outputs from the representative concentration pathways (RCPs) (Huang et al. 2016 <sup>[[#fn:r1052|1052]]</sup> ) or by linking IAMs to other land and ecosystem models (Ten Brink et al. 2018 <sup>[[#fn:r1275|1275]]</sup> ; UNCCD 2017 <sup>[[#fn:r1053|1053]]</sup> ).

For many of the scenarios in the literature, land-based response options are included as part of a suite of mitigation options (Popp et al. 2017 <sup>[[#fn:r1054|1054]]</sup> ; Van Vuuren et al. 2015). As a result, it is difficult to isolate the effect of an individual option on land-related challenges. A few studies focus on specific response options (Calvin et al. 2014 <sup>[[#fn:r1055|1055]]</sup> ; Popp et al. 2014 <sup>[[#fn:r1056|1056]]</sup> ; Kreidenweis et al. 2016 <sup>[[#fn:r1057|1057]]</sup> ; Humpenöder et al. 2018 <sup>[[#fn:r1058|1058]]</sup> ), quantifying the effect of including an individual option on a variety of sustainability targets.

<div id="section-6-4-4-2-interlinkages-and-response-options-in-future-scenarios-block-2"></div>

<span id="table-6.76"></span>
<!-- START IMG -->
<!-- TABLE IMG -->
<!-- IMG TITLE -->
'''Table 6.76'''

<span id="number-of-iam-and-non-iam-studies-including-specific-response-options-rows-and-quantifying-particular-land-challenges-columns."></span>
<!-- IMG CAPTION -->
'''Number of IAM and non-IAM studies including specific response options (rows) and quantifying particular land challenges (columns).'''

Thethird column shows how many IAM models include the individual response option. The remaining columns show challenges related to climate change (C), mitigation (M), adaptation (A), desertification (D), land degradation (L), food security (F), and biodiversity/ecosystem services/sustainable development (B). Additionally, counts of total (left value) and IAM-only (right value) studies are included. Some IAMs include agricultural economic models, which can also be run separately; these models are not counted as IAM literature when used on their own. Studies using a combination of IAMs and non-IAMs are included in the total only. A complete list of studies is included in the Appendix.
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[[File:1ed9445e1a0fc320ff64f76906dd2167 table-6.76a.png]] [[File:c227a95b28d21beaa206b94c0af9e80d table-6.76b.png]]

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<div id="section-6-4-4-2-interlinkages-and-response-options-in-future-scenarios-block-3"></div>

''Interactions and interlinkages between response options''

The effect of response options on desertification, land degradation, food security, biodiversity, and other SDGs depends strongly on which options are included, and the extent to which they are deployed. For example, Sections 2.6 and 6.3.6, and Cross-Chapter Box 7 note that bioenergy and BECCS has a large mitigation potential, but could potentially have adverse side effects for land degradation, food security, and other SDGs. Global modelling studies demonstrate that these effects are dependent on scale. Increased use of bioenergy can result in increased mitigation (Figure 6.8, panel A) and reduced climate change, but can also lead to increased energy cropland expansion (Figure 6.8, panel B), and increased competition for land, resulting in increased food prices (Figure 6.8, panel C). However, the exact relationship between bioenergy deployment and each sustainability target depends on a number of other factors, including the feedstock used, the underlying socio-economic scenario, assumptions about technology and resource base, the inclusion of other response options, and the specific model used (Calvin et al. 2014 <sup>[[#fn:r1059|1059]]</sup> ; Clarke et al. 2014 <sup>[[#fn:r1060|1060]]</sup> ; Popp et al. 2014, 2017 <sup>[[#fn:r1061|1061]]</sup> ; Kriegler et al. 2014 <sup>[[#fn:r1062|1062]]</sup> ).

