FINAL DRAFT Chapter 5 IPCC WGII Sixth Assessment Report
1
2 Chapter 5: Food, Fibre, and other Ecosystem Products
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4 Coordinating Lead Authors: Rachel Bezner Kerr (USA/Canada), Toshihiro Hasegawa (Japan), Rodel
5 Lasco (Philippines)
6
7 Lead Authors: Indra Bhatt (India), Delphine Deryng (Germany/France), Aidan Farrell (Trinidad and
8 Tobago/Ireland), Helen Gurney-Smith (Canada/United Kingdom), Hui Ju (China), Salvador Lluch-Cota
9 (Mexico), Francisco Meza (Chile), Gerald Nelson (USA), Henry Neufeldt (Denmark/Germany), Philip
10 Thornton (Kenya/United Kingdom)
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12 Contributing Authors: Guleid Artan (Kenya/Somalia), Ayansina Ayanlade (Nigeria), Marta Baraibar
13 (Kenya/Spain), Manuel Barange (South Africa/Italy), Mucahid Mustafa Bayrak (The Netherlands), Ermias
14 A. Betemariam (Kenya/Ethiopia), Edwin Castellanos (Guatemala), William Cheung (Canada), Priscilla
15 Claeys (Belgium), Jennifer Clapp (Canada), Verónica Crespo-Pérez (Ecuador), Shouro Dasgupta
16 (Italy/Bangladesh), Deborah Delgado Pugley (Peru), Alice Favero (USA), Jennifer Franco (The
17 Netherlands), Eranga Galappaththi (Canada/Sri Lanka), Amelie Gaudin (USA/France), Adugna Gemeda
18 (Ethiopia), Patrick Gonzalez (USA), Jack Heinemann (New Zealand/USA), Ann Kingiri (Kenya), Xiaoyue
19 Li (China), Ana Maria Loboguerrero (Colombia), Dianne Mayberry (Australia), Kenneth Kemucie Mwangi
20 (Kenya), Christine Negra (USA), Kari Marie Norgaard (USA), Hanson Nyantakyi-Frimpong (USA/Ghana),
21 Patricia Pinho (Brazil), Julio C. Postigo (USA/Peru), Bronwen Powell (Canada), Victoria Reyes-García
22 (Spain), Marta Rivera-Ferre (Spain), Abubakr A.M. Salih (Kenya/Sudan), Arnim Scheidel (Spain/Austria),
23 Matthew Schnurr (Canada), Anna Schlingmann (Spain/Germany), Rupert Seidl (Germany), Gudeta W.
24 Sileshi (Tanzania), Doris Soto (Chile), Pete Smith (United Kingdom), Elizabeth Sprout (United
25 Kingdom/USA), M. Cristina Tirado-von der Pahlen (USA/Spain), Hitomi Wakatsuki (Japan), Jennifer Vanos
26 (Canada), Lewis Ziska (USA), Robert Zougmoré (Burkina Faso)
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28 Review Editors: Pauline Dube (Botswana), James Morison (United Kingdom)
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30 Chapter Scientists: Emily Baker (USA), Hitomi Wakatsuki (Japan), Elizabeth Sprout (United
31 Kingdom/USA)
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33 Date of Draft: 1 October 2021
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35 Notes: TSU Compiled Version
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37
38 Table of Contents
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40 Executive Summary..........................................................................................................................................4
41 5.1 Introduction ..............................................................................................................................................8
42 5.1.1 Scope of the Chapter .......................................................................................................................8
43 5.1.2 Starting Point: AR5 and Recent IPCC Special Reports..................................................................8
44 5.1.3 Chapter Framework........................................................................................................................8
45 5.2 Observed Impacts and Key Risks .........................................................................................................14
46 5.2.1 Detection and Attribution of Observed Impacts ...........................................................................14
47 5.2.2 Key Risks .......................................................................................................................................15
48 5.3 Methodologies and Associated Uncertainties.......................................................................................17
49 5.3.1 Methodologies for Assessing Impacts and Risks...........................................................................17
50 5.3.2 Methodologies for Assessing Vulnerabilities and Adaptation ......................................................19
51 5.4 Crop-based Systems ...............................................................................................................................20
52 5.4.1 Observed Impacts..........................................................................................................................20
53 Box 5.1: Evidence for Simultaneous Crop Failures due to Climate Change ............................................22
54 5.4.2 Assessing Vulnerabilities within Production Systems...................................................................27
55 5.4.3 Projected Impacts .........................................................................................................................30
56 Box 5.2: Case Study: Wine.............................................................................................................................34
57 Box 5.3: Pollinators.........................................................................................................................................35
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1 Box 5.4: Soil Health ........................................................................................................................................37
2 5.4.4 Adaptation Options .......................................................................................................................38
3 5.5 Livestock-based Systems........................................................................................................................45
4 5.5.1 Observed Impacts..........................................................................................................................45
5 5.5.2 Assessing Vulnerabilities ..............................................................................................................46
6 5.5.3 Projected Impacts .........................................................................................................................47
7 5.5.4 Adaptation in Livestock-based Systems ........................................................................................51
8 Box 5.5: Alternative Sources of Protein for Food and Feed .......................................................................53
9 5.6 Forestry Systems.....................................................................................................................................54
10 5.6.1 Observed Impacts..........................................................................................................................54
11 5.6.2 Projected Impacts .........................................................................................................................55
12 5.6.3 Adaptation.....................................................................................................................................57
13 Box 5.6: Contributions of Indigenous and local knowledge: an example..................................................58
14 5.7 Other Natural Products .........................................................................................................................60
15 5.7.1 Medicinal Plants ...........................................................................................................................60
16 5.7.2 Resin and Gum ..............................................................................................................................60
17 5.7.3 Wild Foods ....................................................................................................................................61
18 5.7.4 Observed and Projected Impacts ..................................................................................................61
19 5.8 Ocean-based and Inland Fisheries Systems .........................................................................................69
20 5.8.1 Observed Impacts..........................................................................................................................70
21 5.8.2 Assessing Vulnerabilities ..............................................................................................................71
22 5.8.3 Projected Impacts .........................................................................................................................73
23 5.8.4 Adaptation.....................................................................................................................................74
24 Cross-Chapter Box: MOVING PLATE: Sourcing food when species distributions change ..................75
25 5.9 Ocean-based and Inland Aquaculture Systems ...................................................................................82
