Editing IPCC:AR6/WGII/Chapter-5 (section)

== 5.14 Implementation Pathways to Adaptation and Co-benefits ==

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<span id="state-of-adaptation-of-food-feed-fibre-and-other-ecosystem-products"></span>
=== 5.14.1 State of Adaptation of Food, Feed, Fibre and Other Ecosystem Products ===

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Since AR5, several adaptation reviews have been done ( [[#Ford--2015|Ford et al., 2015]] ; [[#Lesnikowski--2016|Lesnikowski et al., 2016]] ). In a review of 1159 peer-reviewed sources, [[#Berrang-Ford--2021b|Berrang-Ford et al. (2021b)]] found that observed adaptations in food, fibre and other ecosystem products have consisted mainly of changes in autonomous behaviour changes, such as changing planting time, followed by technological/infrastructure and ecosystem-based adaptation approaches, the majority of which have occurred in Africa and Asia (Figures 5.20 and 5.21, Table 5.22). Several adaptation options addressed multiple SDGs (e.g., 2, 6, 8, 12) (Figure 5.21).

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[[File:b41ed2ff75d9ec3f7f91a415a3342193 IPCC_AR6_WGII_Figure_5_019.png]]

'''Figure 5.19 |''' '''State of adaptation by region and type of response (based on 1159 peer-reviewed references that addressed adaptation in food, fibre and other ecosystem products sector; source: Global Adaptation Mapping Initiative (GAMI) database (Berrang-Ford et al.''' ''', 2021a).''' The bars indicate the amount of evidence for the category ''x'' region.

Assessment of adaptation options was done for 15 potential options for land and ecosystem transitions (SM5.7, Figure 5.22a). Several adaptation options have high to medium feasibility, with ''robust evidence'' , ''high agreement'' about the adaptive capacity resilience building potential of options in relation to climate change impact drivers ( ''high confidence'' ). Policy and planning and production shifts have limited evidence for feasibility. Most options are technically and physically feasible, with generally high political and social acceptability and environmental feasibility, but have limited evidence for institutional feasibility. Most adaptation options have medium to high microeconomic feasibility ( ''high confidence'' ) but ''limited evidence'' for macroeconomic viability.

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[[File:6841b99fbe0d5aa33f0d7512c25da42a IPCC_AR6_WGII_Figure_5_022.png]]

'''Figure 5.22 |''' '''Assessment of 11 feasibility indicators (six categories), five effectiveness indicators and maladaptation of adaptation options based on 287 peer-reviewed papers.''' See SM5.7 for methods and data. Scores ranging from 1 (low) to 3 (high) were obtained by averaging five or more papers for each option and indicator. Blank cells were not assessed because of insufficient literature.

Among five effectiveness indicators (SM5.7, Figure 5.22b), most options have ''robust evidence'' of reduced risk vulnerability to climate change, with low scores for local governance, substitution of plant or animal type, community forest management, livelihood diversification and climate services. Higher-scored options to reduce risk included increasing biodiversity (at landscape and field level), community seed banks, conventional breeding (plant and animals), mixed systems and agroecological approaches ( ''medium confidence'' ), suggesting multiple co-benefits of these options. Most options have high scores for enhancing social well-being and economic and environmental benefits ( ''medium confidence'' ) but limited evidence for strengthening institutions for most options. There were low scores for potential maladaptation ( ''medium confidence'' ).

'''Table 5.23 |''' State of adaptation in food, fibre and other ecosystem products by actors and vulnerabe groups (source: GAMI database; [[#Berrang-Ford--2021a|Berrang-Ford et al., 2021a]] )).

{| class="wikitable"
|-
! '''Actors'''

! '''''N''''' '''(%)'''

! '''Vulnerable groups'''

! '''Planned,''' '''''N''''' '''(%)'''

! '''Implemented,''' '''''N''''' '''(%)'''

|-
| ''International or multi-national governance institutions''

| 72 (6%)

| ''Women''

| 134 (12%)

| 118 (10%)

|-
| ''National government''

| 264 (23%)

| ''Youth''

| 22 (2%)

| 24 (2%)

|-
| ''Local government''

| 267 (23%)

| ''Elderly''

| 31 (3%)

| 28 (2%)

|-
| ''Sub-national government''

| 89 (8%)

| ''Low income''

| 201 (17%)

| 258 (22%)

|-
| ''Private sector corporations''

| 56 (5%)

| ''Disabled''

| 2 (0%)

| 3 (0%)

|-
| ''Private sector SMEs''

| 80 (7%)

| ''Migrants''

| 12 (1%)

| 18 (2%)

|-
| ''Civil Society — international/multi-national/national''

| 117 (10%)

| ''Indigenous''

| 95 (8%)

| 85 (7%)

|-
| ''Civil Society — sub-national or local''

| 257 (22%)

| ''Ethnic minorities''

| 32 (3%)

| 32 (3%)

|-
| ''Individuals or households''

| 1087 (94%)

|
|}

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[[File:93ce548539bd2c960acf37bba4d04ae7 IPCC_AR6_WGII_Figure_5_020.png]]

'''Figure 5.20 |''' '''Observed adaptation across regions in food, fibre and other ecosystem products based on the GAMI database (Berrang-Ford et al.''' ''', 2021a).''' The bars indicate the number of evidence for the options ''x'' region.

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[[File:513a63d93ec2f2ce5b59de040b203bd6 IPCC_AR6_WGII_Figure_5_021.png]]

'''Figure 5.21 |''' '''How different response types address the SDGs based on GAMI.'''

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<span id="nature-based-solutions-or-ecosystem-based-adaptation"></span>
==== 5.14.1.1 Nature-based solutions or ecosystem-based adaptation ====

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There is growing evidence that nature-based solutions (NBS), which emphasise ecological approaches and biodiversity conservation (Chapter 1), have high potential to transform land and aquatic systems into climate-resilient systems ''(medium evidence'' , ''high agreement'' ) ( [[#Albert--2017|Albert et al., 2017]] ; [[#Brugère--2019|Brugère et al., 2019]] ; [[#Galappaththi--2020b|Galappaththi et al., 2020b]] ; [[#Snapp--2021|Snapp et al., 2021]] ; Cross-Working Group Box BIOECO; Cross-Chapter Box NATURAL in Chapter 2).

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<span id="climate-services"></span>
==== 5.14.1.2 Climate services ====

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Climate services, understood as the production, translation, communication and use of climate information in decision-making processes, can contribute to adaptation efforts in agricultural systems ( ''medium agreement'' , ''low evidence'' ). Climate services can support decision makers in agriculture by providing tailored information that can inform the implementation of specific adaptation options (Vaughan, 2018; [[#Buontempo--2019|Buontempo et al., 2019]] ; [[#Dobardzic--2019|Dobardzic et al., 2019]] ; [[#Hank--2019|Hank et al., 2019]] ).

For some high- and medium-income countries, evidence suggests that climate services have been underutilised ( [[#Mase--2014|Mase and Prokopy, 2014]] ), with ''limited evidence'' in these countries of the impact of climate services on yields, income, and food security and nutrition. In low-income countries, use of climate services can increase yields and incomes and promote changes in farmers’ practices ( ''low confidence'' ) ( [[#Roudier--2014|Roudier et al., 2014]] ; [[#Roudier--2016|Roudier et al., 2016]] ; [[#Tarchiani--2017|Tarchiani et al., 2017]] ; [[#Ouedraogo--2018|Ouedraogo et al., 2018]] ). There is ''low confidence'' that climate services are delivering on their potential, whether they are being accessed by the vulnerable, and how these services are contributing to food security and nutrition ( [[#Ouedraogo--2018|Ouedraogo et al., 2018]] ; [[#Vaughan--2019|Vaughan et al., 2019]] ).

Improved design and delivery of climate services can enhance effectiveness ( ''medium confidence'' ) ''.'' Ways to enhance the impact of climate services include integrating information from multiple sources at different scales ( [[#Bouroncle--2019|Bouroncle et al., 2019]] ), participatory collection and analysis of climate information (Loboguerrero AM, 2018; [[#Tesfaye--2019|Tesfaye et al., 2019]] ; Rossa, 2020), and making forecast information available in local languages and as verbal communications for farmers who cannot read ( [[#Nkiaka--2019|Nkiaka et al., 2019]] ).

In countries with limited climate data, crowd sourcing (outsourcing data collection to the public) ( [[#Minet--2017|Minet et al., 2017]] ) and digital tools present an opportunity for addressing climate risk ( ''medium confidence'' ) ( [[#Osgood--2018|Osgood et al., 2018]] ; Thornton, 2018; [[#Partey--2020|Partey et al., 2020]] ; [[#Sotelo--2020|Sotelo et al., 2020]] ). Bundling additional services such as market information with climate information may be effective at plugging information gaps ( ''low confidence'' ) ( [[#Chatuphale--2018|Chatuphale and Armstrong, 2018]] ; Tsan et al., 2019; [[#Tesfaye--2019|Tesfaye et al., 2019]] )

There may be inequality in access to climate services; their use may tend to benefit large-scale operations and disadvantage small- and medium-scale farmers and others who face issues of access due to social and economic inequity; also some groups such as pastoralists have not yet benefitted from climate services ( ''high confidence'' ) ( [[#Furman--2014|Furman et al., 2014]] ; [[#Muema--2018|Muema et al., 2018]] ; [[#Awazi--2019|Awazi et al., 2019]] ; [[#Nyantakyi-Frimpong--2019|Nyantakyi-Frimpong, 2019]] ; [[#Paudyal--2019|Paudyal et al., 2019]] ; [[#Vaughan--2019|Vaughan et al., 2019]] ; [[#Nidumolu--2020|Nidumolu et al., 2020]] ; [[#Partey--2020|Partey et al., 2020]] ). Other challenges include technology ignorance, data privacy and security, data access permissions, software and system compatibility, and understanding how to use and derive value from accessed data ( [[#Chatuphale--2018|Chatuphale and Armstrong, 2018]] ; [[#Drewry--2019|Drewry et al., 2019]] ). More work is needed to understand the factors that prevent farmers and fishers from benefitting from this new information. Recent assessments suggest that access to, and value of, climate and weather information can be enhanced by the development of digital tools (including radio, text messages, etc.) appropriate to the specific needs of different vulnerable groups, as well as by including these groups in their development and building their capacity ( ''medium confidence'' ) ( [[#Camacho--2019|Camacho and Conover, 2019]] ; [[#Gumucio--2020|Gumucio et al., 2020]] ; [[#Sultan--2020|Sultan et al., 2020]] ).

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<span id="insurance-as-a-climate-impact-risk-management-tool"></span>
==== 5.14.1.3 Insurance as a climate impact risk management tool ====

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Insurance is a financial adaptation strategy increasingly used in agriculture and aquaculture. A relatively new approach to agricultural insurance risk is the use of financial derivative products, such as index-based agricultural insurance (IBAI), marketed by financial institutions to farmers to help them deal with weather-related production risks ( [[#Isakson--2015|Isakson, 2015]] ; [[#Jensen--2017|Jensen and Barrett, 2017]] ). The basic idea is to rely on easily observed weather indices, such as precipitation or temperature, that co-vary with farm production. Insurance payments are received when the metric trigger for a region is reached, eliminating the need to collect farm-specific information. Proponents of index insurance argue that it can resolve the information costs and incentive problems inherent in rural financial markets, such as adverse selection, and allow provision of insurance coverage at a fraction of the costs of loss-based polices ( [[#Jensen--2017|Jensen and Barrett, 2017]] ). Buyers of index policies do not have to prove their ownership of assets with weather-related losses. This lowers transactions costs and makes it more affordable to insure small plots of land.

The creation of index insurance requires significant prior research and extensive data that may not be available or sufficient in lower-income countries, including identifying the most appropriate farm and climate variables to include and financial and regulatory support from the public sector ( [[#Economic%20Commission%20for%20Latin%20America%20and%20the%20Caribbean%20and%20Central%20American%20Agricultural%20Council%20of%20the%20Central%20American%20Integration%20System--2013|Economic Commission for Latin America and the Caribbean and Central American Agricultural Council of the Central American Integration System, 2013]] ; Economic Commission for Latin America and the Caribbean and System, 2014). Some insurance providers bundle it with other services, such as fertilizer use or seeds that may not be useful to particular farmers and can increase their overall capital costs ( [[#Isakson--2015|Isakson, 2015]] ). Although proponents see IBAI as a way to mitigate farmers’ risks associated with more variable weather patterns ( [[#Greatrex--2015|Greatrex et al., 2015]] ), critics argue that derivative-based insurance products tend to benefit wealthier farmers and fail in assisting the poorest and most marginalised farmers ( [[#Isakson--2015|Isakson, 2015]] ; [[#Taylor--2016|Taylor, 2016]] ). Thus far, there is ''low agreement'' and ''medium evidence'' regarding the adaptation potential of derivatives-based insurance products, signalling a need for further research in this area.

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<span id="community-based-adaptation-approaches"></span>
==== 5.14.1.4 Community-based adaptation approaches ====

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Community-based adaptation (CbA) strategies, which involve locally driven, place-based adaptation approaches, can help build adaptive capacity to climate change impacts, but require explicit attention to power dynamics, respect for local and Indigenous knowledge systems, adequate resources, future climatic trends and coordination at multiple levels of governance to be effective ( ''high confidence'' ) ( [[#Spires--2014|Spires et al., 2014]] ; [[#Fernández-Giménez--2015|Fernández-Giménez et al., 2015]] ; [[#Nagoda--2015|Nagoda, 2015]] ; [[#Ashley--2016|Ashley et al., 2016]] ; [[#Berner--2016|Berner et al., 2016]] ; [[#Ensor--2016|Ensor et al., 2016]] ; [[#Avtar--2019|Avtar et al., 2019]] ; [[#Lam--2019|Lam et al., 2019]] ; [[#Silwal--2019|Silwal et al., 2019]] ; [[#McNamara--2020|McNamara et al., 2020]] ; [[#Piggott-McKellar--2020|Piggott-McKellar et al., 2020]] ; Rossa, 2020; [[#Uchiyama--2020|Uchiyama et al., 2020]] ). Since AR5, there is strong evidence that participation of local stakeholders in adaptation planning and implementation improves communities’ capacity to monitor and respond to climate change impacts on food, fibre and forestry systems, provided that adequate resources and local knowledge on climate change exist. Participatory monitoring of climate change impacts and participatory scenario development to develop community action plans are examples, which can help strengthen community preparation for and response to climate impacts.