The previous sections have examined the effects of individual land-response options on multiple challenges. A number of studies using global modelling and analyses have examined interlinkages and interaction effects among land response options by incrementally adding or isolating the effects of individual options. Most of these studies focus on interactions with bioenergy and BECCS (Table 6.77). Adding response options that require land (e.g., reforestation, afforestation, reduced deforestation, avoided grassland conversion, or biodiversity conservation) results in increased food prices (Calvin et al. 2014 <sup>[[#fn:r1063|1063]]</sup> ; Humpenöder et al. 2014 <sup>[[#fn:r1064|1064]]</sup> ; Obersteiner et al. 2016 <sup>[[#fn:r1065|1065]]</sup> ; Reilly et al. 2012 <sup>[[#fn:r1066|1066]]</sup> ) and potentially increased temperature through biophysical climate effects (Jones et al. 2013 <sup>[[#fn:r1067|1067]]</sup> ). However, this combination can result in reduced water consumption (Hejazi et al. 2014b <sup>[[#fn:r1068|1068]]</sup> ), reduced cropland expansion (Calvin et al. 2014 <sup>[[#fn:r1069|1069]]</sup> ; Humpenöder et al. 2018 <sup>[[#fn:r1070|1070]]</sup> ), increased forest cover (Calvin et al. 2014 <sup>[[#fn:r1071|1071]]</sup> ; Humpenöder et al. 2018 <sup>[[#fn:r1072|1072]]</sup> ; Wise et al. 2009 <sup>[[#fn:r1073|1073]]</sup> ) and reduced biodiversity loss (Pereira et al. 2010 <sup>[[#fn:r1074|1074]]</sup> ), compared to scenarios with bioenergy and BECCS alone. While these options increase total mitigation, they reduce mitigation from bioenergy and BECCS as they compete for the same land (Wu et al. 2019 <sup>[[#fn:r1075|1075]]</sup> ; Baker et al. 2019 <sup>[[#fn:r1076|1076]]</sup> ; Calvin et al. 2014 <sup>[[#fn:r1077|1077]]</sup> ; Humpenöder et al. 2014 <sup>[[#fn:r1078|1078]]</sup> ).

The inclusion of land-sparing options (e.g., dietary change, increased food productivity, reduced food waste, management of supply chains) in addition to bioenergy and BECCS results in reduced food prices, reduced agricultural land expansion, reduced deforestation, reduced mitigation costs, reduced water use, and reduced biodiversity loss (Bertram et al. 2018 <sup>[[#fn:r1276|1276]]</sup> ; Wu et al. 2019 <sup>[[#fn:r1079|1079]]</sup> ; Obersteiner et al. 2016 <sup>[[#fn:r1080|1080]]</sup> ; Stehfest et al. 2009 <sup>[[#fn:r1081|1081]]</sup> ; Van Vuuren et al. 2018). These options can increase bioenergy potential, resulting in increased mitigation than from bioenergy and BECCS alone (Wu et al. 2019 <sup>[[#fn:r1082|1082]]</sup> ; Stehfest et al. 2009 <sup>[[#fn:r1083|1083]]</sup> ; Favero and Massetti 2014 <sup>[[#fn:r1084|1084]]</sup> ).

Other combinations of land response options create synergies, alleviating land pressures. The inclusion of increased food productivity and dietary change can increase mitigation, reduce cropland use, reduce water consumption, reduce fertiliser application, and reduce biodiversity loss (Springmann et al. 2018 <sup>[[#fn:r1085|1085]]</sup> ; Obersteiner et al. 2016 <sup>[[#fn:r1086|1086]]</sup> ). Similarly, improved livestock management, combined with increased food productivity, can reduce agricultural land expansion (Weindl et al. 2017 <sup>[[#fn:r1087|1087]]</sup> ). Reducing disturbances (e.g., fire management) in combination with afforestation can increase the terrestrial carbon sink, resulting in increased mitigation potential and reduced mitigation cost (Le Page et al. 2013 <sup>[[#fn:r1088|1088]]</sup> ).

Studies including multiple land response options often find that the combined mitigation potential is not equal to the sum of individual mitigation potential as these options often share the same land. For example, including both afforestation and bioenergy and BECCS results in a cumulative reduction in GHG emissions of 1200 GtCO 2 between 2005 and 2100, which is much lower than the sum of the contributions of bioenergy (800 GtCO 2 ) and afforestation (900 GtCO 2 ) individually (Humpenöder et al. 2014 <sup>[[#fn:r1089|1089]]</sup> ). More specifically, Baker et al. (2019) <sup>[[#fn:r1090|1090]]</sup> find that woody bioenergy and afforestation are complementary in the near term, but become substitutes in the long term, as they begin to compete for the same land. Similarly, the combined effect of increased food productivity, dietary change and reduced waste on GHG emissions is less than the sum of the individual effects (Springmann et al. 2018 <sup>[[#fn:r1091|1091]]</sup> ).