26 5.9.1 Observed Impacts..........................................................................................................................83
27 5.9.2 Assessing Vulnerabilities ..............................................................................................................84
28 5.9.3 Projected Impacts .........................................................................................................................86
29 5.9.4 Aquaculture Adaptation ................................................................................................................90
30 5.9.5 Contributions of Indigenous, Traditional, and Local Knowledge ................................................93
31 5.10 Mixed Systems ........................................................................................................................................94
32 5.10.1 Observed Impacts..........................................................................................................................94
33 5.10.2 Assessing Vulnerabilities ..............................................................................................................95
34 5.10.3 Projected Impacts .........................................................................................................................96
35 Box 5.7: Perspectives of crop and livestock farmers on observed changes in climate in the Sahel ........97
36 5.10.4 Adaptation Strategies....................................................................................................................98
37 Box 5.8: Climate Adaptation and Maladaptation in Cocoa and Coffee Production..............................101
38 5.11 The Supply Chain from Postharvest to Food.....................................................................................102
39 5.11.1 Current and Future Climate Change Impacts on Food Safety ...................................................102
40 5.11.2 Current and Future Climate Change Impacts on Food Loss in Storage, Distribution and
41 Processing ........................................................................................................................... 104
42 5.11.3 Current and Projected Impacts on Transportation and Distribution: Domestic and International
43 Trade ...................................................................................................................................104
44 5.11.4 Adaptation in the Post-harvest Supply Chain .............................................................................106
45 5.12 Food Security, Consumption and Nutrition.......................................................................................107
46 5.12.1 Introduction.................................................................................................................................107
47 5.12.2 Mechanisms for Climate Change Impacts on Food Security......................................................108
48 5.12.3 Observed Impacts........................................................................................................................110
49 Box 5.9: Desert Locust Case Study: Climate as Compounding Effect on Food Security ......................111
50 5.12.4 Projected Impacts on Food Security...........................................................................................113
51 Box 5.10: Food Safety Interactions with Food Security and Malnutrition .............................................115
52 5.12.5 Adaptation Options for Food Security and Nutrition .................................................................116
53 5.12.6 Changing Dietary Patterns .........................................................................................................118
54 5.12.7 Integrated Multisectoral Food Security and Nutrition Adaptation Options...............................119
55 5.12.8 Incorporating Human Rights-based Approaches into Food Systems .........................................121
56 5.13 Climate Change Triggered Competition, Trade-offs and Nexus Interactions in Land and Ocean
57 ................................................................................................................................................................ 121
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1 5.13.1 Impacts of Global Land Deals on Land Use, Vulnerable Groups, and Adaptation to Climate
2 Change ................................................................................................................................121
3 5.13.2 Trade-offs Generated by Agricultural Intensification and Expansion........................................124
4 5.13.3 Competition Between Food Systems in Land and Ocean ...........................................................125
5 5.13.4 Maladaptation Responses and sustainable solutions..................................................................126
6 5.13.5 Climate Change and Climate Response Impacts on Indigenous People ....................................130
7 5.13.6 Increased Presence of Financial Actors in the Agrifood System................................................133
8 5.13.7 Climate Change Interactions with other Drivers Food-Water-Health-Energy-Security Nexus
9 ............................................................................................................................................. 133
10 5.14 Implementation Pathways to Adaptation and Co-benefits...............................................................134
11 5.14.1 State of Adaptation of Food, Feed, Fibre, and Other Ecosystem Products................................134
12 Box 5.11: Agroecology as a Transformative Climate Change Adaptation Approach ...........................139
13 5.14.2 Enabling Conditions for Implementing Adaptation ....................................................................144
14 Box 5.12: Is Climate-smart Agriculture Overlooking Gender and Power Relations?...........................144
15 Box 5.13: Supporting youth adaptation in food systems...........................................................................145
16 5.14.3 Climate-resilient Development Pathways...................................................................................156
17 Cross-Working Group Box BIOECONOMY: Mitigation and Adaptation via the Bioeconomy..........157
18 FAQ5.1: How is climate change (already) affecting people's ability to have enough nutritious food? 162
19 FAQ5.2: How will climate change impact food availability by mid and late century and who will suffer
20 most? ......................................................................................................................................................163
21 FAQ5.3: Land is going to be an important resource for mitigating climate change: How is the
22 increasing competition for land threatening global food security and who will be affected the
23 most? ......................................................................................................................................................164
24 FAQ5.4: What are effective adaptation strategies for improving food security in a warming world? 166
25 FAQ5.5: Climate change is not the only factor threatening global food security: other than climate
26 action, what other actions are needed to end hunger and ensure access by all people to nutritious
27 and sufficient food all year round? .....................................................................................................167
28 References......................................................................................................................................................169
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1 Executive Summary
2
3 Current Impacts
4
5 Climate change impacts are stressing agriculture, forestry, fisheries, and aquaculture, increasingly
6 hindering efforts to meet human needs (high confidence1). Human-induced warming has slowed growth
7 of agricultural productivity over the past 50 years in mid- and low-latitudes (medium confidence). Crop
8 yields are compromised by surface ozone (high confidence). Methane emissions have negatively impacted
9 crop yields by increasing temperatures and surface ozone concentrations (medium confidence). Warming is
10 negatively affecting crop and grassland quality and harvest stability (high confidence). Warmer and drier
11 conditions have increased tree mortality and forest disturbances in many temperate and boreal biomes (high
12 confidence), negatively impacting provisioning services (medium confidence). Ocean warming has decreased
13 sustainable yields of some wild fish populations (high confidence). Ocean acidification and warming have
14 already affected farmed aquatic species (high confidence). {5.2.1, 5.4.1, 5.5.1, 5.6.1, 5.7.1, 5.8.1, 5.9.1}
15
16 Warming has altered the distribution, growing area suitability and timing of key biological events,
17 such as flowering and insect emergence, impacting food quality and harvest stability (high confidence).