Community-based monitoring of forests, coral reefs, seagrass and mangroves are examples of local natural resource assessment that can support food security and livelihoods while informing regional and national climate change planning tools ( [[#Carter--2014|Carter et al., 2014]] ; [[#Gevaña--2018|Gevaña et al., 2018]] ; [[#Avtar--2019|Avtar et al., 2019]] ). Negotiation among many stakeholders at multiple scales, including inclusive mechanisms to address power inequities in governance structures and communities, may be needed for CbA to be effective ( [[#Avtar--2019|Avtar et al., 2019]] ; [[#McNamara--2020|McNamara et al., 2020]] ). Indigenous knowledge and community-based management of fisheries and aquaculture in the Arctic and Asia ( [[#Roux--2019|Roux et al., 2019]] ; [[#Chen--2020|Chen and Cheng, 2020]] ; [[#Galappaththi--2020a|Galappaththi et al., 2020a]] ; [[#Schott--2020|Schott et al., 2020]] ; [[#Galappaththi--2021|Galappaththi et al., 2021]] ) provide adaptive strategies for sustainable use. ( [[#Iticha--2019|Iticha and Husen, 2019]] ). Community-based climate services in the Andes (managed through a collaboration of smallholder producers and an international partnership) built capacity and knowledge of climate change dynamics as well as trust in local climate institutions, providing meaningful information for regional responses to climate change impacts (Rossa, 2020). Community-based participatory scenario planning can help identify multiple climate stressors and vulnerabilities to develop effective adaptation plans ( [[#Fernández-Giménez--2015|Fernández-Giménez et al., 2015]] ; [[#Bennett--2016|Bennett et al., 2016]] ; Cross-Chapter Box MOVING PLATE this chapter).

An assessment of 32 different CbA initiatives in the Pacific Islands, including addressing risks to food security, found high-performing projects had six key entry points: effective methods to improve adaptive capacity, appropriate to the local context, which moved beyond narrow geographical definitions of community to consider equity of impact, and ecosystem-based approaches, jointly addressing climatic and non-livelihood pressures and consideration of future climatic trends ( [[#McNamara--2020|McNamara et al., 2020]] ). Low-performing initiatives, in contrast, were not sustained; these overlooked future climatic trends in their initiatives, such as beehive susceptibility to climate extremes, and had dependent, unequal relationships that lacked genuine local approval or ownership and did not fit local values and context ( [[#Spires--2014|Spires et al., 2014]] ; [[#McNamara--2020|McNamara et al., 2020]] ; [[#Piggott-McKellar--2020|Piggott-McKellar et al., 2020]] ). CbA initiatives can also suffer from not having adequate local knowledge of potential strategies to address future climatic scenarios, and may lead to maladaptation, increasing socioeconomic inequities in communities ( [[#Nagoda--2015|Nagoda, 2015]] ). Addressing inequity in power dynamics and building technical adaptive capacity of local people are some of the ways that CbA initiatives can support more resilient food systems ( [[#McNamara--2020|McNamara et al., 2020]] ).

<div id="5.14.1.5" class="h3-container"></div>

<span id="local-and-regional-food-systems-strengthening-and-food-sovereignty"></span>
==== 5.14.1.5 Local and regional food systems’ strengthening and food sovereignty ====

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Food sovereignty brings together adaptation options based on agroecological methods, access to resources, collective and CbA ( [[#HLPE--2019|HLPE, 2019]] ). Addressing food security and nutrition in light of climate change impacts and vulnerabilities is considered to arise from a mixture of globalised supply chains and local production, not one or the other ( [[#Blesh--2019|Blesh et al., 2019]] ; [[#Stringer--2020|Stringer et al., 2020]] ). Evidence on strengthening local and regional food systems with a food sovereignty approach, in terms of access to resources (land, seeds, water), shortened food chains and CbA strategies suggest that these strategies can positively contribute to climate change adaptation in many contexts ( ''medium confidence'' ) (SRCCL) but can also lead to conflict especially regarding management of mobile resources such as fisheries ( [[#5.8|Section 5.8]] , Cross-Chapter Box MOVING PLATE this chapter). All these options can build adaptation through actions that strengthen local capacities and the power to act within food systems. Securing and recognising tenure for Indigenous Peoples ( [[#Hurlbert--2019|Hurlbert et al., 2019]] ) and local communities ( [[#Oates--2020|Oates et al., 2020]] ) can improve their ability to adapt by increasing the incentive to invest in resilient infrastructure and sustainable land management practices. Community seed banks and networks strengthen local seed systems and realise farmers’ rights favouring access to a variety of local genetic resources, with landraces often more adapted to the local social, cultural and ecological environment and needs, and better adapted to harsh environments without external inputs ( [[#Mousseau--2015|Mousseau, 2015]] ; [[#Bisht--2018|Bisht et al., 2018]] ; [[#Maharjan--2018|Maharjan and Maharjan, 2018]] ; [[#Otieno--2018|Otieno et al., 2018]] ; [[#Mbow--2019|Mbow et al., 2019]] ). This plays a key role in PPB ( [[#5.4.4|Section 5.4.4.5]] ; [[#FAO--2019e|FAO, 2019e]] ). The integration of informal and formal seed system elements is important for the adaptive capacity of smallholder farmers (Westengen and Brysting, 2014; [[#Westengen--2016|Westengen and Berg, 2016]] ; [[#FAO--2019e|FAO, 2019e]] ).

Strengthening both local and regional food systems is a strategy to increase resilience ( [[#Schipanski--2016|Schipanski et al., 2016]] ; [[#Palmer--2017|Palmer et al., 2017]] ), resource use efficiency ( [[#Mu--2019|Mu et al., 2019]] ) and self-reliance ( ''medium evidence'' , ''low agreement'' ) ( [[#Griffin--2015|Griffin et al., 2015]] ; [[#Chapin--2016|Chapin et al., 2016]] ; [[#Karg--2016|Karg et al., 2016]] ). Collective trademarks ( [[#Quiñones-Ruiz--2015|Quiñones-Ruiz et al., 2015]] ) and participatory guarantee systems ( [[#Niederle--2020|Niederle et al., 2020]] ) are examples of innovative institutional strategies to strengthen local and regional food systems. In the urban context, the city region food system (CRFS) approach is motivated by reducing dependence on international trade and associated instability and to facilitate local decision making ( [[#Karg--2016|Karg et al., 2016]] ). CRFS includes a network within a regional landscape around one urban centre and surrounding peri-urban and rural regions ( [[#Blay-Palmer--2018|Blay-Palmer et al., 2018]] ). UPA is promoted as an effective strategy to adapt to climate change in different contexts (see [[#5.12.5|Section 5.12.5.3]] , [[#Dubbeling--2015|Dubbeling, 2015]] ; [[#Lwasa--2015|Lwasa et al., 2015]] ). To cope with the effects of climate change, strengthening regional food systems is becoming an explicit part of urban and regional policy, being tested in many different cities worldwide ( [[#Dubbeling--2017|Dubbeling et al., 2017]] ; [[#Blay-Palmer--2018|Blay-Palmer et al., 2018]] ; [[#Berner--2019|Berner et al., 2019]] ; [[#Sellberg--2020|Sellberg et al., 2020]] ; [[#van%20der%20Gaast--2020|van der Gaast et al., 2020]] ). Strengthening both local and regional food systems has to be balanced against limitations and trade-offs, since modelling exercises of regionalisation scenarios show urban agriculture cannot achieve food security in areas with rapid population growth ( [[#Le%20Mouël--2018|Le Mouël et al., 2018]] ). Furthermore, international trade can compensate in cases where the regional system fails due to extreme events or other related climate shocks ( [[#5.11|Section 5.11.8]] ).

<div id="box-5.11:-agroecology-as-a-transformative-climate-change-adaptation-approach" class="h2-container box-container"></div>

'''Box 5.11: Agroecology as a Transformative Climate Change Adaptation Approach'''
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Agroecological approaches can increase food system resilience ( ''robust evidence'' , ''medium agreement'' ), while some agroecological practices such as agroforestry can provide mitigation measures ( ''medium confidence'' ) ( [[#5.10.4.2|Section 5.10.4.2]] , Table Box 5.11.1, [[#Altieri--2015|Altieri et al., 2015]] ; [[#Martin--2016|Martin and Willaume, 2016]] ; [[#HLPE--2019|HLPE, 2019]] ; [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ; [[#Snapp--2021|Snapp et al., 2021]] ). Studies testing agroecological approaches have shown ''robust evidence'' , ''medium agreement'' of increasing adaptation effectiveness through reducing risk, improving food security and yield stability, reducing input costs, and other supporting and provisioning ecosystem services ( [[#5.4.4.4|Section 5.4.4.4]] [[#Diacono--2017|Diacono et al., 2017]] ; [[#Pandey--2017|Pandey et al., 2017]] ; [[#Schulte--2017|Schulte et al., 2017]] ; Calderón, 2018; [[#Bezner%20Kerr--2019|Bezner Kerr et al., 2019]] ; [[#Côte--2019|Côte et al., 2019]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ; [[#Snapp--2021|Snapp et al., 2021]] ). Effective locally relevant agroecological approaches involve participatory processes, co-creation of knowledge with farmers and attention to social inequities ( [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ; [[#Santoso--2021|Santoso et al., 2021]] ; [[#Snapp--2021|Snapp et al., 2021]] ). To address smallholder vulnerability to climate change impacts, however, additional policy support beyond agroecology will be needed that is context specific; for example, addressing farmer capacity, limited political power to access land, water, seeds and other key natural resources, structural gender inequities, policy and market disincentives that support large-scale monocultures ( ''high confidence'' ) ( [[#Anderson--2019a|Anderson et al., 2019a]] ; [[#HLPE--2019|HLPE, 2019]] ; [[#Holt-Giménez--2021|Holt-Giménez et al., 2021]] ; [[#Snapp--2021|Snapp et al., 2021]] ).

'''Table Box 5.11.1 |''' Dimensions of agroecological transitions as a transformative climate change adaptation strategy, benefits, trade-offs and constraints to implementation.

{| class="wikitable"
|-
! '''Different dimensions of agroecological transitions as a transformative climate change adaptation strategy'''

! '''Links to climate change impacts, benefits, trade-offs and constraints to implementation with examples'''

|-
| ''Environmental'' : Agroecology can support long-term productivity and resilience of food systems by sustaining ecosystem services such as pollination, SOC, pest and weed control, soil microbial activity, crop yield stability, water quality and biodiversity ( ''high confidence'' , see [[#5.4.4.4|Section 5.4.4.4]] , Cross-Working Group Box BIOECONOMY this chapter and Cross-Chapter Box NATURAL in Chapter 2). ( [[#Isbell--2017|Isbell et al., 2017]] ; [[#Kremen--2018|Kremen and Merenlender, 2018]] ; [[#LaCanne--2018|LaCanne and Lundgren, 2018]] ; [[#Beillouin--2019b|Beillouin et al., 2019b]] ; [[#Dainese--2019|Dainese et al., 2019]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Snapp--2021|Snapp et al., 2021]] ).

| * Biodiversity of functional species groups and responses to climate hazards play an important role in building stability and productivity in agroecological systems (5.4.4.4). A 5-year study, for example, in Asia, Africa and Latin America found that smallholder farmers (&lt;2 ha) increased yields by 25% through promoting pollination ( [[#Garibaldi--2016|Garibaldi et al., 2016]] ).
* Landscape complexity is an important feature of agroecology which can increase resilience to extreme events, such as pest and disease outbreaks or floods, and provide multi-purpose benefits (Sections 5.4.4; 5.10.4.2) ( [[#Paolotti--2016|Paolotti et al., 2016]] ; [[#Reed--2016|Reed et al., 2016]] ; [[#Kremen--2018|Kremen and Merenlender, 2018]] ; [[#LaCanne--2018|LaCanne and Lundgren, 2018]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Holt-Giménez--2021|Holt-Giménez et al., 2021]] ).
* Context-specific: some agroecological systems and practices have lower average crop productivity than conventional systems, while others can have higher overall crop productivity and farm profitability ( [[#LaCanne--2018|LaCanne and Lundgren, 2018]] ; [[#Barbieri--2019|Barbieri et al., 2019]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ).

|-
| ''Socio-cultural'' : Effective locally relevant agroecological approaches involve participatory processes, co-creation of knowledge with farmers and attention to social inequities, in doing so building farmer capacity ( [[#HLPE--2019|HLPE, 2019]] ; [[#Bharucha--2020|Bharucha et al., 2020]] ; [[#Holt-Giménez--2021|Holt-Giménez et al., 2021]] ; [[#Snapp--2021|Snapp et al., 2021]] ).

| * Agroecology can emphasise social justice concerns, including gender inequities, considered crucial for climate change adaptations in food production to have positive impacts on food security and nutrition (Cross-Chapter Box GENDER in Chapter 18; ( [[#Smith--2015|Smith and Haddad, 2015]] ; [[#HLPE--2019|HLPE, 2019]] ; [[#Sylvester--2020|Sylvester and Little, 2020]] ).
* In some contexts, agroecological systems can draw on and support Indigenous knowledge, farming systems, networks and socio-cultural values ( [[#Catacora-Vargas--2017|Catacora-Vargas et al., 2017]] ).

|-
| ''Food security and nutrition'' : Agroecological practices can increase household food security and nutrition for producer households, with more evidence in low- and medium-income countries ( ''high confidence'' ) (Darrouzet-Nardi, 2016; [[#Demeke--2017|Demeke et al., 2017]] ; [[#Jones--2017a|Jones, 2017a]] ; [[#Kangmennaang--2017|Kangmennaang et al., 2017]] ; [[#Pandey--2017|Pandey et al., 2017]] ; [[#Luna-Gonzalez--2018|Luna-Gonzalez and Sorensen, 2018]] ; [[#Bezner%20Kerr--2019|Bezner Kerr et al., 2019]] ; [[#Boedecker--2019|Boedecker et al., 2019]] ; [[#Mulwa--2020|Mulwa and Visser, 2020]] ; [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ; [[#Santoso--2021|Santoso et al., 2021]] ).