<div id="section-6-4-4-2-interlinkages-and-response-options-in-future-scenarios-block-4"></div>

<span id="table-6.77"></span>
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'''Table 6.77'''

<span id="interlinkages-between-bioenergy-and-beccs-and-other-response-options."></span>
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'''Interlinkages between bioenergy and BECCS and other response options.'''

Table indicates the combined effects of multiple land-response options on climate change (C), mitigation (M), adaptation (A), desertification (D), land degradation (L), food security (F), and biodiversity/ecosystem services/sustainable development (O). Each cell indicates the implications of adding the option specified in the row in addition to bioenergy and BECCS. Blue colours indicate positive interactions (e.g., including the option in the second column increases mitigation, reduces cropland area, or reduces food prices relative to bioenergy and BECCS alone). Yellow indicates negative interactions; grey indicates mixed interactions (some positive, some negative). Note that only response option combinations found in the assessed literature are included in the interest of space.
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[[File:4d6d1c2debaf8ba92a8ab32e2f83baca table-6.77a.png]] [[File:74513e4d1bd4d21adea7a5f1b3a1872f table-6.77b.png]]

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<div id="section-6-4-4-2-interlinkages-and-response-options-in-future-scenarios-block-5"></div>

Land-related response options can also interact with response options in other sectors. For example, limiting deployment of a mitigation response option will either result in increased climate change or additional mitigation in other sectors. A number of studies have examined limiting bioenergy and BECCS. Some such studies show increased emissions (Reilly et al. 2012 <sup>[[#fn:r1097|1097]]</sup> ). Other studies meet the same climate goal, but reduce emissions elsewhere ''via'' reduced energy demand (Grubler et al. 2018 <sup>[[#fn:r1098|1098]]</sup> ; Van Vuuren et al. 2018 <sup>[[#fn:r1277|1277]]</sup> ), increased fossil carbon capture and storage (CCS), nuclear energy, energy efficiency and/or renewable energy (Van Vuuren et al. 2018 <sup>[[#fn:r1278|1278]]</sup> ; Rose et al. 2014 <sup>[[#fn:r1099|1099]]</sup> ; Calvin et al. 2014 <sup>[[#fn:r1100|1100]]</sup> ; Van Vuuren et al. 2017b <sup>[[#fn:r1279|1279]]</sup> ), dietary change (Van Vuuren et al. 2018 <sup>[[#fn:r1280|1280]]</sup> ), reduced non-CO 2 emissions (Van Vuuren et al. 2018 <sup>[[#fn:r1281|1281]]</sup> ), or lower population (Van Vuuren et al. 2018 <sup>[[#fn:r1282|1282]]</sup> ). The co-benefits and adverse side effects of non-land mitigation options are discussed in SR15, Chapter 5. Limitations on bioenergy and BECCS can result in increases in the cost of mitigation (Kriegler et al. 2014 <sup>[[#fn:r1101|1101]]</sup> ; Edmonds et al. 2013 <sup>[[#fn:r1102|1102]]</sup> ). Studies have also examined limiting CDR, including reforestation, afforestation, and bioenergy and BECCS (Kriegler et al. 2018a <sup>[[#fn:r1282|1282]]</sup> ,b <sup>[[#fn:r1283|1283]]</sup> ). These studies find that limiting CDR can increase mitigation costs, increase food prices, and even preclude limiting warming to less than 1.5°C above pre-industrial levels (Kriegler et al. 2018a,b; Muratori et al. 2016 <sup>[[#fn:r1103|1103]]</sup> ).

In some cases, the land challenges themselves may interact with land-response options. For example, climate change could affect the production of bioenergy and BECCS. A few studies examine these effects, quantifying differences in bioenergy production (Calvin et al. 2013 <sup>[[#fn:r1104|1104]]</sup> ; Kyle et al. 2014 <sup>[[#fn:r1105|1105]]</sup> ) or carbon price (Calvin et al. 2013 <sup>[[#fn:r1106|1106]]</sup> ) as a result of climate change. Kyle et al. (2014) <sup>[[#fn:r1107|1107]]</sup> find increase in bioenergy production due to increases in bioenergy yields, while Calvin et al. (2013) <sup>[[#fn:r1108|1108]]</sup> find declines in bioenergy production and increases in carbon price due to the negative effects of climate on crop yield.