18 It is very likely2 that climate change is altering the distribution of cultivated, wild terrestrial, marine and
19 freshwater species. At higher-latitudes warming has expanded potential area but has also altered phenology
20 (high confidence), potentially causing plant-pollinator and pest mismatches (medium confidence). At low-
21 latitude temperatures have crossed upper tolerance thresholds more frequently leading to heat stress (high
22 confidence). {5.4.1, 5.7.4, 5.8.1, Cross-Chapter Box MOVING PLATE this Chapter , 5.12.3.4}
23
24 Climate-related extremes have affected the productivity of all agricultural and fishery sectors, with
25 negative consequences for food security and livelihoods (high confidence). The frequency of sudden food
26 production losses has increased since at least mid-20th century on land and sea (medium evidence, high
27 agreement). Droughts, floods, and marine heatwaves contribute to reduced food availability and increased
28 food prices, threatening food security, nutrition, and livelihoods of millions (high confidence). Droughts
29 induced by the 2015-2016 El Niño, partially attributable to human influences (medium confidence), caused
30 acute food insecurity in various regions, including eastern and southern Africa and the dry corridor of
31 Central America (high confidence). In the northeast Pacific, a recent 5-year warm period impacted the
32 migration, distribution, and abundance of key fish resources (high confidence). Increasing variability in
33 grazing systems has negatively affected animal fertility, mortality, and herd recovery rates, reducing
34 livestock keepers' resilience (medium confidence). {WGI AR6 Sections 11.2-11.8, 5.2.1, 5.4.1, 5.4.2,
35 5.5.2,5.8.1, 5.9.1, 5.12.1, 5.14.2, 5.14.6, Cross-Chapter Box MOVING PLATE this Chapter}
36
37 Climate change impacts everybody, but vulnerable groups, such as women, children, low-income
38 households, Indigenous or other minority groups and small-scale producers, are often at higher risk of
39 malnutrition, livelihood loss, rising costs and competition over resources (high confidence). Increasing
40 competition for land, energy, and water, exacerbates impacts of climate change on food security (high
41 confidence). {5.4.2.2, 5.5.2.6; 5.8.2.2, 5.9.2.1, 5.12.2, 5.12.3.1; 5.12.3.2; 5.12.3.3; 5.13.1, 5.13.3, 5.13.4}
42
43 Projected Impacts
44
45 Climate change will make some current food production areas unsuitable (high confidence). Current
46 global crop and livestock areas will increasingly become climatically unsuitable under a high emission
47 scenario (high confidence) (e.g.,10% by 2050, over 30 % by 2100 under SSP-8.5 vs below 8% by 2100 under
48 SSP1-2.6). Increased, potentially concurrent climate extremes will periodically increase simultaneous losses
1 In this Report, the following summary terms are used to describe the available evidence: limited, medium, or robust; and for the
degree of agreement: low, medium, or high. A level of confidence is expressed using five qualifiers: very low, low, medium, high,
and very high, and typeset in italics, e.g., medium confidence. For a given evidence and agreement statement, different confidence
levels can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing confidence.
2 In this Report, the following terms have been used to indicate the assessed likelihood of an outcome or a result: Virtually certain
99100% probability, Very likely 90100%, Likely 66100%, About as likely as not 3366%, Unlikely 033%, Very unlikely 0
10%, and Exceptionally unlikely 01%. Additional terms (Extremely likely: 95100%, More likely than not >50100%, and
Extremely unlikely 05%) may also be used when appropriate. Assessed likelihood is typeset in italics, e.g., very likely. This Report
also uses the term `likely range' to indicate that the assessed likelihood of an outcome lies within the 17-83% probability range.
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1 in major food-producing regions (medium confidence). {WGI Section 11.8, 5.2.2, 5.4.1, 5.4.3, 5.5.2, 5.5.3,
2 Cross-Chapter Box MOVING PLATE in Chapter 5 this Chapter, Section 5.12.4}
3
4 Impacts on food availability and nutritional quality will increase the number of people at risk of
5 hunger, malnutrition and diet-related mortality (high confidence). Climate change will increase the
6 number of people at risk of hunger in mid-century, concentrated in Sub-Saharan Africa, South Asia and
7 Central America (high confidence) (e.g. between 8 million under SSP1-6.0 to 80 million people under SSP3-
8 6.0). Increased CO2 concentrations will reduce nutrient density in some crops (high confidence). Climate
9 change will increase loss of years of full health3 by 10% in 2050 under RCP8.5 due to undernutrition and
10 micronutrient deficiencies (medium evidence, high agreement). {5.2.2, 5.4.2, 5.4.3, 5.12.1.2, 5.12.4; Cross-
11 Chapter Box MOVING PLATE this Chapter}
12
13 Climate change will increasingly expose outdoor workers and animals to heat stress, reducing labour
14 capacity, animal health, and dairy and meat production (high confidence). The number of days with
15 climatically stressful conditions for outdoor workers will increase by up to 250 workdays per year by
16 century's end in some parts of South Asia, tropical sub-Saharan Africa and parts of Central and South
17 America under SSP5-8.5, with negative consequences such as reduced food productivity, higher costs and
18 prices (medium confidence). From early-to end-century, cattle, sheep, goats, pigs and poultry in the low
19 latitudes will face 72-136 additional days per year of extreme stress from high heat and humidity under
20 SSP5-8.5. Meat and milk productivity will be reduced (medium confidence). {5.5.3.4; 5.12.4}
21
22 Climate change will further increase pressures on terrestrial ecosystem services supporting global food
23 systems (high confidence). Climate change will reduce the effectiveness of pollinator agents as species are
24 lost from certain areas, or the coordination of pollinator activity and flower receptiveness is disrupted in
25 some regions (high confidence). Greenhouse gas emissions will negatively impact air, soil, and water quality,
26 exacerbating direct climatic impacts on yields (high confidence). {5.4.3, Box5.3, Box5.4, 5.5.3.4; 5.7.1,
27 5.7.4, 5.10.3}
28
29 Climate change will significantly alter aquatic food provisioning services and water security with
30 regional variances (high confidence). Climate change will reduce marine fisheries and aquaculture
31 productivity, altering the species that will be fished or cultured, and reducing aquaculture habitat in tropical
32 and sub-tropical areas (high confidence).. Global ocean animal biomass will decrease by 5 to 17% under
33 RCP2.6 and 8.5 respectively from 1970 to 2100 with an average decline of 5% for every 1°C of warming,
34 affecting food provisioning, revenue value and distribution, (medium confidence). Global marine aquaculture
35 will decline under warming and acidification from 2020 to 2100, with potential short-term gains for
36 temperate finfish and overall negative impacts on bivalve aquaculture from habitat reduction (50-100% for
37 some countries in the Northern Hemisphere) (medium confidence). Changes in precipitation, sea level,
38 temperature, and extreme climate events will affect food provisioning from inland and coastal aquatic
39 systems (high confidence). Sea-level rise and altered precipitation will increase coastal inundation and water
40 conflicts between water-dependent sectors, such as rice production, direct human use, and hydropower
41 (medium confidence). {5.8.3, 5.9.3, 5.13, Cross-Chapter Box SLR in Chapter 3}.