| * Combinations of practices, such as intercropping, crop rotation and crop diversification, often outperform individual practices for yield and food security outcomes ( [[#Beillouin--2019b|Beillouin et al., 2019b]] ; [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ).
* Agroecological systems more effectively support food security and nutrition when complemented by nutrition and health education, participatory research and other public policies and programmes which address access to knowledge ( ''high confidence;'' ( [[#HLPE--2019|HLPE, 2019]] ; [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ; 7.4).

|-
| ''Economic'' : Agroecology can support socioeconomic resilience, through reducing reliance on purchased inputs, enhancing local and regional economies ( [[#HLPE--2019|HLPE, 2019]] ; [[#Bharucha--2020|Bharucha et al., 2020]] ; [[#Holt-Giménez--2021|Holt-Giménez et al., 2021]] ).

| * Multi-level policies and programmes that support urban and peri-urban networks with agroecological producers, including farmers’ markets, public procurement (e.g., school meals, hospitals), incentives for short food value chains, and participatory guarantee certification schemes which build producer–consumer networks are all ways to support agroecological transitions by consumers ( ''high confidence'' ) ( [[#Catacora-Vargas--2017|Catacora-Vargas et al., 2017]] ; [[#Pérez-Marin--2017|Pérez-Marin et al., 2017]] ; Mier y Terán Giménez [[#Cacho--2018|Cacho et al., 2018]] ; [[#Anderson--2019a|Anderson et al., 2019a]] ; [[#HLPE--2019|HLPE, 2019]] ; [[#Borsatto--2020|Borsatto et al., 2020]] ; [[#González%20de%20Molina--2020|González de Molina, 2020]] ).
* Transitions to agroecology at a global scale, however, may require considerable dietary shifts which vary by region, and have implications for total food production and farm-level revenues, especially in the short term (medium confidence, ( [[#Muller--2017|Muller et al., 2017]] ; [[#Seufert--2017|Seufert and Ramakutty, 2017]] ; [[#Barbieri--2019|Barbieri et al., 2019]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Smith--2019b|Smith et al., 2019b]] ; [[#Smith--2020a|Smith et al., 2020a]] ).
* To address smallholder vulnerability to climate change impacts, additional policy support beyond agroecology will be needed that is context specific; for example, addressing farmer capacity, limited political power to access land, water, seeds and other key natural resources, structural gender inequities, policy and market disincentives that support large-scale monocultures ( [[#Anderson--2019a|Anderson et al., 2019a]] ; [[#Holt-Giménez--2021|Holt-Giménez et al., 2021]] ; [[#Snapp--2021|Snapp et al., 2021]] ).

|-
| ''Long-term investment'' : Timeframes are an important consideration, as an agroecological transition involves multiple overlapping stages, of reducing chemical inputs, experimenting with and applying new agroecological practices and adjusting them, redesigning the farm, strengthening short value chains and producer networks ( [[#Gliessman--2014|Gliessman, 2014]] ; [[#Padel--2020|Padel et al., 2020]] ).

| * In the short term, without policy support, the costs of implementing agroecological practices at the farm scale can outweigh ecological and adaptation benefits, although the timeframe required is context-specific ( [[#Padel--2020|Padel et al., 2020]] ).
* In the long term, implementing agroecological practices can increase yields, yield stability and farm profitability, reduce risks, and build resilience alongside ecological, health and social co-benefits, but impacts are context-specific ( [[#5.4.4.4|Section 5.4.4.4]] , [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ; [[#Snapp--2021|Snapp et al., 2021]] ).
* In Malawi, for example, studies indicate that smallholder producers using agroecological practices improved food security and nutrition, livelihoods and provisioning ecosystem services after 2 years ( [[#Kangmennaang--2017|Kangmennaang et al., 2017]] ; [[#Bezner%20Kerr--2019|Bezner Kerr et al., 2019]] ; [[#Kansanga--2021|Kansanga et al., 2021]] ), while in the UK, farmers transitioning to agroecological practices took 3 or more years to realise benefits ( [[#Padel--2020|Padel et al., 2020]] ).

|-
| ''Policy tools'' : Investment in agroecological approaches that are designed for socio-ecological context, farmer-led schools, co-learning platforms, and networks of farmers, scientists, private sector and civil society can support agroecological transitions at a regional scale ( ''high confidence'' ) ( [[#Coe--2014|Coe et al., 2014]] ; [[#Catacora-Vargas--2017|Catacora-Vargas et al., 2017]] ; [[#Pérez-Marin--2017|Pérez-Marin et al., 2017]] ; Mier y Terán Giménez [[#Cacho--2018|Cacho et al., 2018]] ; [[#Anderson--2019a|Anderson et al., 2019a]] ; [[#González%20de%20Molina--2020|González de Molina, 2020]] ; [[#Lampkin--2020|Lampkin et al., 2020]] ; [[#Padel--2020|Padel et al., 2020]] ; [[#Snapp--2021|Snapp et al., 2021]] ). Policies can provide incentives (e.g., price premiums, access to credit, extension service, taxes, regulation) to support agroecological transitions by producers ( [[#HLPE--2019|HLPE, 2019]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Gerard--2020|Gerard et al., 2020]] ; [[#SAPEA--2020|SAPEA, 2020]] ).

| * Farm scale and landscape diversity can affect the capacity for producers to implement agroecological systems. Small to mid-sized farms can more effectively integrate agroecological methods such as increasing landscape diversity, on-farm diversity and intercrops ( ''medium confidence)'' ( [[#Garibaldi--2016|Garibaldi et al., 2016]] ; [[#Herrero--2017|Herrero et al., 2017]] ; [[#HLPE--2019|HLPE, 2019]] ). Barriers to adopting agroecological practices for small to mid-sized farms include limited market options, subsidy and policy disincentives, lack of extension support, knowledge and insecure land tenure ( [[#Jacobi--2017|Jacobi et al., 2017]] ; [[#Kongsager--2017|Kongsager, 2017]] ; [[#Hernández-Morcillo--2018|Hernández-Morcillo et al., 2018]] ; [[#Iiyama--2018|Iiyama et al., 2018]] ; [[#Anderson--2019a|Anderson et al., 2019a]] ; [[#Gerard--2020|Gerard et al., 2020]] ).
* Barriers for large farms to transition to agroecological practices include knowledge gaps, cost, significant infrastructure and farm design changes, labour, psycho-social adjustments, policy disincentives and market lock-ins ( [[#Hill--2014|Hill, 2014]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Lampkin--2020|Lampkin et al., 2020]] ).
* Some policies and initiatives support large-sized farms to transition to agroecology ( [[#Zhou--2014|Zhou et al., 2014]] ; [[#Liebman--2015|Liebman and Schulte, 2015]] ; [[#Ajates%20Gonzalez--2018|Ajates Gonzalez et al., 2018]] ; [[#Bellon--2018|Bellon and Ollivier, 2018]] ; [[#Lampkin--2020|Lampkin et al., 2020]] ; [[#Padel--2020|Padel et al., 2020]] ).

|-
| Other drivers of agroecological transitions can include crises (environmental, economic or social), social movements, changing socio-cultural values, addressing social inequities, and discourse ( [[#Pérez-Marin--2017|Pérez-Marin et al., 2017]] ; Mier y Terán Giménez [[#Cacho--2018|Cacho et al., 2018]] ; [[#Anderson--2019a|Anderson et al., 2019a]] ).

| Further research could provide context-specific information about economic and ecological benefits of some practices and combinations, with effective policies to support their implementation ( ''high confidence'' ) ( [[#HLPE--2019|HLPE, 2019]] ; [[#Rosa-Schleich--2019|Rosa-Schleich et al., 2019]] ; [[#Snapp--2021|Snapp et al., 2021]] ). Institutional support to monitor the ecosystem services climate change mitigation and adaptation impact of agroecological systems can inform policy, using systematic methods and indicators (e.g., [[#Barrios--2020|Barrios et al., 2020]] ; [[#Mottet--2020|Mottet et al., 2020]] ) including annual reporting to the United Nations Framework Convention on Climate Change (UNFCCC) ( [[#Snapp--2021|Snapp et al., 2021]] ).

|}

Box 5.11

Box 5.11

<div id="5.14.2" class="h2-container"></div>

<span id="enabling-conditions-for-implementing-adaptation"></span>
=== 5.14.2 Enabling Conditions for Implementing Adaptation ===

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<div id="5.14.2.1" class="h3-container"></div>

<span id="addressing-social-inequities-in-food-systems"></span>
==== 5.14.2.1 Addressing social inequities in food systems ====

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Addressing gender and other social inequities (e.g., racial, ethnicity, age, income, geographic location) in markets, governance and control over resources is a key enabling condition for climate-resilient transitions in land and aquatic ecosystems ( ''high confidence'' ) ( [[#Pearse--2017|Pearse, 2017]] ; [[#Vermeulen--2018|Vermeulen et al., 2018]] ; [[#Blesh--2019|Blesh et al., 2019]] ; [[#Rao--2019b|Rao et al., 2019b]] ; Cross-Chapter Box GENDER in Chapter 18, Section 5,13,1; [[#Tavenner--2019|Tavenner et al., 2019]] ). Adaptation strategies can have negative impacts on marginalised social groups and worsen socioeconomic inequities unless explicit efforts are made to address unequal power dynamics and differences in access to resources in agricultural, fisheries, aquaculture, livestock and forestry systems ( ''high confidence'' ) ( [[#Glemarec--2017|Glemarec, 2017]] ; [[#Haji--2017|Haji and Legesse, 2017]] ; [[#Nagoda--2017|Nagoda and]] [[#Nightingale--2017|Nightingale, 2017]] ; [[#Nightingale--2017|Nightingale, 2017]] ; [[#Rao--2019b|Rao et al., 2019b]] ; [[#Huyer--2020|Huyer and Partey, 2020]] ; [[#Mikulewicz--2020|Mikulewicz, 2020]] ; [[#Taylor--2020|Taylor and Bhasme, 2020]] ; [[#Eriksen--2021|Eriksen et al., 2021]] ). Technical approaches to adaptation that ignore inequities can worsen them; see, for example, the case study on Climate Smart Agriculture (Box 5.12). Enabling environments support inclusive decision making, capacity building, shifts in social rules, norms and behaviours and access to resources for marginalised groups for climate change adaptation (e.g., [[#Tschakert--2016|Tschakert et al., 2016]] ; [[#Ziervogel--2019|Ziervogel, 2019]] ; [[#Eriksen--2021|Eriksen et al., 2021]] ; [[#Garcia--2021|Garcia et al., 2021]] ).

<div id="5.14.2.2" class="h3-container"></div>

<span id="incorporating-indigenous-knowledge-and-local-knowledge"></span>
==== 5.14.2.2 Incorporating Indigenous knowledge and local knowledge ====

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Indigenous knowledge (IK) and local knowledge (LK), while an important component of many adaptation strategies (Reyes-García, 2014; Roue, 2018), continues to be marginalised in food systems; greater integration will increase effectiveness ( ''high confidence'' ) ( [[#Ford--2015|Ford et al., 2015]] ; [[#Brugnach--2017|Brugnach et al., 2017]] ; [[#Figueroa-Helland--2018|Figueroa-Helland et al., 2018]] ). Where Indigenous Peoples have access to and control over their lands and natural resources, food systems can potentially be more sustainably managed and more resilient ( ''high confidence'' ) ( [[#Rumbach--2014|Rumbach and Foley, 2014]] ; O’Connell-Milne, 2015; [[#Camacho--2016|Camacho et al., 2016]] ; Janhiainen, 2017; [[#Kihila--2018|Kihila, 2018]] ). For example, on Solomon Islands, community-based adaptation combining with IK-informed community mapping helped boost agricultural yields sustainably ( [[#Leon--2015|Leon et al., 2015]] ), and in China people living in rich plant resource regions have used their wild plants IK to complement the decrease of crop yields during extreme droughts to ensure food security ( [[#Zhang--2016|Zhang et al., 2016]] ). These cases have led scientists and local communities to call for more practical actions to bridge local knowledge, IK and formal science ( [[#Borquez--2017|Borquez et al., 2017]] ; [[#Klenk--2017|Klenk et al., 2017]] ; Mukhopadhyay, 2017; Olorunfemi, 2017; [[#Reyes-Garcia--2019|Reyes-Garcia et al., 2019]] ). Despite this increased public and scientific recognition, IK is often not acknowledged or used.

Effective adaptation requires a more holistic approach that includes the recognition of Indigenous rights, governance systems and laws ( ''high confidence'' ) ( [[#Robinson--2016a|Robinson et al., 2016a]] ; [[#Brugnach--2017|Brugnach et al., 2017]] ; [[#Magni--2017|Magni, 2017]] ; [[#McMillen--2017|McMillen et al., 2017]] ; [[#McNeeley--2017|McNeeley, 2017]] ; [[#Pearce--2018|Pearce et al., 2018]] ), and to couple IK with proactive and regionally coherent adaptation plans, actions and cooperation ( [[#Shaffer--2014|Shaffer, 2014]] ; [[#Melvin--2017|Melvin et al., 2017]] ; Forbis Jr. and Hayhoe, 2018; [[#Makondo--2018|Makondo and Thomas, 2018]] ).