''Gaps in the literature''

Not all of the response options discussed in this chapter are included in the assessed literature, and many response options are excluded from the IAM models. The included options (e.g., bioenergy and BECCS; reforestation) are some of the largest in terms of mitigation potential (see Section 6.3). However, some of the options excluded also have large mitigation potential. For example, biochar, agroforestry, restoration/avoided conversion of coastal wetlands, and restoration/ avoided conversion of peatland all have mitigation potential of about 1 GtCO 2 yr –1 (Griscom et al. 2017 <sup>[[#fn:r1109|1109]]</sup> ). Additionally, quantifications of and response options targeting land degradation and desertification are largely excluded from the modelled studies, with a few notable exceptions (Wolff et al. 2018 <sup>[[#fn:r1110|1110]]</sup> ; Gao and Bryan 2017 <sup>[[#fn:r1111|1111]]</sup> ; Ten Brink et al. 2018 <sup>[[#fn:r1112|1112]]</sup> ; UNCCD 2017 <sup>[[#fn:r1113|1113]]</sup> ). Finally, while a large number of papers have examined interactions between bioenergy and BECCS and other response options, the literature examining other combinations of response options is more limited.

<div id="section-6-4-4-3-resolving-challenges-in-response-option-implementation"></div>

<span id="resolving-challenges-in-response-option-implementation"></span>
==== 6.4.4.3 Resolving challenges in response option implementation ====

<div id="section-6-4-4-3-resolving-challenges-in-response-option-implementation-block-1"></div>

The 40 response options assessed in this chapter face a variety of barriers to implementation that require action across multiple actors to overcome (Section 6.4.1). Studies have noted that, while adoption of response options by individuals may depend on individual assets and motivation, larger structural and institutional factors are almost always equally important if not more so (Adimassu et al. 2016 <sup>[[#fn:r1114|1114]]</sup> ; Djenontin et al. 2018 <sup>[[#fn:r1115|1115]]</sup> ), though harder to capture in research variables (Schwilch et al. 2014 <sup>[[#fn:r1116|1116]]</sup> ). These institutional and governance factors can create an enabling environment for sustainable land management (SLM) practices, or challenges to their adoption (Adimassu et al. 2013 <sup>[[#fn:r1117|1117]]</sup> ). Governance factors include the institutions that manage rules and policies, the social norms and collective actions of participants (including civil society actors and the private sector), and the interactions between them (Ostrom 1990 <sup>[[#fn:r1118|1118]]</sup> ; Huntjens et al. 2012 <sup>[[#fn:r1119|1119]]</sup> ; Davies 2016 <sup>[[#fn:r1120|1120]]</sup> ). Many of Ostrom’s design principles for successful governance can be applied to response options for SLM; these principles are: (i) clearly defined boundaries, (ii) understanding of both benefits and costs, (iii) collective choice arrangements, (iv) monitoring, (v) graduated sanctions, (vi) conflict-resolution mechanisms, (vii) recognition of rights, and (viii) nested (multi-scale) approaches. Unfortunately, studies of many natural resources and land management policy systems – in particular, in developing countries – often show the opposite: a lack of flexibility, strong hierarchical tendencies, and a lack of local participation in institutional frameworks (Ampaire et al. 2017 <sup>[[#fn:r1121|1121]]</sup> ). Analysis of government effectiveness (GE) – defined as quality of public services, policy formulation and implementation, civil service and the degree of its independence from political pressures, as well as credibility of the government’s commitment to its policies (Kaufmann et al. 2010 <sup>[[#fn:r1122|1122]]</sup> ) – has been shown to play a key role in land management. GE mediates land-user actions on land management and investment, and government policies and laws can help land users adopt sustainable land management practices (Nkonya et al. 2016 <sup>[[#fn:r1123|1123]]</sup> ) (Figure 6.9).