42
43 The occurrence and distribution of pests, weeds and diseases, including zoonoses, in agricultural,
44 forest and food systems (terrestrial and aquatic) will be altered and their control will become
45 costlier (medium confidence). Changes in the rates of reproduction and distribution of weeds, insect pests,
46 pathogens and disease vectors will increase biotic stress on crops, forests, and livestock, and will increase the
47 risk of biodiversity loss and ecosystem degradation (medium evidence, high agreement). Risks will increase
48 for climate-driven emerging zoonoses (medium evidence, high agreement). {5.4.1.3, 5.9.4, Cross-Chapter
49 Box MOVING PLATE this Chapter}
50
51 Forest production systems will have variable responses to climate change across regions, with negative
52 effects being more predominant in tropical forests (high confidence). In temperate and boreal regions,
53 some productivity gains are projected, but tree mortality will increase in some areas (high confidence). In
54 tropical forests, change in species composition and forest structure will lower production (medium
55 confidence). Some models project a possible increase in global wood supply and lowering of average wood
3 Disability-Adjusted Life Years or DALYs.
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1 prices, but they do not account for the negative impacts of extreme events and thus possibly overestimate the
2 wood supply (medium confidence). {5.6.2}
3
4 Climate change will negatively impact food safety (high confidence). Higher temperatures and humidity
5 will favour toxigenic fungi, plant and animal-based pathogens, and harmful algal blooms (HABs) (high
6 confidence). More frequent and intense flood events and increased melting of snow and ice will increase
7 food contamination (high confidence). Incidence and severity of harmful algal blooms and water-borne
8 diseases will increase, as will indirect effects from infrastructure damage during extreme events (high
9 confidence). {5.4.3, 5.5.2.3, 5.8.1, 5.8.2, 5.8.3, 5.9.1, 5.11.1, 5.11.3, 5.12.3; Cross-Chapter Box ILLNESS in
10 Chapter 2}
11
12 Adaptation
13
14 Many autonomous adaptation options have been implemented in both terrestrial and aquatic systems,
15 but on-farm adaptations are insufficient to meet SDG2 (high confidence). Autonomous responses
16 include livestock and farm management, switching varieties/species and altered timing of key farm activities
17 such as planting or stocking (high confidence). However, because of limited adaptive capacities and non-
18 climatic compounding drivers of food insecurity, SDG2 will not be met (high confidence). {Table 5.1, 5.4.4;
19 5.5.4, 5.9.4, 5.10.4; 5.12.4}
20
21 Various adaptation options are currently feasible and effective at reducing climate impacts in different
22 socio-cultural, economic, and geographical contexts (high confidence) but some lack adequate
23 economic or institutional feasibility or information on limits (medium confidence). Feasible and effective
24 options include cultivar improvements, community-based adaptation, agricultural diversification, climate
25 services, adaptive eco-management in fisheries and aquaculture. There is limited evidence, medium
26 agreement on the institutional feasibility or cost effectiveness of adaptation activities, and the limits to such
27 adaptations. {5.4.4, 5.5.4, 5.6.3, 5.8.4, 5.9.4, 5.10.4, 5.11.4, 5.12.4, 5.14.1}
28
29 Ecosystem-based approaches such as diversification, land restoration, agroecology, and agroforestry
30 have the potential to strengthen resilience to climate change with multiple co-benefits but trade-offs
31 and benefits vary with socio-ecological context (high confidence). Ecosystem-based approaches support
32 long-term productivity and ecosystem services such as pest control, soil health, pollination and buffering of
33 temperature extremes (high confidence), but potential and trade-offs vary by socio-economic context,
34 ecosystem zone, species combinations and institutional support (medium confidence). {5.4.4.4, 5.6.3, 5.10.4,
35 5.14.1, Cross-Chapter Box NATURAL in Chapter 2; Cross-Working Group Box BIOECONOMY this
36 Chapter}
37
38 Bio-based products as part of a circular bioeconomy have potential to support adaptation and
39 mitigation, with sectoral integration, transparent governance and stakeholder involvement key to
40 maximizing benefits and managing trade-offs (high confidence). A sustainable bioeconomy relying on
41 bioresources will need to be supported by technology innovation and international cooperation and
42 governance of global trade to disincentivize environmental and social externalities (medium confidence).
43 {Cross-Working Group Box BIOECONOMY this Chapter}
44
45 Sustainable resource management in response to distribution shifts of terrestrial and aquatic species
46 under climate change is an effective adaptation option to reduce food and nutritional risk, conflict and
47 loss of livelihood (medium confidence). Adaptive transboundary governance and ecosystem-based
48 management, livelihood diversification, capacity development and improved knowledge-sharing will reduce
49 conflict and promote the fair distribution of sustainably-harvested wild products and revenues (medium
50 confidence). Other options include shared quotas and access rights considering trade-offs, shifting
51 livelihoods to follow target species, new markets for emerging species, and technology {Cross Chapter Box
52 MOVING PLATE this Chapter, 5.8.4, 5.14.3.4}
53
54 Implemented adaptation in crop production will be insufficient to offset the negative effects of climate
55 change (high confidence). Currently available management options have the potential to compensate global
56 crop production losses due to climate change up to ~2-°C warming, but the negative impacts even with
57 adaptation will grow substantially from the mid-century under high temperature change scenarios (high
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1 confidence). Regionally, the negative effects will prevail sooner where current temperatures are already
2 higher as in lower latitudes (high confidence). {5.2.2, 5.4.3, 5.4.4, 5.8.4, 5.9.4, 5.14.2.4}
3
4 Supportive public policies will enhance effectiveness and/or feasibility of adaptation in ecosystem
5 provisioning services (medium confidence). Policies that support system transitions include shifting
6 subsidies, removing perverse incentives, regulation and certification, green public procurement, investment
7 in sustainable value chains, support for capacity-building, access to insurance premiums and payments for
8 ecosystem services, social protection, among others (medium confidence). {5.4.4.3; 5.4.4.4; 5.10.4.4; 5.12.6;
9 5.13.4; 5.14.1.3; 5.14.2.4; Box 5.13, Cross-Working Group Box BIOECONOMY in Chapter 2}.