Supporting Indigenous groups’ knowledge and other excluded social groups can help preserve and harness underutilised resources to enhance nutritional and economic security, with careful measures in protecting Indigenous intellectual rights and avoiding commodification exploitation ( [[#Nakashima--2012|Nakashima et al., 2012]] ; [[#Nandal--2014|Nandal and Bhardwaj, 2014]] ; [[#Ghosh-Jerath--2015|Ghosh-Jerath et al., 2015]] ; [[#Ebert--2017|Ebert, 2017]] ). In some regions, there has been a loss of IK about food systems, reducing adaptive capacity ( [[#Richards--2019|Richards et al., 2019]] ; [[#Panikkar--2020|Panikkar and Lemmond, 2020]] ). Knowledge exchange between Indigenous elders and youth can support adaptive capacity ( [[#Osterhoudt--2018|Osterhoudt, 2018]] ; [[#Richards--2019|Richards et al., 2019]] ; [[#Zin--2019|Zin et al., 2019]] ). Education utilising IK and LK can help prevent maladaptation options ( ''high confidence'' ) ( [[#Melvin--2017|Melvin et al., 2017]] ; Taremwa, 2017; Forbis Jr. and Hayhoe, 2018; [[#Narayan--2020|Narayan et al., 2020]] ). There are examples of integrating IK and LK into resource management systems and school curricula and in local institutions with existing decision-making process to strengthen their capacity to address climate change ( [[#Huaman--2014|Huaman and Valdiviezo, 2014]] ; [[#McNamara--2014|McNamara and Prasad, 2014]] ; [[#Abah--2015|Abah et al., 2015]] ; [[#Mistry--2016|Mistry and Berardi, 2016]] ; [[#Tschakert--2017|Tschakert et al., 2017]] ; [[#McNeeley--2018|McNeeley et al., 2018]] ; [[#McNeeley--2020|McNeeley et al., 2020]] ). However, there are limitations of IK and LK to address future climate impacts. Therefore, it is important that science-based knowledge and other knowledge coalesce to produce solutions that are sustainable and viable in the face of projected impacts of climate change. Community-based adaptation approaches can integrate IK and LK and more formal knowledge systems, provided efforts to establish relationships of respect, trust and common understanding between different stakeholders involved ( [[#Herath--2015|Herath et al., 2015]] ; [[#Camacho--2016|Camacho et al., 2016]] ; [[#Fidelman--2017|Fidelman et al., 2017]] ; [[#Inaotombi--2019|Inaotombi and Mahanta, 2019]] ; [[#Lam--2019|Lam et al., 2019]] ).

<div id="5.14.2.3" class="h3-container"></div>

<span id="system-transformation-and-policy-enablers"></span>
==== 5.14.2.3 System transformation and policy enablers ====

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Recent literature highlights the future challenges of producing the quantities of food needed to feed a growing world population in a way that satisfies nutritional needs, benefits everyone equally and equitably, and minimises the negative impacts of food systems on the environment and the natural resource base. There is broad agreement that current trajectories towards the SDGs and countries’ commitments under the Paris Agreement are slow and that transformation of food systems is needed ( ''medium agreement'' , ''robust evidence'' ) ( [[#Campbell--2018|Campbell et al., 2018]] ; [[#Brondizio--2019|Brondizio et al., 2019]] ; [[#Dury--2019|Dury et al., 2019]] ; [[#EAT-LANCET--2019|EAT-LANCET, 2019]] ; FAO, 2019 f; [[#Food%20and%20Land%20Use%20Coalition--2019|Food and Land Use Coalition, 2019]] ; [[#Sachs--2019|Sachs et al., 2019]] ; Searchinger, 2019a; Searchinger T, 2019b; [[#Loboguerrero--2020|Loboguerrero et al., 2020]] ; [[#Meridian%20Institute--2020|Meridian Institute, 2020]] ; Steiner A, 2020).

Recent reviews have summarised literature on production system transformations, driven at least in part by a changing climate or changing climate variability. Such transformations may involve sometimes substantial shifts in farm and livelihood enterprises and land configurations, including intensification, diversification, sedentarisation and abandonment of agriculture ( [[#Vermeulen--2018|Vermeulen et al., 2018]] ; [[#Thornton--2019|Thornton et al., 2019]] ). Relevant literature is summarised in Table 5.24, showing reported farmers’ perceptions of the drivers of change and the different outcomes of these changes. The consequences of these production system transitions have been mixed; in about 40% of cases, the outcomes at household level have been unequivocally beneficial. In the other cases, there were detrimental effects on livelihoods, or a mixture of positive and negative effects. The effects on nutritional security reported in these studies were limited. Different enablers of change appear critical if transitions are to have positive outcomes. Policy environments, defined in terms of multi-level governance structures and institutions, are a key driver of systems change, as well as being enablers of and barriers to adaptation responses ( [[#Xu--2008|Xu et al., 2008]] ; [[#Namgay--2014|Namgay et al., 2014]] ; [[#Galvin--2015|Galvin et al., 2015]] ; [[#Schmidt--2016|Schmidt and Pearson, 2016]] ; [[#Liao--2017|Liao and Fei, 2017]] ). Policies around property and grazing rights are directly linked to small-scale food producer vulnerability, and land ownership changes will pose a key challenge as climate change impacts in the marginal lands intensify ( [[#Reid--2014|Reid et al., 2014]] ). Collective action at multiple scales and effective governance structures are also a key enabler of transformational change, for helping community initiatives overcome economic, social and technical barriers, and to strengthen social capital and farmer knowledge ( [[#Haglund--2011|Haglund et al., 2011]] ; [[#Reed--2017|Reed et al., 2017]] ; [[#Vermeulen--2018|Vermeulen et al., 2018]] ; [[#Fedele--2019|Fedele et al., 2019]] ). Market development has been shown to be a critical factor for successful adaptation at scale in sub-Saharan Africa ( [[#Ouédraogo--2017|Ouédraogo et al., 2017]] ; [[#Iiyama--2018|Iiyama et al., 2018]] ; [[#Totin--2018|Totin et al., 2018]] ). At the same time, financing mechanisms may be a crucial enabler for different food system actors: de-risking agricultural production and food system investments for producers and input suppliers, for example, that address core market failures and compensate actors for extra short-term costs that can lead to longer-term benefits, particularly for small-scale producers and businesses with comparatively low access to technologies and services ( [[#Vermeulen--2018|Vermeulen et al., 2018]] ; Millan, 2019; see [[#5.1|Section 5.1]] 4.2.5).

The examples in Table 5.24 highlight the uneven impact of adaptation programmes and projects in general, due in part to differences in institutional support and failure of policies to take into account inequities ( [[#Clay--2019|Clay and King, 2019]] ; [[#Nightingale--2020|Nightingale et al., 2020]] ). Focusing on transformational adaptation, Vermeulen (2018) suggested the need to expand the remit of adaptation planning to consider the multi-functionality of agriculture and a system-wide view of food production and consumption. Several authors argue that transformational change must address the personal, practical and political spheres, in view of the role of power relations and worldviews in shaping practices, food security and inequity (O’Brien, 2015; [[#Nightingale--2017|Nightingale, 2017]] ; [[#O’Brien--2018|O’Brien, 2018]] ; [[#Eriksen--2019|Eriksen et al., 2019]] ; [[#Gosnell--2019|Gosnell et al., 2019]] ). If it involves new or unfamiliar technology, transformation may also be highly disruptive, and the added vulnerabilities of food system actors at risk will need to be addressed ( [[#Herrero--2020|Herrero et al., 2020]] ; see Box 5.5).

'''Table 5.24 |''' Agricultural and livelihood system transformations from systematic searches of the literature, which are at least partially attributable to climatic factors and that involve increased or decreased system integration, and major consequences of the change. Information in the table is from the references cited. Sources: updated from ( [[#Vermeulen--2018|Vermeulen et al., 2018]] ; [[#Thornton--2019|Thornton et al., 2019]] ).

{| class="wikitable"
|-
! '''Underlying production system'''

! '''Primary drivers of change as stated'''

! '''Major processes of change as reported'''

! '''Consequences of change,''' '''if reported'''

! '''Reference'''

|-
| colspan="5"| '''''Extensive grassland-based systems'''''

|-
| Extensive grassland-based, northwest China

| Government policy, climate

| Sedentarisation

Diversification (crops, wages)

| Income decline, asset holding decline

| Liao and Fei, (2017)

|-
| Extensive grassland-based, Peruvian Andes

| Multiple climatic and non-climatic drivers

| Diversification (wages, livestock assets, land)

Extensification

| Livestock accumulation in wealthy households, asset diversification in poorer households

| López-i-Gelats et al., (2015)

|-
| Extensive grassland-based, Bhutan

| Government policy, labour constraints, climate

| Sedentarisation

Diversification (crops)

Exit

| Increased risk, loss of cultural identity, improved market access, livelihood ‘lock-in’ (inability to change rapidly)

| Namgay et al., (2014)

|-
| Extensive grassland-based, Borana, Ethiopia

| Increase in climate variability, resource degradation

| Livestock herd diversification (more small stock and camels, fewer cattle)

| Enhanced household resilience

| Megersa et al., (2014)

|-
| Extensive grassland-based, Tibetan Plateau

| Government policy, climate

| Sedentarisation

Diversification (crops, off-farm wages, trade)

| Increased food production, increased disease burden

| [[#Xu--2008|Xu et al. (2008)]]

|-
| Extensive grassland-based, Afar, Ethiopia

| Government policy, climate

| Sedentarisation

Diversification (crops)

| Weakened institutions and cultural practices, deteriorating natural resources

| [[#Schmidt--2016|Schmidt and Pearson (2016)]]

|-
| Extensive grassland-based, Kajiado, Kenya

| Government policy, climate, population growth

| Sedentarisation

Diversification (crops, wages, remittances)

Intensification

| Nutritional status remains poor

| [[#Galvin--2015|Galvin et al. (2015)]]

|-
| Extensive grassland-based, Mongolian Altai

| Government policy, climate

| Sedentarisation

Diversification (cashmere sales, forest products)

| Fodder shortages, forest over-use, unsustainable land use system

| [[#Lkhagvadorj--2013|Lkhagvadorj et al. (2013)]]

|-
| Extensive grassland based, Mongolia

| Increasing drought, grassland degradation

| Diversification (decreases in sheep and goats, increases in cattle, decreases in grain production, increases in fruit and vegetable production)

Exit from agriculture

| Increased household income from off-farm employment, more diverse diets

| [[#Du--2016|Du et al. (2016)]]

|-
| Extensive grassland-based, northern Kenya

| Climate change and variability

| Diversification (crops, wages, migration)

| Decreasing adaptive capacity, over-dependence on local knowledge for adaptation

| [[#Ogalleh--2012|Ogalleh et al. (2012)]]

|-
| colspan="5"| '''''Extensive systems with crops'''''

|-
| Extensive with crops, Eastern Cape, South Africa

| Multiple

| Intensification (richer households)

Exit and abandonment (poorer households)

Livelihood diversification

| Wildlife conflicts, loss of cultural identity

| [[#Shackleton--2013|Shackleton et al. (2013)]]

|-
| Extensive with crops, Peruvian highlands

| Economic globalisation, climate change

| Diversification (dairy production, wage migration)

Conversion (away from staple crops to feed production)

Intensification (feed production)

| Reduced vulnerability to climate change, but potential loss of both agrobiodiversity and food self-sufficiency identified by the author

| [[#Lennox--2015|Lennox (2015)]]

|-
| Extensive with crops, East Africa

| Climate

| Diversification (crops, livestock, wages)

Intensification (crops, intercrops)

| Increasing household vulnerability

| [[#Rufino--2013|Rufino et al. (2013)]]

|-
| Extensive with crops, Ghana

| Climate variability, temperature change

| Diversification (off-farm activities)

| Reduced vulnerability

| [[#Antwi-Agyei--2018|Antwi-Agyei et al. (2018)]]

|-
| Extensive smallholder cropping, Nepal

| Annual and seasonal warming. Increased precipitation with changes in patterns.

| Diversification and integration (from growing buckwheat and barley to vegetables and fruit trees)

| Increased household resilience due to diversification of production

| [[#Konchar--2015|Konchar et al. (2015)]]

|-
| Extensive smallholder mixed system, Niger

| Droughts and famines, and land degradation

| Large-scale regeneration of native trees and shrubs in the arable landscape

| Increased household income, effects on household food security not yet known

| [[#Haglund--2011|Haglund et al. (2011)]]

|-
| colspan="5"| '''''Other mixed coastal and forest systems'''''

|-
| Coastal rice-based, Bangladesh

| Increased salinity due to reduced dry season flows from rivers in India, use of groundwater for irrigation

| Diversification (from rice cultivation to aquaculture of shrimp and prawn)

| Increased household income, increased engagement of women, increased human disease vulnerability

| [[#Faruque--2017|Faruque et al. (2017)]]

|-
| Smallholder cropping systems, coastal Bangladesh

| Increasing frequency and severity of floods since 2008

| Diversification (re-allocation of land from crops to aquaculture)

Exit (migration away from village)

| Mixed impacts on household incomes and seasonal migration frequency

| Fenton et al. (2017)

|-
| Smallholder mixed cropping in forested landscapes in Indonesia

| Floods, drought, crop and livestock disease

| Diversification (re-allocation of land from forests to rubber plantations and rice)

Intensification (agroforestry)

Extensification (reforestation, forest protection)

| Locally, increased household incomes in general; more widely, some trade-offs with biodiversity, water, carbon stocks

| [[#Fedele--2018|Fedele et al. (2018)]]

|}

‘Transformation’, defined by [[#IPCC--2019a|IPCC (2019a)]] as ‘a change in the fundamental attributes of natural and human systems’, is defined here as a redistribution of at least a third in the primary factors of production (land, labour, capital) and/or the outputs and outcomes of production (the types and amounts of production and consumption of goods and services arising from multi-functional agricultural systems) ( [[#Vermeulen--2018|Vermeulen et al., 2018]] ; [[#Thornton--2019|Thornton et al., 2019]] ).

<div id="5.14.2.4" class="h3-container"></div>

<span id="finance-needs-and-strategies-for-adaptation"></span>
==== 5.14.2.4 Finance needs and strategies for adaptation ====

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Current understanding of finance flows and needs for adaptation in crop agriculture, livestock, fisheries, aquaculture and forest products relies primarily on top-down projections, with limited data ( [[#UNFCCC--2018|UNFCCC, 2018]] ; [[#Buchner--2019|Buchner et al., 2019]] ; [[#Jachnik--2019|Jachnik et al., 2019]] ). By one estimate, in 2017/2018, agriculture, forestry and land use received 24% of public adaptation finance (totaling USD 7 billion; half via multilateral development finance institutions and one-quarter from governments) and 35% of international grants (with 71% used for adaptation) ( [[#Buchner--2019|Buchner et al., 2019]] ). According to data from [[#OECD--2020|OECD (2020)]] , finance flows for agriculture, forestry and fisheries have risen fairly linearly from ca. USD 1.46 billion in 2010 (the year the Rio marker on climate change adaptation was introduced) to ca. 5.5 billion in 2018. Over the entire tracked period, the three subsectors combined received a total of USD 29.82 billion for activities with principal and significant adaptation components. [[#footnote-001|4]] However, the data set only includes climate-related development finance from bilateral, multilateral and private philanthropic sources, whereas private sector finance flows are not captured as this is notoriously difficult to track ( [[#UNEP--2016|UNEP, 2016]] ; [[#OECD--2020|OECD, 2020]] ; cross-ref to Cross-Chapter Box FINANCE in Chapter 17). Most of the funding (85%) was directed towards agriculture, with forestry (12%) and fisheries (3%) receiving significantly less, but across the subsectors, there is consistency in the sense that policy and administrative management and development receive the lion’s share of support, which is predominantly given in the form of grants (72%), while debt instruments (26%) and equity and shares in collective investment vehicles (2%) contribute less. From a regional perspective, 80% were directed to Africa (47%), Asia-Pacific (27%), and Latin America and Caribbean States (7%), whereas Eastern Europe and Western Europe and Other States received (2%) each and 17% were destined for ‘developing countries’ without regional tags. Finally, it is noteworthy that 38% of adaptation finance in agriculture, forestry and fisheries is marked as also having mitigation benefits, and roughly a quarter of funding is reported as having principal or significant gender objectives.