It is simply not a matter of putting the ‘right’ institutions or policies in place, however, as governance can be undermined by inattention to power dynamics (Fabinyi et al. 2014 <sup>[[#fn:r1124|1124]]</sup> ). Power shapes how actors gain access and control over resources, and negotiate, transform and adopt certain response options or not. These variable dynamics of power between different levels and stakeholders have an impact on the ability to implement different response options. The inability of many national governments to address social exclusion in general will have an effect on the implementation of many response options. Further, response options themselves can become avenues for actors to exert power claims over others (Nightingale 2017 <sup>[[#fn:r1125|1125]]</sup> ). For example, there have been many concerns that reduced deforestation and forest degradation projects run the risk of reversing trends towards decentralisation in forest management and creating new power disparities between the state and local actors (Phelps et al. 2010 <sup>[[#fn:r1126|1126]]</sup> ). Below we assess how two important factors – the involvement of stakeholders, and the coordination of action across scales – will help in moving from response options to policy implementation, a theme Chapter 7 takes up in further detail.

''Involvement of stakeholders''

A wide range of stakeholders are necessary for successful land, agricultural and environmental policy, and implementing response options requires that a range of actors, including businesses, consumers, land managers, indigenous peoples and local communities, scientists, and policymakers work together for success. Diverse stakeholders have a particularly important role to play in defining problems, assessing knowledge and proposing solutions (Stokes et al. 2006 <sup>[[#fn:r1127|1127]]</sup> ; Phillipson et al. 2012 <sup>[[#fn:r1128|1128]]</sup> ). Lack of connection between science knowledge and on-the-ground practice has hampered adoption of many response options in the past; simply presenting ‘scientifically’ derived response options is not enough (Marques et al. 2016 <sup>[[#fn:r1129|1129]]</sup> ). For example, the importance of recognising and incorporating local knowledge and indigenous knowledge is increasingly emphasised in successful policy implementation (see Cross-Chapter Box 13 in Chapter 7), as local practices of water management, soil fertility management, improved grazing, restoration and sustainable management of forests are often well-aligned with response options assessed by scientists (Marques et al. 2016 <sup>[[#fn:r1130|1130]]</sup> ).

<div id="section-6-4-4-3-resolving-challenges-in-response-option-implementation-block-2"></div>

<span id="figure-6.9"></span>
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'''Figure 6.9'''

<span id="relationship-between-changes-in-government-effectiveness-ge-and-changes-in-land-management.-notes-ndvi-change-in-normalized-difference-vegetation-index-baseline-year-2001-endline-year-2010.-source-of-ndvi-data-modis-goveff-change-in-ge-baseline-year-2001-endline-year-2010.-world-bank-nkonya-et-al.-2016."></span>
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'''Relationship between changes in government effectiveness (GE) and changes in land management. Notes: ∆NDVI = Change in Normalized Difference Vegetation Index (baseline year 2001, Endline year 2010). Source of NDVI data: MODIS ∆GovEff = Change in GE (baseline year 2001, endline year 2010). (World Bank; Nkonya et al. 2016).'''
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[[File:71fa138c8d6e6564c85c3e6e1e1fc811 Figure-6.9-1024x819.jpg]]

Relationship between changes in government effectiveness (GE) and changes in land management. Notes: ∆NDVI = Change in Normalized Difference Vegetation Index (baseline year 2001, Endline year 2010). Source of NDVI data: MODIS ∆GovEff = Change in GE (baseline year 2001, endline year 2010). (World Bank; Nkonya et al. 2016 <sup>[[#fn:r1284|1284]]</sup> ).

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<div id="section-6-4-4-3-resolving-challenges-in-response-option-implementation-block-3"></div>