10
11 Harnessing youth innovation and vision alongside other SDGs such as gender equity, Indigenous
12 knowledge, local knowledge, urban and rural livelihoods, will support effective climate change
13 adaptation to ensure resilient economies in food systems (high confidence). Adaptation strategies that
14 address power inequities lead to co-benefits in equity outcomes and resilience for vulnerable groups (medium
15 confidence). Indigenous knowledge and local knowledge facilitate adaptation strategies for ecosystem
16 provisioning, especially when combined with scientific knowledge using participatory and community-based
17 approaches (high confidence). {5.4.4.3, Table 5.6, 5.6.3, 5.8.4, 5.9.2, 5.9.4.1, 5.9.5, 5.10.2.2, 5.12.7, 5.12.8,
18 5.13.4, 5.13.5, 5.14.1.1, 5.14.1.2, 5.14.1.4,5.14.2.1, Box 5.13, 5.14.2.2 }
19
20 Policy decisions related to climate change adaptation and mitigation that ignore or worsen risks of
21 adverse effects for different groups and ecosystems increase vulnerability, negatively affect capacity to
22 deal with climate impacts, and impede sustainable development (medium confidence with robust
23 evidence, medium agreement). Lacking sufficient stakeholder participation, large-scale land acquisitions
24 have had mostly negative implications for vulnerable groups and climate change adaptation (high
25 confidence). Policy and program appraisal of adaptation options that consider the risks of adverse effects
26 across different groups at different scales and use inclusive rights-based approaches help avoid
27 maladaptation (medium confidence). Successful forest adaptation involves recognition of land rights and
28 cooperation with Indigenous Peoples and other local communities who depend on forest resources (high
29 confidence). {5.6.3; 5.12.3, 5.13.1; 5.13.2; 5.14.2.1}
30
31 Financial barriers limit implementation of adaptation options in agriculture, fisheries, aquaculture
32 and forestry and vastly more public and private investment is required (high confidence).
33 Public-sector investment in adaptation of agriculture, forestry and fisheries has grown four-fold since 2010
34 but adaptation costs will be much higher to meet future adaptation needs (medium confidence). Expanding
35 access to financial services and pooling climate risks will enable and incentivize climate change adaptation
36 (medium confidence). {5.14.3, 5.14.5., Cross-Chapter Box FINANCE in Chapter 17}.
37
38 Climate-resilient development pathways offer a way forward to guide climate action in food system
39 transitions, but operationalisation is hampered by limited indicators and analyses (medium
40 confidence). Robust analyses are needed that detail plausible pathways to move towards more resilient,
41 equitable and sustainable food systems in ways that are socially, economically and environmentally
42 acceptable through time (high confidence). Appropriate monitoring and rapid feedback to food system actors
43 will be critical to the success of many current and future adaptation actions (high confidence). {5.14.4}
44
45
46
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1 5.1 Introduction
2
3 5.1.1 Scope of the Chapter
4
5 This chapter assesses the scientific literature produced after AR5 dealing with past, current, and future
6 climate change effects on managed ecosystems that provide provisioning and cultural services. It spans low
7 and high intensity production systems for food, feed, fibre, and other ecosystem products.
8
9 Climate change has already had global impacts, including high income countries. Special emphasis is placed
10 on the assessment of vulnerabilities of particular groups that are context- and location-specific, such as
11 Indigenous Peoples and other minorities, women and small-scale food producers. The report builds on the
12 IPCC AR5 and recent Special Reports. This chapter combines food systems, fibre, wood, and other products
13 from ecosystems previously detailed in separate chapters of AR5, with an increased focus on ecosystem
14 services, including the long-term sustainability of the global food system (Figure 5.1). The chapter focuses
15 on key climate risks, implementation and outcomes of adaptation solutions for different groups as well as
16 limits to adaptation.
17
18 5.1.2 Starting Point: AR5 and Recent IPCC Special Reports
19
20 AR5 Chapter 7 reported with high confidence that food production systems were being negatively impacted
21 by climate change, including both terrestrial and aquatic food species (Porter et al., 2014). Increased
22 temperatures will have large negative impacts on the food production system under 2°C warming by late
23 20th century, with temperatures exceeding 4°C posing even greater risk to global food security (Porter et al.,
24 2014). Adaptation options are needed to reduce the risk from climate change, but there was limited
25 information of their effectiveness.
26
27 The 1.5°C Special Report concluded that climate-related risks to food security will rise under 1.5°C and will
28 increase further under 2°C or higher. Above 1.5°C, currently available adaptation options will be much less
29 effective and site-specific limits to adaptation will be reached for vulnerable regions and sectors. There was
30 high confidence that limiting warming to 1.5°C will result in smaller net reductions in yields of major crops
31 affecting food availability and nutrition, and that rising temperatures will adversely affect livestock via
32 changes in feed quality, fertility, production, spread of diseases and water availability.
33
34 The SRCCL expanded beyond the 1.5°C report to provide more in-depth information on climate change
35 interactions with food security, desertification, and degradation. There was high confidence that climate
36 risks, both for slow changes and extreme events, are interlinked with ecosystem services, health, and food
37 security, often cascading and potentially reinforcing effects. Climate change already affects all dimensions of
38 food security, namely availability, access, utilization, and stability, by disrupting food production, quality,
39 storage, transport, and retail. These effects exacerbate competition for land and water resources, leading to
40 increased deforestation, biodiversity reduction and loss of wetlands. With high certainty, limiting global
41 warming would lower future risks related to land, such as water scarcity, fire, vegetation shifts, degradation,
42 desertification and food insecurity and malnutrition, particularly for those most vulnerable today: small-scale
43 food producers in low-income countries, Indigenous communities, women, and the urban poor. SRCCL
44 assessed a range of adaptation pathways to increase food resilience.