Whether current levels of growth in adaptation finance for agriculture, forestry and fisheries is keeping up with estimated needs cannot be assessed because of the large uncertainties that surround adaptation cost estimates (Cross-Chapter Box FINANCE in Chapter 17). There is, hence, high agreement that better assessment of adaptation costs of climate impacts requires considerably more research ( [[#Watkiss--2015|Watkiss, 2015]] ; [[#Diaz--2017|Diaz and Moore, 2017]] ). A recent study focusing on investments needed to offset the effects of climate change on the prevalence of hunger concludes that investments in agricultural research and development (R&amp;D) have to increase from USD 1.62 billion to USD 2.77 billion per year between 2015 and 2050 ( [[#Sulser--2021a|Sulser et al., 2021a]] ). In addition to agricultural R&amp;D, significant investment increases in water and infrastructure in the range of USD 12.7 billion and USD 10.8 billion are required, respectively, a considerable portion of which is relevant to the food system. In total, [[#Sulser--2021a|Sulser et al. (2021a)]] estimate that annual investment between USD 21.47 billion and USD 29.8 billion are needed to avoid sliding back from climate-change-related increases in the prevalence of hunger but recognise the shortcomings of their approach and acknowledge that ‘a full analysis of adaptation to climate change in agriculture would require including many other social, economic, and environmental dimensions’. For comparison, [[#World%20Bank--2010|World Bank (2010)]] estimated global costs of USD 70–100 billion per year for agriculture, forestry and fisheries, infrastructure, water resources, health, ecosystem services, coastal zones and extreme weather events to adapt to an approximately 2°C warmer world between 2010 and 2050. While the World Bank includes more sectors, more recent publications consider the resulting figures to be significantly too low ( [[#Baarsch--2015|Baarsch et al., 2015]] ; [[#UNEP--2016|UNEP, 2016]] ; Rossi and Miola, 2017; [[#Hallegatte--2018|Hallegatte et al., 2018]] ; [[#Markandya--2019|Markandya and González-Eguino, 2019]] ; [[#Chapagain--2020|Chapagain et al., 2020]] ; WGII Cross-Chapter Box FINANCE in Chapter 17). Therefore, despite the methodological and data challenges, further efforts are needed to better capture the economic risks of climate change and provide estimates of adaptation costs at global to national scales as well as across sectors ( [[#Watkiss--2015|Watkiss, 2015]] ; [[#Diaz--2017|Diaz and Moore, 2017]] ).

Financial barriers limit implementation of adaptation options in agriculture, fisheries, aquaculture and forestry ( ''high confidence'' ) ( [[#Shukla--2019|Shukla et al., 2019]] ; [[#FAO--2020|FAO et al., 2020]] ). Finance strategies can contribute to adaptation in these sectors in different ways (Table 5.25) and to different degrees. Standardised strategies have not yet been developed for specific adaptation needs, and in current practice, finance strategies are opportunistically deployed, with developing countries facing particular challenges due to under-developed financial mechanisms ( [[#Omari-Motsumi--2019|Omari-Motsumi et al., 2019]] ).

'''Table 5.25 |''' Potential adaptation finance strategies for categories of climate-related risks in the agriculture, fisheries, aquaculture and forestry sectors.

{| class="wikitable"
|-
! '''Finance strategies'''

! '''Reduced food availability'''

! '''Low food safety /''' '''dietary health'''

! '''Diminished livelihoods'''

! '''Declining ecosystem services'''

|-
| '''Reduce vulnerability'''

| ''Avoid staple failure'' : Vouchers to producers for improved production inputs

| ''Diversify production strategies'' : Invest in alternative crops/species/harvest methods

| ''Increase producer capacity'' : Fund technical assistance programmes

| ''Incentivise improved management'' : Improved access to credit based on environmental performance

|-
| '''Anticipate/minimise impacts'''

| ''Minimise impact of extreme weather'' : Fund early-warning systems

| ''Diversify products in supply chains'' : Finance processing equipment for alternative food products

| ''Moderate food price spikes'' : National food reserves

| ''Minimise resource depletion'' : Subsidise micro-lending for water-efficient technologies

|-
| '''Steer capital towards climate resilience'''

| ''Develop climate-resilient production technologies'' : Fund R&amp;D for improved genetics (crops, fish, livestock) and management

| ''Build nutrition-sensitive food systems'' : Finance early-stage market building for diversified food products

| ''Increase resilience of supply chain infrastructure'' : Finance improved storage and transport facilities

| ''Disincentivise low-resilience production:'' Screen investments based on climate risk disclosures

|-
| '''Pool climate-related risks'''

| ''Distribute climate-related risks:'' Securitise investments in production systems

| ''De-risk diversified food supply chains'' : Invest in producer aggregation to improve supply chain efficiency

| ''Insure against supply chain risks'' : Subsidised index insurance programmes

| ''Detect high-risk production systems'' : Invest in supply chain monitoring/traceability mechanisms

|-
| '''Compensate for climate-related impacts'''

| ''Compensate for production losses'' : Financial transfers to affected producers

| ''Avoid food shortages'' : Subsidise food importation

| ''Avoid selling off productive assets'' : Fund social support for low-income households

| ''Ecological restoration'' : Direct development aid to land rehabilitation projects

|}

Many types of financial instruments are employed by diverse actors (Table 5.26) guided by their mandates (e.g., development, commerce), capacity (investor, intermediary, donor) and risk appetite. Actors within a sector or local production area can coordinate their financial strategies towards common objectives (e.g., reduced supply chain loss) or participate in joint financial action such as blended finance structures that combine commercial and concessionary finance to catalyse additional private investment, enrich the pipeline of bankable projects, and test business models ( [[#FAO--2020b|FAO, 2020b]] ).

'''Table 5.26 |''' Potential adaptation finance objectives for major actors in agriculture, fisheries, aquaculture and forestry sectors.

{| class="wikitable"
|-
! '''Actors'''

! '''Potential adaptation finance objectives'''

|-
| colspan="2"| '''Private sector''' : Focused on capturing positive externalities (i.e., lower risks or costs) from adaptation investments ( [[#Woodard--2019|Woodard et al., 2019]] ). Major considerations include fiduciary responsibilities; expected rates of return (i.e., risk-adjusted; benchmarked to comparable investments); investment characteristics (e.g., liquidity, structure, size) and contribution to investor portfolio; material business risks (e.g., supply chain reliability; stranded assets); cost control (e.g., product losses; insurance); legal compliance; and sectoral requirements (e.g., climate risk disclosure) ( [[#Havemann--2020|Havemann et al., 2020]] ).

|-
| Production companies or cooperatives

| * Supply chain transactions (e.g., trade finance)
* Sustainable agricultural infrastructure (e.g., capital investment in storage or processing facilities to reduce exposure to climate risks)
* Developing or accessing advisory services (weather data; agronomic information) ( [[#Orchard--2019|Orchard, 2019]] )
* Risk management (e.g., insurance/reinsurance; budget reserves)

|-
| Financial investors and intermediaries (e.g., banks, asset managers, venture capital; non-bank financial institutions)

| * Ownership shares in established companies (i.e., private equity) or large publicly traded companies (i.e., listed equities)
* Debt issuance (e.g., working capital; catastrophe bonds; emergency loans)
* Real estate investment
* Financial derivatives
* Technological research and development
* (Impact investors) Bespoke non-financial sustainability objectives (e.g., fairtrade products; financial inclusion) ( [[#Havemann--2020|Havemann et al., 2020]] )

|-
| colspan="2"| '''Public sector''' : Encompassing nearly commercial (e.g., specialised commodity boards; bond issuances), partially subsidised (e.g., low-interest loans) and fully subsidised (e.g., R&amp;D; grants) investments. Major considerations include avoiding negative impacts to citizens (e.g., food price spikes) and specific constituencies (e.g., catastrophic losses to producers) and maintaining/enhancing public revenues (i.e., taxes from economic activity in agriculture, fisheries, aquaculture and forestry).

|-
| Government agencies and multilateral institutions

| * Strengthen enabling environments for sustainable production and ecosystem protection (e.g., price transparency; information exchange; international coordination)
* Support demonstration projects for sustainable land and resource management (e.g., grants)
* Disaster risk reduction (e.g., national disaster funds; social protection programmes; contingent credit lines; sovereign/sub-sovereign insurance ( [[#Global%20Commission%20on%20Adaptation--2019|Global Commission on Adaptation, 2019]] )
* Increase resilience through early-warning systems, infrastructure, and capacity building (e.g., climate change adaptation funds)
* Increase revenues for adaptation activities (e.g., income/luxury taxes)
* Reduce production risks (e.g., agricultural subsidies)
* Promote advanced technology implementation (e.g., tax incentives)
* Coordinate and align donor funding with national priorities (e.g., multi-donor national climate change funds)
* Incentivise and de-risk commercial investments (e.g., interest rate reduction programmes, structured financing, guarantee funds) ( [[#Woodard--2019|Woodard et al., 2019]] )

|}

Expanding access to financial services and pooling climate risks can enable and incentivise climate change adaptation ( ''medium confidence'' ) ( [[#Shukla--2019|Shukla et al., 2019]] ). To mobilise financial instruments (Table 5.27) towards adaptation needs, individual actors can apply an adaptation lens to existing or new activities, accounting for investment characteristics (e.g., development stage; cash flow profile), requirements (e.g., amount; risk–return) and context (e.g., regulatory landscape) ( [[#Havemann--2020|Havemann et al., 2020]] ). Risk-layering can match financial instruments to severity and probability climate risks ( [[#Hochrainer-Stigler--2021|Hochrainer-Stigler and Reiter, 2021]] ).

'''Table 5.27 |''' Major types of financial instruments suitable to adaptation finance in agriculture, fisheries, aquaculture and forestry sectors (adapted from [[#Havemann--2020|Havemann et al., 2020]] ).

{| class="wikitable"
|-
! '''Financial instrument'''

! '''Description'''

|-
| colspan="2"| '''Equity''' : Ownership stake in a company (e.g., agricultural technology company; processing company) or collective investment vehicle (e.g., agriculture fund; Timber Investment Management Organization; commodity index fund) providing returns (via dividends and/or sale of equity shares) corresponding to business-related risk (e.g., higher return for higher risk and/or lower liquidity)

|-
| Listed equities

| Ownership of shares in a company listed in a public market

|-
| Private equity

| Ownership of shares in a company or other assets

|-
| Junior or risk-absorbing equity

| Ownership of lower-tier shares in a company (e.g., common stock) or collective investment vehicle (e.g., first-loss tranche)

|-
| colspan="2"| '''Debt''' : Capital provided directly or indirectly (via banks or other third-party institutions) to users with defined repayment terms (i.e., timeframe, interest rate); more likely to deliver adaptation benefits when coupled with capacity building (e.g., technical assistance, education, analytics) ( [[#Woodard--2019|Woodard et al., 2019]] )

|-
| Loan, bond, note, credit line

| Direct or indirect provision of capital (e.g., operating loans; dedicated credit line for agricultural trade); concessionary loans may allow for below-market interest rates

|-
| Soft loan

| Direct interest-free loan (e.g., funds provided in advance of good/service delivery)

|-
| Emergency loan

| Lending in response to climate risks or impacts with repayment terms (e.g., return period) that consider necessary relief, recovery and reconstruction

|-
| Catastrophe bond

| Risk transfer instrument in which insurers or reinsurers provide high interest payments to investors in exchange for a payout (and repayment deferment or forgiveness) activated by specific events (e.g., extreme weather)

|-
| Impact bond

| Subsidised investment providing capital upfront or based on defined outcomes

|-
| Subordinated loan

| Concessionary capital with a junior position (i.e., accepting higher risk of non-repayment and / or lower rate of return on investment) relative to other investors

|-
| Securitised investments

| Aggregation of equity or debt to offer marketable securities to a wider pool of investors with different risk–return appetites

|-
| colspan="2"| '''Guarantees''' : Commercial and concessionary guarantees that provide compensation for losses due to specified risks (e.g., political risk, performance risk); more likely to deliver adaptation benefits when linked to robust underwriting standards and verification protocols ( [[#Woodard--2019|Woodard et al., 2019]] )

|-
| Credit guarantee

| Compensation for specified losses incurred by agricultural lenders

|-
| Payment, performance, surety bonds

| De-risking mechanism for transactions between providers and buyers of goods/services; may be used in trade finance and other forms of intermediation

|-
| colspan="2"| '''Insurance''' : Policies and other financial instruments that provide compensation for losses based on defined terms and conditions.