Stakeholder engagement is an important approach for successful environmental and climate policy and planning. Tools such as stakeholder mapping, in which affected and interested parties are identified and described in terms of their interrelationships and current or future objectives and aspirations, and scenario-based stakeholder engagement, which combines stakeholder analysis with climate scenarios, are increasingly being applied to facilitate better planning outcomes (Tompkins et al. 2008 <sup>[[#fn:r1131|1131]]</sup> ; Pomeroy and Douvere 2008 <sup>[[#fn:r1132|1132]]</sup> ; Star et al. 2016 <sup>[[#fn:r1133|1133]]</sup> ). Facilitated dialogues early in design processes have shown good success in bringing multiple and sometimes conflicting stakeholders to the table to discuss synergies and trade-offs around policy implementation (Gopnik et al. 2012 <sup>[[#fn:r1134|1134]]</sup> ). Knowledge exchange, social learning, and other concepts are also increasingly being incorporated into understanding how to facilitate sustainable land management (Djenontin et al. 2018 <sup>[[#fn:r1135|1135]]</sup> ), as evidence suggests that negotiating the complexity of socio-ecological systems (SES) requires flexible learning arrangements, in particular for multiple stakeholders (Gerlak and Heikkila 2011 <sup>[[#fn:r1136|1136]]</sup> ; Armitage et al. 2018 <sup>[[#fn:r1137|1137]]</sup> ; Heikkila and Gerlak 2018 <sup>[[#fn:r1138|1138]]</sup> ). Social learning has been defined as ‘a change in understanding and skills that becomes situated in groups of actors/ communities of practice through social interactions,’ (Albert et al. 2012 <sup>[[#fn:r1139|1139]]</sup> ), and social learning is often linked with attempts to increase levels of participation in decision-making, from consultation to more serious community control (Collins and Ison 2009 <sup>[[#fn:r1140|1140]]</sup> ; McCrum et al. 2009 <sup>[[#fn:r1141|1141]]</sup> ). Learning also facilitates responses to emerging problems and helps actors in SESs grapple with complexity. One outcome of learning can be adaptive risk management (ARM), in which ‘one takes action based on available information, monitors what happens, learns from the experience and adjusts future actions based on what has been learnt’ (Bidwell et al. 2013 <sup>[[#fn:r1142|1142]]</sup> ). Suggestions to facilitate social learning, ARM, and decision-making include extending science-policy networks and using local bridging organisations, such as extension services, for knowledge co-production (Bidwell et al. 2013 <sup>[[#fn:r1143|1143]]</sup> ; Böcher and Krott 2014 <sup>[[#fn:r1144|1144]]</sup> ; Howarth and Monasterolo 2017 <sup>[[#fn:r1145|1145]]</sup> ) (see further discussion in Chapter 7, Section 7.5).

Ensuring that women are included as key stakeholders in response option implementation is also important, as gender norms and roles affect vulnerability and access to resources, and gender inequality limits the possible range of responses for adoption by women (Lambrou and Piana 2006 <sup>[[#fn:r1146|1146]]</sup> ). For example, environmental change may increase women’s workload as their access to natural resources may decline, or they may have to take up low-wage labour if agriculture becomes unsuitable in their local areas under climate change (Nelson et al. 2002 <sup>[[#fn:r1147|1147]]</sup> ). Every response option considered in this chapter potentially has a gender dimension to it that needs to be taken into consideration (Tables 6.73–6.75 note how response options intersect with SDG 5 Gender Equality); for example, to address food security through sustainable intensification will clearly have to address female farmers in Africa (Kondylis et al. 2016 <sup>[[#fn:r1148|1148]]</sup> ; Garcia and Wanner 2017 <sup>[[#fn:r1149|1149]]</sup> ) (for further information, see Cross-Chapter Box 11 in Chapter 7).

''Challenges of coordination''

Coordinated action to implement the response options will be required across a range of actors, including business, consumers, land managers, indigenous peoples and local communities and policymakers to create enabling conditions. Conjoining response options to maximise social, climatic and environmental benefits will require framing of such actions as strong pathways to sustainable development (Ayers and Dodman 2010 <sup>[[#fn:r1150|1150]]</sup> ). As the chapter has pointed out, there are many potential options for synergies, especially among several response options that might be applied together and in coordination with one another (such as dietary change and improved land management measures). This coordination will help ensure that synergies are met and trade-offs minimised, but this will require deliberate coordination across multiple scales, actors and sectors. For example, 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. 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 (Biermann et al. 2009 <sup>[[#fn:r1151|1151]]</sup> ; Deininger et al. 2014 <sup>[[#fn:r1152|1152]]</sup> ) (see Chapter 7, Section 7.6.2).