45
46 The SROCC identified climate change impacts of warming, deoxygenation and acidification of the ocean
47 and reductions in snow, sea ice and glaciers as having major negative impacts on fisheries and crops watered
48 from mountain runoff, agriculture. These impacts affect food provisioning of food and directly threatening
49 livelihoods and food security of vulnerable coastal communities and glacier-fed river basins. Climate change
50 impacts on fisheries will be particularly high in tropical regions, where reductions in catch are expected to be
51 among the largest globally, leading to negative economic and social effects for fishing communities and with
52 implications for the supply of fish and shellfish (high confidence). While specific impacts will depend on the
53 level of global warming and mitigative action to improve fisheries and aquaculture management, some
54 current management practices and extraction levels may not be viable in the future.
55
56 5.1.3 Chapter Framework
57
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1 This chapter is taking a food systems approach similar to the food security chapter in SRCCL (Mbow et al.,
2 2019), with close attention to food system linkages, interactions and impacts on ecosystem services and
3 biodiversity (Steffen et al., 2015; Raworth, 2017; Gerten et al., 2020). Climate change directly affects food
4 systems, and the impacts on terrestrial or aquatic food production will become increasingly negative,
5 although regionally some changes may be beneficial in the near future (Porter et al., 2014). Current food
6 system trajectories are leading to biodiversity loss, land and aquatic ecosystem degradation without
7 delivering food security and nutrition, sustainable and healthy livelihoods to many (Steffen et al., 2015).
8 Addressing climate change in isolation ignores these interconnections, which is why the chapter considers
9 integrated adaptation solutions to allow humanity to thrive in the long term. At the same time, social
10 foundations of equality, justice and political participation are crucial in order to move toward a safe
11 operating space for humanity (Raworth, 2017). The SDGs provide the most comprehensive set of metrics of
12 humanity's progress in achieving equitable and thriving socio-ecological systems. Therefore, while the focus
13 of this chapter is climate change impacts, vulnerability and adaptation of food systems, feed, fibre and other
14 ecosystem products, other environmental and social challenges are considered concomitantly.
15
16 Food system and natural systems interact via political, economic, social, cultural, and demographic factors in
17 complex ways, leading to food security and sustainability outcomes. The food system has a supply
18 (production) and demand (consumption) side, connected via processing, trade and retail, with loss and waste
19 streams all along the food chain. Natural ecosystems provide multiple services (regulating, supporting,
20 provisioning, cultural) to the food system. Food security and nutrition strongly depend on the driving forces
21 connecting food and natural systems while at the same time positively or negatively influencing them.
22 Climate change frequently exacerbates the effects of other drivers of change, further limiting the
23 environment within which humanity can safely operate and thrive. The chapter assesses how climate change
24 affects the four pillars of food security and nutrition and how these effects can be mediated by various
25 factors, including our adaptation responses, social equity, underlying ecosystem services and governance
26 (Figure 5.1). Adaptation solutions are a major emphasis of this chapter, including many ecosystem-based
27 adaptation options (Table 5.1), which fall under the broader umbrella of nature-based solutions (Seddon et
28 al., 2020).
29
30 Ecosystem-based adaptation, defined as the "use of ecosystem management activities to increase the
31 resilience and reduce the vulnerability of people and ecosystems to climate change" (Campbell et al., 2009),
32 has at its core the recognition that there are unexploited synergies in agricultural systems that can increase
33 productivity and resilience. These can result from increasing biodiversity, adding organic matter to soils,
34 integrating livestock and aquatic species, including aquaculture, into farming practices, broadening
35 landscape practices to exploit crop-forestry synergies, supporting beneficial insect populations, and altering
36 pest management practices that have unintended negative consequences. In addition, the chapter considers
37 socio-economic strategies to build resilience in the food system, strengthening local and regional economies,
38 building on Indigenous and local knowledge, addressing social inequity, inclusive, participatory and
39 democratic governance of food systems (HLPE, 2019; Wezel et al., 2020).
40
41
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1
2 Figure 5.1: Conceptual framework of Chapter 5
3
4
5 Table 5.1: Adaptation strategies assessment in food, fibre, and other ecosystem provisioning services.
Adaptation Systems Benefits Constraints or Confidence Relevant
strategies/options enablers sections
· Ecosystem-based Crops · Improve Secure tenure High (5.4.4.5,
integrated approaches resilience of arrangements are 5.6.3,
such as agroecology food systems often critical for 5.12.3,
that increase soil delivering Cross-
organic matter, · Provide successful Chapter Box
enhance soil and water mitigation ecosystem-based NATURAL
conservation, and measures and adaptation. in Chapter 2,
diversify food co-benefits in 5.14.3.6,
production systems health, 5.14.3.11;
ecosystem Cross-
· Certain types of urban services and Chapter Box
agriculture other HEALTH in
sustainable Chapter 7)
development
goals
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· Improve
productivity and
yield stability
· Increasing Crops, · Increase Policies and High (5.4.4.4,
agroecosystem Livestock, resilience, technologies that Medium 5.14.3.1,
diversification through Aquacultur productivity, support 5.14.3.6)
-expanding crop, e, Mixed, and diversification at
animal, fish and other Agroforestr sustainability of landscape and farm (5.5.4;
species genetic y systems farming systems levels: programs 5.10.4)
diversity under climate that reward farmers
-varying spatial and Crops- change. for diversification (5.4.4.5,
temporal arrangements livestock practices, reduced 5.6.3,
including mixed mixed · Increase incentives for 5.14.3)
planting, crop system resilience intensified
rotations, integrated particularly monocultures, (5.6.3)
crop, livestock and in the extension support
agroforestry systems tropics and and market
subtropics infrastructure for
· Changing the relative diverse crops, and
emphasis on crops and productivity
livestock research on a greater
variety of crops with
· Changing crop support for post-
varieties and livestock harvest processing
breeds and species and regional
markets
Gender inequalities
can act as a risk
multiplier
· Indigenous and local Crops, · Increase Indigenous High
knowledge including Forestry, resilience and knowledge and local Medium
participatory plant Fisheries sustainability of knowledge can
breeding or food, fibre, facilitate adaptation
community-based Forestry forest, and when combined
adaptation small-scale with scientific
fisheries knowledge and
· Land restoration production utilized in
· Agroforestry management
· Silvo-pasture · Improve regimes.