|-
| Production insurance

| Compensation for specified losses related to production (e.g., insurance indexed to specific weather events) or supply chains (e.g., shipping insurance)

|-
| Market and price insurance

| Compensation for specified market-related losses (e.g., price or currency fluctuation)

|-
| colspan="2"| '''Grants''' : Concessionary funding provided by public or philanthropic entities to support climate adaptation costs or outcomes (no expectation of repayment)

|-
| Direct support

| Funding for provision of goods (e.g., fertilizer, seeds, nursery stock) or services (e.g., technical assistance, product storage) to producers, local companies or intermediaries (e.g., for agronomic or business management expertise); can reduce credit risk when part of blended finance arrangements

|-
| Performance-based grants

| Grants or other concessionary funding contingent on achievement of defined adaptation outcomes (with possible third-party verification requirement); may support development and testing of new approaches (i.e., design funding; challenges/prizes)

|-
| colspan="2"| '''Governmental instruments'''

|-
| Policy incentives

| Public policies designed to stimulate adaptation action among targeted groups (e.g., producers, consumers, agri-businesses, financiers) including direct or indirect subsidies (e.g., producer payments, tax breaks, health insurance), procurement policies (e.g., low carbon and sustainability criteria; nutrition-sensitive school feeding programmes) and other fiscal measures (e.g., infrastructure development; funding R&amp;D in climate-resilient practices or technologies) ( [[#Shukla--2019|Shukla et al., 2019]] )

|-
| Development aid

| International or domestic programmes that directly or indirectly fund adaptation actions including financial transfers (e.g., producer support or anti-poverty programmes) and subsidised credit ( ''medium confidence'' ) ( [[#Shukla--2019|Shukla et al., 2019]] )

|-
| Planning grants

| Financial support to governments for adaptation planning (e.g., via readiness programmes)

|-
| colspan="2"| '''Other instruments'''

|-
| Fintech

| Data analytics and risk analysis models used to better assess borrowers’ repayment risk (e.g., due to crop failure) and reduce transaction costs (e.g., streamlined lending processes); applications may include financial inclusion (e.g., micro-financing; lending to small- and mid-size operators), alternative repayment programmes (e.g., for larger capital borrowing), insurance (e.g., more granular risk assessment) or digital strategies (e.g., crowdfunding, smallholder credit) ( [[#Agyekumhene--2018|Agyekumhene et al., 2018]] )

|-
| Payment for Ecosystem Services (PES)

| Funds delivered to land and resource managers in exchange for compliance with specified sustainability practices or environmental outcomes; PES depends on willing payers (i.e., direct and indirect beneficiaries of ecosystem services such as governments, companies, conservation groups, philanthropies)

|}

<div id="5.14.2.5" class="h3-container"></div>

<span id="constraints-on-adaptation-finance-for-food-feed-fibre-and-other-ecosystem-products"></span>
==== 5.14.2.5 Constraints on adaptation finance for food, feed, fibre and other ecosystem products ====

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Flow of adaptation finance in the agriculture, fisheries, aquaculture and forestry sectors is impeded by weak measurement and benchmarking of financial and resilience outcomes ( [[#Kramer--2019|Kramer et al., 2019]] ; [[#Negra--2020|Negra et al., 2020]] ), and challenges in assessing repayment capacity of investee producers and companies ( ''medium confidence'' ). Immature information systems (e.g., weak analytics, fragmented standards) ( [[#Woodard--2019|Woodard et al., 2019]] ; [[#Negra--2020|Negra et al., 2020]] ) inhibit effective due diligence and impact assessment, contributing to uncertainty and low investor confidence ( [[#Havemann--2020|Havemann et al., 2020]] ; [[#NGFS--2020|NGFS, 2020]] ). Improved characterisation of adaptation finance strategies (e.g., insurance, subsidies, blended finance) requires increased transaction volume ( [[#Millan--2019|Millan et al., 2019]] ) and analysis of financial (e.g., risk–return profile, investor demand) and resilience (e.g., reduced vulnerability) effects.

Use of climate-resilient financial strategies and instruments is limited by weak incentives, which commonly take the form of high upfront costs ( [[#Verdolini--2018|Verdolini et al., 2018]] ), high transaction and intermediation costs ( [[#Havemann--2020|Havemann et al., 2020]] ) and relatively long pay-off time. Tenant producers may not experience benefits from adaptation investments ( [[#Woodard--2019|Woodard et al., 2019]] ). Investors seek low-risk, liquid investments and credit-worthy counterparties ( [[#Havemann--2020|Havemann et al., 2020]] ), yet small- and medium-sized producers and supply chain actors often lack access to formal credit. Given limited experience and weak information for adaptation finance, sub-optimal outcomes may include imbalanced allocation of public and private finance (e.g., to less vulnerable regions and producers; to lower-resilience investments; to short-term benefits) as well as inequitable division of risks and returns (e.g., within blended finance structures) ( [[#Clapp--2017|Clapp, 2017]] ; [[#World%20Bank--2018|World Bank, 2018]] ; [[#Attridge--2019|Attridge and Engen, 2019]] ). Additionally, while risk-sharing finance strategies can deliver adaptation benefits, they do not inherently reduce overall risk and commonly cover only specified types of risks ( [[#Kellett--2014|Kellett and Peters, 2014]] ; [[#Watson--2015|Watson et al., 2015]] ).

Methods to strengthen adaptation finance include updating regulations and policies to support adaptation finance instruments (e.g., climate accounting standards), requiring climate-risk disclosure, improved information-sharing among public and private sector actors and devolving funding to local actors ( ''medium confidence'' ) ( [[#Global%20Commission%20on%20Adaptation--2019|Global Commission on Adaptation, 2019]] ; [[#Millan--2019|Millan et al., 2019]] ).

<div id="box-5.12:-is-climate-smart-agriculture-overlooking-gender-and-power-relations?" class="h2-container box-container"></div>

'''Box 5.12: Is Climate-Smart Agriculture Overlooking Gender and Power Relations?'''
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Climate-smart agriculture (CSA) is an approach that aims to increase agricultural productivity, enhance food security, adapt to climate change and, where possible, reduce GHG emissions. The effective implementation of climate-smart practices is conceptually linked to an enabling environment in which policies, institutions and finance can re-orient agricultural systems, thereby supporting development and enhancing food security in a changing climate ( [[#Lipper--2014|Lipper et al., 2014]] ; [[#Karttunen--2017|Karttunen et al., 2017]] ). However, the concept has received criticism based on the absence of conceptual clarity of the interrelations between productivity, food security, adaptation and mitigation ( [[#Arenas-Sanchez--2019|Arenas-Sanchez et al., 2019]] ) and because of limited evidence on the efficacy of CSA for achieving adaptation and mitigation outcomes at a global scale ( [[#Arslan--2015|Arslan et al., 2015]] ; [[#Lamanna--2016|Lamanna et al., 2016]] ; [[#Chandra--2018|Chandra et al., 2018]] ). Some argue that CSA operates within an apolitical framework that tends to minimise issues concerning power, inequity and access, and is overly focused on technical approaches ( [[#Taylor--2017|Taylor, 2017]] ; [[#HLPE--2019|HLPE, 2019]] ). CSA is explicitly referenced by more than 30 countries in their Intended Nationally Determined Contributions (INDCs) ( [[#Ross--2016|Ross et al., 2016]] ), but measuring the degree of its implementation still represents a challenge.

There is ''low agreement'' , ''medium evidence'' on the relationship between CSA and equity (Allen, 2018; [[#Karlsson--2018|Karlsson et al., 2018]] ). CSA can potentially benefit women if they are able to take advantage of improvements in productivity, food security and adaptation decision making as a result of the implementation of CSA practices. Nevertheless, these advantages can be unequally realised given male domination in receiving information and extension services, as well as financial or resource access ( [[#Jost--2016|Jost et al., 2016]] ). Some ( [[#Huyer--2020|Huyer and Partey, 2020]] ) argue that CSA may undermine gender equity ( [[#Collins--2018|Collins, 2018]] ), entrench and solidify power ( [[#Haapala--2018|Haapala, 2018]] ), and result in the disproportional allocation of new labour-intensive activities to women ( [[#Jost--2016|Jost et al., 2016]] ). Uptake of some climate-smart technologies can further marginalise the most disadvantaged local groups ( [[#Roncoli--2009|Roncoli et al., 2009]] ; [[#Haapala--2018|Haapala, 2018]] ). Unequal sharing of benefits and burdens with respect to emission reduction costs among different agricultural groups has also been observed ( [[#Budiman--2019|Budiman, 2019]] ).

In contrast, emerging research points to the potential of CSA as a supporting condition for gender equity, provided that equity and power concerns are explicitly included in the approach ( [[#Chanana-Nag--2020|Chanana-Nag and Aggarwal, 2020]] ). Some CSA technologies and practices, such as direct seeding, green manuring and laser land levelling, can have a significant role in reducing the gender gap in labour burden for women in agriculture ( [[#Khatri-Chhetri--2020|Khatri-Chhetri et al., 2020]] ). The use of participatory approaches can facilitate community-based adaptation of gender-sensitive CSA practices (Rosimo, 2018). CSA may also empower both men and women: in two villages in India, CSA adoption empowered both sexes in decision making and use and control of income ( [[#Hariharan--2018|Hariharan et al., 2018]] ).

In general CSA programmes have tended to overlook questions of inequity ( ''medium confidence'' ), including limited attention to social conditions that promote Business-As-Usual pathways, although this is now changing. Addressing questions of rights, social injustice, unequal power relations and inequity would help make CSA-related policy responses more effective in addressing vulnerability ( [[#Chandra--2017|Chandra et al., 2017]] ; [[#Clapp--2018|Clapp and Isakson, 2018]] ; [[#Karlsson--2018|Karlsson et al., 2018]] ; [[#Westengen--2018|Westengen et al., 2018]] ; [[#Ellis--2019|Ellis and Tschakert, 2019]] ; [[#Eriksen--2019|Eriksen et al., 2019]] ; [[#Westengen--2019|Westengen et al., 2019]] ).

<div id="box-5.13:-supporting-youth-adaptation-in-food-systems" class="h2-container box-container"></div>

'''Box 5.13: Supporting Youth Adaptation in Food Systems'''
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Young people are key agents in agrifood systems: both a vulnerable group, and one that can foster systemic change ( ''high confidence'' ) ( [[#Brooks--2019|Brooks et al., 2019]] ; Figure X; [[#IFAD--2019|IFAD, 2019]] ; [[#Flynn--2021|Flynn and Sumberg, 2021]] ; [[#HLPE--2021|HLPE, 2021]] ). Food systems are the largest source of employment for young people, but do not always provide adequate livelihoods or decent working conditions ( [[#HLPE--2021|HLPE, 2021]] ). Regions with more youthful populations—such as Sub-Saharan Africa, South Asia and Central America—are both highly vulnerable to climate change impacts and reliant on agriculture, forestry, aquaculture and fisheries for livelihoods ( [[#Brooks--2019|Brooks et al., 2019]] ; [[#IFAD--2019|IFAD, 2019]] ; [[#HLPE--2021|HLPE, 2021]] ). Rural youth in these sectors are particularly vulnerable, often with less access to land, water, capital and other resources, shaped by family and social relations, and fewer opportunities ( ''high confidence'' ) ( [[#Chingala--2017|Chingala et al., 2017]] ; [[#Ricker-Gilbert--2018|Ricker-Gilbert and Chamberlin, 2018]] ; [[#IFAD--2019|IFAD, 2019]] ; [[#Yeboah--2020|Yeboah et al., 2020]] ; [[#Flynn--2021|Flynn and Sumberg, 2021]] ; [[#Nhat%20Lam%20Duyen--2021|Nhat Lam Duyen, 2021]] ). In these vulnerable regions, climate change compounds other drivers such as poverty to increase youth out-migration to urban areas or other regions ( ''medium confidence'' ) ( [[#Zin--2019|Zin et al., 2019]] ; [[#Weinreb--2020|Weinreb et al., 2020]] ; [[#HLPE--2021|HLPE, 2021]] ; [[#Stoltz--2021|Stoltz et al., 2021]] ; [[#Voss--2021|Voss, 2021]] ), which can further worsen rural economies. Young low-income rural women may be particularly marginalised and vulnerable due to systemic gender inequities in access to land, credit, employment, institutions and other resources ( ''medium confidence'' ) ( [[#Sah%20Akwen--2017|Sah Akwen, 2017]] ; [[#IFAD--2019|IFAD, 2019]] ; [[#Flynn--2021|Flynn and Sumberg, 2021]] ).

Youth play a critical role in all sectors of the food system ( [[#HLPE--2021|HLPE, 2021]] ; Figure Box 5.13.1), and some are actively pursuing work and innovation in agrifood systems ( ''medium confidence'' ) ( [[#Sah%20Akwen--2017|Sah Akwen, 2017]] ; 2019; [[#Yeboah--2020|Yeboah et al., 2020]] ; [[#Flynn--2021|Flynn and Sumberg, 2021]] ). Climate change impacts may reduce youth employment options in food systems in some regions, while they are often politically marginalised ( [[#Brooks--2019|Brooks et al., 2019]] ; [[#IFAD--2019|IFAD, 2019]] ; [[#HLPE--2021|HLPE, 2021]] ). At the same time, due to heightened awareness about climate change, youth may be more willing to apply climate adaptation strategies ( ''medium confidence'' ) ( [[#Ali--2017|Ali and Erenstein, 2017]] ; [[#Jiri--2017|Jiri et al., 2017]] ; [[#Sah%20Akwen--2017|Sah Akwen, 2017]] ; [[#Chamberlin--2021|Chamberlin and Sumberg, 2021]] ; [[#Doherty--2021|Doherty et al., 2021]] ). Agrifood policy implementation of adaptation strategies could increase inclusive participation of youth to meet their needs ( [[#HLPE--2021|HLPE, 2021]] ). Inclusive investments in water management, infrastructure, agrifood science, and policies that increase youth access to land, credit, knowledge, education, skills and other crucial resources can support dignified and rewarding agrifood employment ( [[#Ahsan--2016|Ahsan and Mitra, 2016]] ; [[#Brooks--2019|Brooks et al., 2019]] ; [[#HLPE--2021|HLPE, 2021]] ). Digital technologies can support agrifood adaptations, but digital divides must be overcome to avoid worsening inequities ( [[#HLPE--2021|HLPE, 2021]] ). Initiatives which protect and strengthen youth engagement and employment in the all points of the food system, including recognition of youth’s critical role and agency through rights-based approaches, can support sustainable food transitions ( [[#HLPE--2021|HLPE, 2021]] ). Harnessing youth innovation and vision to address climate change alongside other SDGs such as gender inequity and rural poverty will be a crucial strategy to ensure resilient economies in food systems ( ''high confidence'' ) ( [[#Laube--2016|Laube, 2016]] ; [[#Brooks--2019|Brooks et al., 2019]] ; [[#IFAD--2019|IFAD, 2019]] ; [[#Abay--2021|Abay et al., 2021]] ; [[#HLPE--2021|HLPE, 2021]] ).

[[File:15b45d66eecc294638de6296f51ceb58 IPCC_AR6_WGII_Figure_5_Box_5_13_1.png]]

'''Figure Box 5.13.1 | Youth agency, engagement and employment in food system ( [[#HLPE--2021|HLPE, 2021]] ).'''