Many of the response options listed in this chapter could be potentially implemented as ‘community-based’ actions, including community-based reforestation, community-based insurance, or community-based disaster risk management. Grounding response options in community approaches aims to identify, assist and implement activities ‘that strengthen the capacity of local people to adapt to living in a riskier and less predictable climate’ (Ayers and Forsyth 2009 <sup>[[#fn:r1153|1153]]</sup> ). Research shows that people willingly come together to provide mutual aid and protection against risk, to manage natural resources, and to work cooperatively to find solutions to environmental provisioning problems. Some activities that fall under this type of collective action include the creation of institutions or rules, working cooperatively to manage a resource by restricting some activities and encouraging others, sharing information to improve public goods, or mobilising resources (such as capital) to fix a collective problem (Ostrom 2000 <sup>[[#fn:r1154|1154]]</sup> ; Poteete and Ostrom 2004 <sup>[[#fn:r1155|1155]]</sup> ), or engagement in participatory land-use planning (Bourgoin 2012 <sup>[[#fn:r1156|1156]]</sup> ; Evers and Hofmeister 2011 <sup>[[#fn:r1157|1157]]</sup> ). These participatory processes ‘are likely to lead to more beneficial environmental outcomes through better informed, sustainable decisions, and win-win solutions regarding economic and conservation objectives’ (Vente et al. 2016 <sup>[[#fn:r1158|1158]]</sup> ), and evaluations of community-based response options have been generally positive (Karim and Thiel 2017 <sup>[[#fn:r1159|1159]]</sup> ; Tompkins and Adger 2004 <sup>[[#fn:r1160|1160]]</sup> ).

Agrawal (2001) <sup>[[#fn:r1161|1161]]</sup> has identified more than 30 different indicators that have been important in understanding who undertakes collective action for the environment, including: the size of the group undertaking action; the type and distribution of the benefits from the action; the heterogeneity of the group; the dependence of the group on these benefits; the presence of leadership; presence of social capital and trust; and autonomy and independence to make and enforce rules. Alternatively, when households expect the government to undertake response actions, they have less incentive to join in collective action, as the state role has ‘crowded out’ local cooperation (Adger 2009 <sup>[[#fn:r1162|1162]]</sup> ). High levels of social trust and capital can increase willingness of farmers to engage in response options, such as improved soil management or carbon forestry (Stringer et al. 2012 <sup>[[#fn:r1163|1163]]</sup> ; Lee 2017 <sup>[[#fn:r1164|1164]]</sup> ), and social capital helps with connectivity across levels of SESs (Brondizio et al. 2009 <sup>[[#fn:r1165|1165]]</sup> ). Dietz et al. (2013) <sup>[[#fn:r1166|1166]]</sup> lay out important policy directions for more successful facilitation of collective action across scales and stakeholders. These include: providing information; dealing with conflict; inducing rule compliance; providing physical, technical or institutional infrastructure; and being prepared for change. The adoption of participatory protocols and structured processes to select response options together with stakeholders will likely lead to greater success in coordination and participation (Bautista et al. 2017 <sup>[[#fn:r1167|1167]]</sup> ; Franks 2010 <sup>[[#fn:r1168|1168]]</sup> ; Schwilch et al. 2012a <sup>[[#fn:r1169|1169]]</sup> ).

However, wider adoption of community-based approaches is potentially hampered by several factors, including the fact that most are small-scale (Forsyth 2013 <sup>[[#fn:r1170|1170]]</sup> ; Ensor et al. 2014 <sup>[[#fn:r1171|1171]]</sup> ) and it is often unclear how to assess criteria of success (Forsyth 2013 <sup>[[#fn:r1172|1172]]</sup> ). Others also caution that community-based approaches often are not able to adequately address the key drivers of vulnerability such as inequality and uneven power relations (Nagoda and Nightingale 2017 <sup>[[#fn:r1173|1173]]</sup> ).

''Moving from response options to policies''

Chapter 7 discusses in further depth the risks and challenges involved in formulating policy responses that meet the demands for sustainable land management and development outcomes, such as food security, community adaptation and poverty alleviation. Table 7.1 in Chapter 7 maps how specific response options might be turned into policies; for example, to implement a response option aimed at agricultural diversification, a range of policies from elimination of agricultural subsidies (which might favour single crops) to environmental farm programmes and agro-environmental payments (to encourage alternative crops). Oftentimes, any particular response option might have a variety of potential policy pathways that might address different scales or stakeholders or take on different aspects of coordination and integration (Section 7.6.1). Given the unique challenges of decision-making under uncertainty in future climate scenarios, Chapter 7 particularly discusses the need for flexible, iterative, and adaptive processes to turn response options into policy frameworks.

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