resilience and Partnerships
productivity between key
stakeholders such as
researchers, forest
managers,
Indigenous and local
forest dependent
communities will
facilitate sustainable
forest management
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· Improved management Fisheries · Promote Governance that Medium (5.14.3.4;
practices that consider sustainable recognizes High Cross-
fish stocks and the Aquacultur harvesting and unexploited Medium Chapter Box
ecosystem (ecosystem- e fair distribution biological and MOVING
based management, of wild fish socioeconomic PLATE this
adaptive management, Freshwater products and food system Chapter)
co-management, fisheries revenues synergies and
adaptive eco- and equity would lead to (5.14.3.5)
management, and aquaculture · Proactive positive adaptation
active adaptive systems, dynamic strategy (5.8.4,
management) fisheries development and 5.9.4.)
management implementation, but
· Adopting and options may be
complementary diversification limited for those
productive activities to based on most at risk due to
reduce economic scientific, technological cost
dependence on Indigenous and and low financial
fisheries local knowledge access
will facilitate Changing
· Developing capacity adaptive precipitation
· Improving information fisheries patterns will
planning and increase competition
flows in adaptive co- reduce conflict for limited
management (national and freshwater supplies.
transboundary international)
resource management over resources.
· Gear or vessel
modifications · Enhance
· Adaptation options sustainable
that incorporate aquaculture
ecological knowledge production
and risk into
management decisions · Reduce the risk
in the near- and long- of food
term insecurity and
livelihood loss
· Effective linkage of for those reliant
freshwater aquatic on freshwater
food provisioning for inland
management to the fisheries and
adaptation plans of aquaculture
other water-using
sectors, considering
trade-offs of
production with
community nutritional
needs
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· Agricultural Mixed · Increase food Uncertainties exist High (5.10.4)
production systems system production per concerning the
that integrate crops, unit of land scalability of (5.11.4)
livestock, forestry, integrated systems; (5.12.4)
fisheries, and · Reduce climate their uptake face (5.12.4)
aquaculture risks particular barriers
around risk, land
· Reduce GHG tenure, social
emission inclusion,
information and
· Confer management skill,
buffering and the nature and
capacity timing of benefit
flows.
· Increasing
· Investments in Post- household The extent to which Medium
improved humidity harvest resilience adaptation activities
and temperature though the beyond harvest are
control in storage Production benefits and cost-effective, and
facilities for perishable and post- challenges the limits to such
items, and changes in harvest depend on local adaptation, are
public policy that context. location-specific and
control international Production largely unknown
trade and domestic and post- · Improve food
market transactions harvest utilization and
access and
· Integrated thereby
multisectoral food resilience to
system adaptation climate change.
approaches that
address food · Protect Differentiated Medium
production, vulnerable responses based on
consumption, and groups against food security level
equity issues. livelihood risks; and climate risk can
be effective.
· Nutrition and gender · Enhance
sensitive agriculture responsiveness
programs, adaptive to extreme
social protection and events
disaster risk
management are · Improved food Focus on Medium
examples. security and meaningful
nutrition for participation in
· Rights-based marginalized governance, design,
approaches, including groups; and implementation
legislation, gender of adaptation
transformative · Increased strategies of those
approaches to resilience groups who are
agriculture, through vulnerable including
recognition of rights to capacity- gender. Can be
land, seeds, fishing building of conflicts and
areas and other natural marginalized tradeoffs, such as
resources, and groups; between addressing
community-based land rights or
adaptation. · Address traditional fishing
questions of grounds.
access to
resources for
marginalized
groups.
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· Climate services Production · Can support For some high- and Medium (5.14.1)
decision-makers in medium-income
agriculture by countries, evidence
providing tailored suggests that climate
information that services have been
can inform the underutilized. In
implementation of low-income
specific adaptation countries, use of
options climate services can
increase yields,
incomes and
promote changes in
farmers' practices,
but 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.
1
2
3 5.2 Observed Impacts and Key Risks
4
5 5.2.1 Detection and Attribution of Observed Impacts
6
7 Detection and attribution of climate change impacts on the food system remain challenging because many
8 non-climate drivers are involved (Porter et al., 2014), but have been improved by recently developed climate
9 model outputs tailored for impact attribution (Iizumi et al., 2018; Moore, 2020; Ortiz-Bobea et al., 2021).
10
11 Climate change has caused regionally different, but mostly negative, impacts on crop yields, quality, and
12 marketability of products (high confidence) (see Section 5.4.1 for observed impacts). There is medium
13 evidence and high agreement that the effects of human-induced climate warming since the pre-industrial era
14 has had significantly negative effects on global crop production, acting as a drag on the growth of
15 agricultural production (Iizumi et al., 2018; Moore, 2020; Ortiz-Bobea et al., 2021). One global study using
16 an empirical model estimated the negative effect of anthropogenic warming trends from 1961 to 2017 to be
17 on average 5.3 % for three staple crops (5.9% for maize, 4.9% for wheat, and 4.2 % for rice) (Moore, 2020).
18 Another study using a process-based crop model found a yield loss of 4.1% (0.5-8.4%) for maize and 4.5%
19 (0.5-8.4%) for soybean between 1981 and 2010 relative to the non-warming condition, even with CO2
20 fertilisation effects (Iizumi et al., 2018). Human-induced warming trends since 1961 have also slowed down
21 the growth of agricultural total factor productivity by 21% (Ortiz-Bobea et al., 2021). Regionally, heat and
22 rainfall extremes intensified by human-induced warming in West Africa have reduced millet and sorghum
23 yields by 10-20%, and 5-15 %, respectively (Sultan et al., 2019).
24
25 Methane emissions significantly impact crop yields by increasing temperatures as a GHG and surface ozone
26 concentrations as a precursor (medium confidence) (Shindell, 2016; Van Dingenen, 2018; Shindell et al.,
27 2019). Shindell (2016) estimated a net yield loss of 9.5±3.0% for four major crops due to anthropogenic
28 emissions (1850-2010), after incorporation of the positive effect of CO2 (6.5±1.0%) and the negative effects
29 of warming (10.9±3.2%) and tropospheric ozone elevation (5.0±1.5%). Although these estimates were not
30 linked with historical yield changes, more than half of the estimated yield loss is attributable to increasing
31 temperature and ozone concentrations from methane emissions, suggesting the importance of methane
32 mitigation in alleviating yield losses (medium confidence) (Section 5.4.1.4).