<div id="5.14.3" class="h2-container"></div>

<span id="climate-resilient-development-pathways"></span>
=== 5.14.3 Climate Resilient Development Pathways ===

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Climate resilient development pathways (CRDPs) introduced in AR5 (Denton, 2014) can briefly be described as ‘development trajectories that integrate adaptation and mitigation to realise the goal of sustainable development’ (see [[#IPCC--2019a|IPCC (2019a)]] ) for a more extensive definition). Several characteristics were proposed in SR1.5 by which such CRDPs could be identified: consistency with principles of sustainable development; ability to deliver poverty reduction; ability to enhance social, gender, racial, ethnic and intergenerational equity; ability to deliver resilience to climate change and other shocks and stresses; and ability to protect species, biodiversity and ecosystem goods and services. There is an increasing literature, assessed in SR1.5, on adaptation pathways approaches, generally for specific regions, locations and subsectors.

Two recent examples directly related to agriculture and food are the following: sustaining agrarian livelihoods to mid-century of Nicaraguan small-scale coffee producers using analyses of suitability and coffee quality changes under an IPCC Special Report on Emissions Scenarios (SRES) A2 emissions scenario ( [[#Läderach--2017|Läderach et al., 2017]] ); and development of participatory pathways to mid-century under RCPs 4.5 and 8.5 support regional adaptation planning in Hawke’s Bay, New Zealand for agricultural producers and rural communities ( [[#Cradock-Henry--2020|Cradock-Henry et al., 2020]] ). CRDPs mentioned in SROCC include shifting from providing coastal defences to adapting to seawater inundation in coastal regions ( [[#Renaud--2015|Renaud et al., 2015]] ) and retreating coastal megacities ( [[#Solecki--2017|Solecki et al., 2017]] ). Pathway frameworks continue to be used to frame the broad-scale challenges of development and climate change, thereby linking different types of food system actor with different responses through time using a variety of approaches, top-down and participatory, qualitative and quantitative ( [[#Butler--2016|Butler et al., 2016]] ; [[#Antle--2017|Antle et al., 2017]] ; [[#Thornton--2017|Thornton and Comberti, 2017]] ; [[#Collste--2019|Collste et al., 2019]] ; [[#Loboguerrero--2020|Loboguerrero et al., 2020]] ; [[#Stringer--2020|Stringer et al., 2020]] ).

While there is consensus that the concept of CRDPs is useful, there are major challenges in identifying, operationalising, monitoring and evaluating them ( [[#Lin--2017|Lin et al., 2017]] ; [[#Bloemen--2018|Bloemen et al., 2018]] ). Management approaches seldom integrate across spatio-temporal scales and may be unable to address unidirectional change and extreme events ( [[#Holsman--2019|Holsman et al., 2019]] ). The socioeconomic complexities and implications of pursuing integrated outcomes make it difficult to evaluate synergies and trade-offs associated with different actions in local contexts through time ( [[#Thornton--2017|Thornton and Comberti, 2017]] ; [[#Ellis--2019|Ellis and Tschakert, 2019]] ; [[#Holsman--2019|Holsman et al., 2019]] ; [[#Orchard--2019|Orchard, 2019]] ). Case studies by Lo (2019) of transformation in a fishing town in south China and by Gajjar (2019) on undesirable path dependencies in development trajectories in urban and rural India show that overall adaptive capacity of populations may be decreased though politicisation and entrenchment of existing inequities, severely limiting the possibilities for future adaptation. A further challenge of implementation is timely detection of tipping points and abrupt exposure events in both climate and environmental systems ( [[#Lenton--2019|Lenton et al., 2019]] ; [[#Trisos--2020|Trisos et al., 2020]] ), which may alter the efficacy of current and planned adaptation actions, necessitating a switch to other, more transformational strategies; in such cases, re-energising food system actors’ commitment to adaptation action may well be needed ( [[#Bloemen--2018|Bloemen et al., 2018]] ).

Integrated modelling of CRDPs will increasingly be needed to throw light on key SDG synergies and trade-offs into the future ( [[#Bleischwitz--2018|Bleischwitz et al., 2018]] ). In investigating possible future pressures on land under the SSPs, Doelman (2018) projected that the largest changes take place in sub-Saharan Africa in SSP3 and SSP4, mostly because of continued high population growth coupled with (projected) sluggish increases in agricultural efficiency, among other things, leading to expansion of agricultural land for crop and livestock production and reduced food security. Lassaletta (2019) evaluated global pig production in the SSPs and concluded that the future sustainability of pig systems will depend on production efficiency improvements coupled with other factors such as use of alternative feed sources and use of slurries on cropland. Such studies will be increasingly important for quantifying the potential trade-offs and synergies between different SDGs, to guide adaptation (and mitigation) action along CRDPs in the future. The current lack of widely accepted and simple-to-measure indicators for tracking progress in adaptation is a significant hurdle to overcome. There is a large literature on the desirable characteristics of future global food systems, but much less on robust analysis that explicitly addresses and evaluates the pathways towards these desired futures. Gerten (2020) estimates that 10.2 billion people can be supported within key planetary boundaries via spatially redistributed cropland and dietary changes, among other actions. There are few, if any, analyses for detailing the plausible pathways to move towards such a future in ways that are socially, economically and environmentally acceptable through time; whether such pathways could indeed be made climate-resilient is unknown. Appropriate monitoring and rapid feedback to food system actors on what is working and why will be critical to the successful operationalisation of adaptation actions within CRDPs ( [[#Bosomworth--2019|Bosomworth and Gaillard, 2019]] ).

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'''Cross-Working Group Box BIOECONOMY: Mitigation and Adaptation via the Bioeconomy'''
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Authors: Henry Neufeldt (Denmark/Germany), Göran Berndes (Sweden), Almut Arneth (Germany), Rachel Bezner Kerr (USA/Canada), Luisa F Cabeza (Spain), Donovan Campbell (Jamaica), Jofre Carnicer Cols (Spain), Annette Cowie (Australia), Vassilis Daioglou (Greece), Joanna House (UK), Adrian Leip (Italy/Germany), Francisco Meza (Chile), Michael Morecroft (UK), Gert-Jan Nabuurs (the Netherlands), Camille Parmesan (UK/USA), Julio C Postigo (USA/Peru), Marta G. Rivera-Ferre (Spain), Raphael Slade (UK), Maria Cristina Tirado von der Pahlen (USA/Spain), Pramod K. Singh (India), Peter Smith (UK)

'''Summary Statement'''
'''''The growing demand for biomass offers both opportunities and challenges to mitigate and adapt to climate change and natural resource constraints (high confidence). Increased technology innovation, stakeholder integration and transparent governance structures and procedures at local to global scales are key to successful bioeconomy deployment maximising benefits and managing trade-offs (high confidence).'''''

Limited global land and biomass resources accompanied by growing demands for food, feed, fibre and fuels, together with prospects for a paradigm shift towards phasing out fossil fuels, set the frame for potentially fierce competition for land 5 [[#footnote-000|1]] and biomass to meet burgeoning demands even as climate change increasingly limits natural resource potentials ( ''high confidence'' ).

Sustainable agriculture and forestry, technology innovation in bio-based production within a circular economy and international cooperation and governance of global trade in products to reflect and disincentivise their environmental and social externalities can provide mitigation and adaptation via bioeconomy development that responds to the needs and perspectives of multiple stakeholders to achieve outcomes that maximise synergies while limiting trade-offs ( ''high confidence'' ).

'''Background'''
There is ''high confidence'' that climate change, population growth and changes in per capita consumption will increase pressures on managed as well as natural and semi-natural ecosystems, exacerbating existing risks to livelihoods, biodiversity, human and ecosystem health, infrastructure and food systems ( [[#Conijn--2018|Conijn et al., 2018]] ; [[#IPCC--2018|IPCC, 2018]] ; [[#IPCC--2019b|IPCC, 2019b]] ; [[#Lade--2020|Lade et al., 2020]] ). At the same time, many global mitigation scenarios presented in Intergovernmental Panel on Climate Change (IPCC) assessment reports rely on large greenhouse gas (GHG) emissions reduction in the Agriculture, Forestry, and Other Land Use (AFOLU) sector and concurrent deployment of reforestation/afforestation and biomass use in a multitude of applications ( [[#Rogelj--2018|Rogelj et al., 2018]] ; AR6 WGIII [[IPCC:Wg2:Chapter:Chapter-3|Chapter 3]] and Chapter 7; [[#Canadell--2021|Canadell et al., 2021]] ; Lee et al., 2021)

Given the finite availability of natural resources, there are invariably trade-offs that complicate land-based mitigation unless land productivity can be enhanced without undermining ecosystem services (e.g., [[#Obersteiner--2016|Obersteiner et al., 2016]] ; [[#Campbell--2017|Campbell et al., 2017]] ; [[#Caron--2018|Caron et al., 2018]] ; [[#Conijn--2018|Conijn et al., 2018]] ; [[#Heck--2018|Heck et al., 2018]] ; [[#WRI--2018|WRI, 2018]] ; [[#Smith--2019c|Smith et al., 2019c]] ). Management intensities can often be adapted to local conditions with consideration of other functions and ecosystem services, but at a global scale the challenge remains to avoid further deforestation and degradation of intact ecosystems, in particular of biodiversity-rich systems (Cross-Chapter Box on NBS-NATURAL in Chapter 2), while meeting the growing demands. Further, increased land use competition can affect food prices and impact food security and livelihoods ( [[#To--2015|To and Grafton, 2015]] ; [[#Chakravorty--2017|Chakravorty et al., 2017]] ), with possible knock-on effects related to civil unrest ( [[#Abbott--2017|Abbott et al., 2017]] ; [[#D’Odorico--2018|D’Odorico et al., 2018]] ).

'''Developing New Bio-Based Solutions while Mitigating Overall Biomass Demand Growth'''
Many existing bio-based products have significant mitigation potential. Increased use of wood in buildings can reduce GHG emissions from cement and steel production while providing carbon storage ( [[#Churkina--2020|Churkina et al., 2020]] ). Substitution of fossil fuels with biomass in manufacture of cement and steel can reduce GHG emissions where these materials are difficult to replace. Dispatchable power based on biomass can provide power stability and quality as the contribution from solar and wind power increases (WGIII Chapter 6), and biofuels can contribute to reducing fossil fuel emissions in the transport and industry sectors (WGIII [[IPCC:Wg2:Chapter:Chapter-10|Chapter 10]] and Chapter 11). The use of bio-based plastics, chemicals and packaging could be increased, and biorefineries can achieve high resource-use efficiency in converting biomass into food, feed, fuels and other bio-based products ( [[#Aristizábal-Marulanda--2019|Aristizábal-Marulanda and Cardona Alzate, 2019]] ; [[#Schmidt--2019|Schmidt et al., 2019]] ). There is also scope for substituting existing bio-based products with more benign products. For example, cellulose-based textiles can replace cotton, which requires large amounts of water, chemical fertilizers and pesticides to ensure high yields.

While increasing and diversified use of biomass can reduce the need for fossil fuels and other GHG-intensive products, unfavourable GHG balances may limit the mitigation value. Growth in biomass use may in the longer term also be constrained by the need to protect biodiversity and ecosystems’ capacity to support essential ecosystem services. Biomass use may also be constrained by water scarcity and other resource scarcities and/or challenges related to public perception and acceptance due to impacts caused by biomass production and use. Energy conservation and efficiency measures and deployment of technologies and systems that do not rely on carbon, such as carbon-free electricity supporting, inter alia, electrification of transport as well as industry processes and residential heating ( [[#IPCC--2018|IPCC, 2018]] ; [[#UNEP--2019|UNEP, 2019]] ), can constrain the growth in biomass demand when countries seek to phase out fossil fuels and other GHG-intensive products while providing an acceptable standard of living. Nevertheless, demand for bio-based products may become high where full decoupling from carbon is difficult to achieve (e.g., aviation, bio-based plastics, and chemicals) or where carbon storage is an associated benefit (e.g., wood buildings, bioenergy with carbon capture and storage (BECCS), biochar for soil amendments), leading to challenging trade-offs (e.g., food security, biodiversity) that need to be managed in environmentally sustainable and socially just ways.

Changes on the demand side as well as improvements in resource-use efficiencies within the global food and other bio-based systems can also reduce pressures on the remaining land resources. For example, dietary changes towards more plant-based food (where appropriate) and reduced food waste can provide climate change mitigation along with health benefits ( WGIII Chapter 7.4 and 12.4, [[#Willett--2019|Willett et al., 2019]] ) and other co-benefits with regard to food security, adaptation and land use ( [[#Mbow--2019|Mbow et al., 2019]] ; [[#Smith--2019c|Smith et al., 2019c]] ; WGII Chapter 5). Advancements in the provision of novel food and feed sources (e.g., cultured meat, insects, grass-based protein feed and cellular agriculture) can also limit the pressures on finite natural resources (WGIII Chapter 12.4, [[#Parodi--2018|Parodi et al., 2018]] ; [[#Zabaniotou--2018|Zabaniotou, 2018]] ).

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Cross-Working Group Box BIOECONOMY

Box Cross-Working Group Box BIOECONOMY.1: Circular Bioeconomy

Circular economy approaches (WGIII-12.6) are commonly depicted by two cycles, where the biological cycle focuses on regeneration in the biosphere and the technical cycle focuses on reuse, refurbishment and recycling to maintain value and maximise material recovery ( [[#Mayer--2019a|Mayer et al., 2019a]] ). Biogenic carbon flows and resources are part of the biological carbon cycle, but carbon-based products can be included in, and affect, both the biological and the technical carbon cycles ( [[#Kirchherr--2017|Kirchherr et al., 2017]] ; [[#Winans--2017|Winans et al., 2017]] ; [[#Velenturf--2019|Velenturf et al., 2019]] ). The integration of circular economy and bioeconomy principles has been discussed in relation to organic waste management ( [[#Teigiserova--2020|Teigiserova et al., 2020]] ), societal transition and policy development (Directorate-General for Research Innovation, 2018; [[#Bugge--2019|Bugge et al., 2019]] ) as well as coronavirus disease 2019 (COVID-19) recovery strategies ( [[#Palahi--2020|Palahi et al., 2020]] ). To maintain the natural resource base, circular bioeconomy emphasises sustainable land use and the return of biomass and nutrients to the biosphere when it leaves the technical cycle.

Biomass scarcity is an argument for adopting circular economy principles for the management of biomass as for non-renewable resources. This includes waste avoidance, product reuse and material recycling, which keep down resource use while maintaining product and material value. However, reuse and recycling is not always feasible, such as when biofuels are used for transport and bio-based biodegradable chemicals are used to reduce ecological impacts where losses to the environment are unavoidable. A balanced approach to management of biomass resources could take departure in the carbon cycle from a value-preservation perspective and the possible routes that can be taken for biomass and carbon, considering a carbon budget defined by the Paris Agreement, principles for sustainable land use and natural ecosystem protection.

'''Land Use Opportunities and Challenges in the Bioeconomy'''
Analyses of synergies and trade-offs between adaptation and mitigation in the agriculture and forestry sectors show that outcomes depend on context, design and implementation, so actions have to be tailored to the specific conditions to minimise adverse effects ( [[#Kongsager--2018|Kongsager, 2018]] ). This is supported in literature analysing the nexus between land, water, energy and food in the context of climate change, which consistently concludes that addressing these different domains together rather than in isolation would enhance synergies and reduce trade-offs ( [[#Obersteiner--2016|Obersteiner et al., 2016]] ; [[#D’Odorico--2018|D’Odorico et al., 2018]] ; [[#Soto%20Golcher--2018|Soto Golcher and Visseren-Hamakers, 2018]] ; Froehse and Schilling, 2019; [[#Momblanch--2019|Momblanch et al., 2019]] ).

Nature-based solutions addressing climate change can provide opportunities for sustainable livelihoods as well as multiple ecosystem services, such as flood risk management through floodplain restoration, saltmarshes, mangroves or peat renaturation (Cross-Chapter Box NATURAL in Chapter 2; [[#UNEP--2021|UNEP, 2021]] ). Climate-smart agriculture can increase productivity while enhancing resilience and reducing GHG emissions inherent to production ( [[#Lipper--2014|Lipper et al., 2014]] ; [[#Singh--2021|Singh and Chudasama, 2021]] ). Similarly, climate-smart forestry considers the whole value chain and integrates climate objectives into forest sector management through multiple measures (from strict reserves to more intensively managed forests) providing mitigation and adaptation benefits ( [[#Nabuurs--2018|Nabuurs et al., 2018]] ; [[#Verkerk--2020|Verkerk et al., 2020]] ; WGIII [[IPCC:Wg2:Chapter:Chapter-7#7.3|Section 7.3]] )

Agroecological approaches can be integrated into a wide range of land management practices to support a sustainable bioeconomy and address equity considerations ( [[#HLPE--2019|HLPE, 2019]] ). Relevant land use practices, such as agroforestry, intercropping, organic amendments, cover crops and rotational grazing, can provide mitigation and support adaption to climate change via food security, livelihoods, biodiversity and health co-benefits ( [[#Ponisio--2015|Ponisio et al., 2015]] ; [[#Garibaldi--2016|Garibaldi et al., 2016]] ; [[#D’Annolfo--2017|D’Annolfo et al., 2017]] ; [[#Bezner%20Kerr--2019|Bezner Kerr et al., 2019]] ; [[#Clark--2019|Clark et al., 2019]] ; [[#Córdova--2019|Córdova et al., 2019]] ; [[#HLPE--2019|HLPE, 2019]] ; [[#Mbow--2019|Mbow et al., 2019]] ; [[#Renard--2019|Renard and Tilman, 2019]] ; [[#Sinclair--2019|Sinclair et al., 2019]] ; [[#Bharucha--2020|Bharucha et al., 2020]] ; [[#Bezner%20Kerr--2021|Bezner Kerr et al., 2021]] ;WGII Cross-Chapter Box NATURAL in Chapter 2). Strategic integration of appropriate biomass production systems into agricultural landscapes can provide biomass for bioenergy and other bio-based products while providing co-benefits such as enhanced landscape diversity, habitat quality, retention of nutrients and sediment, erosion control, climate regulation, flood regulation, pollination and biological pest and disease control (WGIII Chapter12 Box on UNCCD-LDN, [[#Christen--2013|Christen and Dalgaard, 2013]] ; [[#Asbjornsen--2014|Asbjornsen et al., 2014]] ; [[#Holland--2015|Holland et al., 2015]] ; [[#Ssegane--2015|Ssegane et al., 2015]] ; [[#Dauber--2016|Dauber and Miyake, 2016]] ; [[#Milner--2016|Milner et al., 2016]] ; [[#Ssegane--2016|Ssegane and Negri, 2016]] ; [[#Styles--2016|Styles et al., 2016]] ; [[#Zumpf--2017|Zumpf et al., 2017]] ; [[#Cacho--2018|Cacho et al., 2018]] ; [[#Alam--2019|Alam and Dwivedi, 2019]] ; [[#Cubins--2019|Cubins et al., 2019]] ; [[#HLPE--2019|HLPE, 2019]] ; [[#Olsson--2019|Olsson et al., 2019]] ; [[#Zalesny--2019|Zalesny et al., 2019]] ; [[#Englund--2020|Englund et al., 2020]] ). Such approaches can help limit environmental impacts from intensive agriculture while maintaining or increasing land productivity and biomass output.

[[File:6514fb6f53a54d39d32f2d4ba66c3035 IPCC_AR6_WGII_Figure_5_Cross-Working_Group_Box_BIOECONOMY_1.png]]

'''Figure Cross-Working Group Box BIOECONOMY.1 |''' '''Left: High-input intensive agriculture, aiming for high yields of a few crop species, with large fields and no semi-natural habitats.''' Right: Agroecological agriculture, supplying a range of ecosystem services, relying on biodiversity and crop and animal diversity instead of external inputs, and integrating plant and animal production, with smaller fields and presence of semi-natural habitats. Credit: Jacques Baudry (left); Valérie Viaud (right), published in van der Werf et al. (2020).

Transitions from conventional to new biomass production and conversion systems include challenges related to cross-sector integration and limited experience with new crops and land use practices, including needs for specialised equipment (WGII Chapter 5.10, [[#Thornton--2015|Thornton and Herrero, 2015]] ; [[#HLPE--2019|HLPE, 2019]] ). Introduction of agroecological approaches and integrated biomass/food crop production can result in lower food crop yields per hectare, particularly during transition phases, potentially causing indirect land use change, but can also support higher and more stable yields, reduce costs, and increase profitability under climate change ( [[#Muller--2017|Muller et al., 2017]] ; [[#Seufert--2017|Seufert and Ramakutty, 2017]] ; [[#Barbieri--2019|Barbieri et al., 2019]] ; [[#HLPE--2019|HLPE, 2019]] ; [[#Sinclair--2019|Sinclair et al., 2019]] ; [[#Smith--2019c|Smith et al., 2019c]] ; [[#Smith--2020a|Smith et al., 2020a]] ). Crop diversification, organic amendments and biological pest control ( [[#HLPE--2019|HLPE, 2019]] ) can reduce input costs and risks of occupational pesticide exposure and food and water contamination ( [[#Gonzalez-Alzaga--2014|Gonzalez-Alzaga et al., 2014]] ; European Food Safety Authority Panel on Plant Protection Products and their Residues et al., 2017; [[#Mie--2017|Mie et al., 2017]] ), reduce farmers’ vulnerability to climate change (e.g., droughts and spread of pests and diseases affecting plant and animal health; [[#Delcour--2015|Delcour et al., 2015]] ; [[#FAO--2020a|FAO, 2020a]] ) and enhance provisioning and sustaining ecosystem services, such as pollination ( [[#D’Annolfo--2017|D’Annolfo et al., 2017]] ; [[#Sinclair--2019|Sinclair et al., 2019]] ).

Barriers towards wider implementation include absence of policies that compensate landowners for providing enhanced ecosystem services and other environmental benefits, which can help overcome short-term losses during the transition from conventional practices before longer-term benefits can accrue. Other barriers include limited access to markets, knowledge gaps, financial, technological or labour constraints, lack of extension support and insecure land tenure ( [[#Jacobi--2017|Jacobi et al., 2017]] ; [[#Kongsager--2017|Kongsager, 2017]] ; [[#Hernández-Morcillo--2018|Hernández-Morcillo et al., 2018]] ; [[#Iiyama--2018|Iiyama et al., 2018]] ; [[#HLPE--2019|HLPE, 2019]] ). Regional-level agroecology transitions may be facilitated by co-learning platforms, farmer networks, private sector, civil society groups, regional and local administration, and other incentive structures (e.g., price premiums, access to credit, regulation) ( [[#Coe--2014|Coe et al., 2014]] ; [[#Pérez-Marin--2017|Pérez-Marin et al., 2017]] ; Mier y Terán Giménez [[#Cacho--2018|Cacho et al., 2018]] ; [[#HLPE--2019|HLPE, 2019]] ; [[#Valencia--2019|Valencia et al., 2019]] ; [[#SAPEA--2020|SAPEA, 2020]] ). With the right incentives, improvements can be made with regard to profitability, making alternatives more attractive to landowners.

'''Governing the Solution Space'''
Literature analysing the synergies and trade-offs between competing demands for land suggest that solutions are highly contextualised in terms of their environmental, socioeconomic and governance-related characteristics, making it difficult to devise generic solutions ( [[#Haasnoot--2020|Haasnoot et al., 2020]] ). Aspects of spatial and temporal scale can further enhance the complexity, for instance where transboundary effects across jurisdictions or upstream–downstream characteristics need to be considered, or where climate change trajectories might alter relevant biogeophysical dynamics ( [[#Postigo--2021|Postigo and Young, 2021]] ). Nonetheless, there is broad agreement that taking the needs and perspectives of multiple stakeholders into account in a transparent process during negotiations improves the chances of achieving outcomes that maximise synergies while limiting trade-offs ( [[#Ariti--2018|Ariti et al., 2018]] ; [[#Metternicht--2018|Metternicht, 2018]] ; [[#Favretto--2020|Favretto et al., 2020]] ; [[#Kopáček--2021|Kopáček, 2021]] ; [[#Muscat--2021|Muscat et al., 2021]] ). Yet differences in agency and power between stakeholders or anticipated changes in access to or control of resources can undermine negotiation results even if there is a common understanding of the overarching benefits of more integrated environmental agreements and the need for greater coordination and cooperation to avoid longer-term losses to all ( [[#Aarts--2010|Aarts and Leeuwis, 2010]] ; [[#Weitz--2017|Weitz et al., 2017]] ). There is also the risk that strong local participatory processes can become disconnected from broader national plans, and thus fail to support the achievement of national targets. Thus, connection between levels is needed to ensure that ambition for transformative change is not derailed at the local level ( [[#Aarts--2010|Aarts and Leeuwis, 2010]] ; [[#Postigo--2021|Postigo and Young, 2021]] ).

Decisions on land uses between biomass production for food, feed, fibre or fuel, as well as nature conservation or restoration and other uses (e.g., mining, urban infrastructure), depend on differences in perspectives and values. Because the availability of land for diverse biomass uses is invariably limited, setting priorities for land use allocations therefore first depends on making the perspectives underlying what is considered as ‘high-value’ explicit ( [[#Fischer--2007|Fischer et al., 2007]] ; [[#Garnett--2015|Garnett et al., 2015]] ; [[#de%20Boer--2018|de Boer and van Ittersum, 2018]] ; [[#Muscat--2020|Muscat et al., 2020]] ). Decisions can then be made transparently based on societal norms, needs and the available resource base. Prioritisation of land use for the common good therefore requires societal consensus-building embedded in the socioeconomic and cultural fabric of regions, societies and communities. Integration of local decision making with national planning ensures local actions complement national development objectives.

International trade in the global economy today provides important opportunities to connect producers and consumers, effectively buffering price volatilities and potentially offering producers in low-income countries access to global markets, which can be seen as an effective adaptation measure ( [[#Baldos--2015|Baldos and Hertel, 2015]] ; [[#Costinot--2016|Costinot et al., 2016]] ; [[#Hertel--2016|Hertel and Baldos, 2016]] ; [[#Gouel--2021|Gouel and Laborde, 2021]] ; WGII Chapter 5.11).. But there is also clear evidence that international trade and the global economy can enhance price volatility, lead to food price spikes and affect food security due to climate and other shocks, as seen recently due to the COVID-19 pandemic (WGII Chapter 5.12, [[#Cottrell--2019|Cottrell et al., 2019]] ; [[#WFP-FSIN--2020|WFP-FSIN, 2020]] ; [[#Verschuur--2021|Verschuur et al., 2021]] ). The continued strong demand for food and other bio-based products, mainly from high- and middle-income countries, therefore, requires better cooperation between nations and global governance of trade to more accurately reflect and disincentivise their environmental and social externalities. Trade in agricultural and extractive products driving land use change in tropical forest and savanna biomes is of major concern because of the biodiversity impacts and GHG emissions incurred in their provision (WGII Cross-Chapter Paper 7, [[#Hosonuma--2012|Hosonuma et al., 2012]] ; [[#Forest%20Trends--2014|Forest Trends, 2014]] ; [[#Henders--2015|Henders et al., 2015]] ; [[#Curtis--2018|Curtis et al., 2018]] ; [[#Pendrill--2019|Pendrill et al., 2019]] ; [[#Seymour--2019|Seymour and Harris, 2019]] ; [[#Kissinger--2021|Kissinger et al., 2021]] ).

In summary, there is significant scope for optimising use of land resources to produce more biomass while reducing adverse effects ( ''high confidence'' ). Context-specific prioritisation, technology innovation in bio-based production, integrative policies, coordinated institutions and improved governance mechanisms to enhance synergies and minimise trade-offs can mitigate the pressure on managed as well as natural and semi-natural ecosystems ( ''medium confidence'' ). Yet, energy conservation and efficiency measures, and deployment of technologies and systems that do not rely on carbon-based energy and materials, are essential for mitigating biomass demand growth as countries pursue ambitious climate goals ( ''high confidence'' ).

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Cross-Working Group Box BIOECONOMY

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<div id="footnote-000" class="_idFootnote"></div>

[[#footnote-000-backlink|1]] 5 For lack of space, the focus is on land only, although the bioeconomy also includes sea-related bioresources.

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