33
34 Climate change is already affecting livestock production (high confidence) (Section 5.5.1). The effects
35 include direct impacts of heat stress on mortality and productivity, and indirect impacts have been observed
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1 on grassland quality, shifts in species distribution and range changes in livestock diseases (Sections 5.5.1.1
2 5.5.1.3). Quantitative assessment of observed impacts is still limited.
3
4 In aquatic systems, more evidence has accumulated since AR5 on warming-induced shifts (mainly poleward)
5 of species (high confidence) (Section 5.8.1, Cross-Chapter Box MOVING PLATE this Chapter), causing
6 significant challenges for resource allocation between different countries and fishing fleets. Quantitative
7 assessments of climate change impacts on production are still limited, but (Free et al., 2019) estimated a
8 4.1% global loss of the maximum sustainable yield of several marine fish populations from 1930 to 2010 due
9 to climate change. The effects of climate change on aquaculture are apparent but diverse, depending on the
10 types and species of aquaculture (high confidence) (Section 5.9.1). Temperature increases, acidification, salt
11 intrusion, oxygen deficiency, floods, and droughts have negatively impacted production via reduced growing
12 suitability, mortalities, or damages to infrastructure (Section 5.9.1).
13
14 The impacts of climate change on food provisioning have cascading effects on key elements of food security,
15 such as food prices, household income, food safety and nutrition of vulnerable groups (Peri, 2017; Ubilava,
16 2018; 5.11, 5.12 ). Climate extreme events are frequently causing acute food insecurity (Section 5.12.3,
17 FSIN, 2021). There is growing evidence that human-induced climate warming has amplified climate extreme
18 events (Seneviratne et al., 2021), but detection and attribution of food insecurity to anthropogenic climate
19 change is still limited by a lack of long-term data and complexity of food systems (Phalkey et al., 2015;
20 Cooper et al., 2019). A recent event attribution study by Funk (2018) demonstrated that anthropogenic
21 enhancement of the 2015/16 El Niño increased drought-induced crop production losses in Southern Africa.
22 Human-induced warming also exacerbated the 2007 drought in southern Africa, causing food shortages,
23 price spikes, and acute food insecurity in Lesoto (Verschuur et al., 2021).
24
25 5.2.2 Key Risks
26
27 Key risks in this chapter are grouped into those related to food security, food safety and dietary health,
28 livelihoods of people in related sectors and ecosystem services (Table 16.9). Determining when a risk is
29 considered severe is challenging to quantify because of the complexity of the food system, uncertainty about
30 the effects and ethical challenges.
31
32 Current levels of food insecurity are already high in some parts of the world, and often exacerbated by short-
33 term food shortages and price spikes caused by weather extremes partly linked to climate change (Sections
34 5.2.1, 5.12.3, 16.5.2). Climate change will increase malnourished populations through direct impacts on food
35 production and have cascading impacts on food prices and household incomes, all of which will reduce
36 access to safe and nutritious food (high confidence) (Figure 5.2, 5.12).
37
38 Extreme climate events will become more frequent and force some of the current food production areas
39 beyond the safe climatic space for production (high confidence) (Sections 5.4.3, 5.5.2). Globally, 10% of the
40 currently suitable area for major crops and livestock are projected to be climatically unsuitable in mid-
41 century and 31-34% by the end of the century under SSP5-8.5 (Kummu et al., 2021). Adverse effects of
42 climate change on food production will become more severe when global temperatures rise by more than
43 2°C (Sections 5.4.4.1, 5.12.4.1). One study estimated that the heat stress from projected 3°C warming above
44 baseline (1986-2005) would reduce labour capacity by 30-50% in Sub-Saharan Africa and southeast Asia,
45 leading to an 5% increase in crop prices because of higher labour cost and production losses, thereby
46 undermining food availability, access, and livelihood (de Lima et al., 2021). Thiault et al. (2019) projected
47 that by 2100 climate change under RCP8.5 could have negative impacts on both agriculture and marine
48 fisheries productivity in countries where 90% of the world population live. A global analysis of shellfish
49 aquaculture estimated that habitat suitability will decline beyond 2060 globally, but much sooner in some
50 Asian countries (Stewart-Sinclair et al., 2020; 5.9.1 ). These negative effects in the second half of the century
51 will be much less under RCP2.6.
52
53 Climate change impacts will increase the number of people at risk of hunger in 2050 ranging from 8 million
54 people under SSP1 to 80 million people under SSP3 scenarios (RCP6.0), compared to a world with no
55 climate change (Mbow et al., 2019). Estimates also vary depending on the adaptation and mitigation
56 assumptions (Hasegawa et al., 2018; Janssens et al., 2020). Geographically, nearly 80% of the population at
57 risk of hunger are projected to occur in Africa and Asia (Nelson et al., 2018). Projections of risk of hunger
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1 beyond 2050 are limited, but it will grow from the mid-century toward the end of the century, with more
2 people at risk under RCP8.5 compared to RCP4.5 (Richardson et al., 2018). Regional disparity is projected
3 to increase, particularly under a high emission scenario.
4
5
6
7 Figure 5.2: Complex pathways from climate/weather variability to malnutrition in subsistence farming households. The
8 factors involved in and the probable impacts of weather variables on crop yields (blue arrows) and of production on
9 malnutrition (red arrows). Adapted and revised from (Phalkey et al., 2015)
10
11
12 Climate change will increase the costs and management challenges of providing safe food. The safety
13 challenges arise from contamination caused by increased prevalence of pathogens, harmful algal bloom, and
14 toxic inorganic bioaccumulation (high confidence) (Sections 5.8, 5.9, 5.11, 5.12). Micronutrient deficiency is
15 prevalent across many regions and will continue to be a problem at least during the first half of the century
16 (Nelson et al., 2018), with significant implications for human health (Section 5.12.4).
17
18 Food security and healthy balanced diets will also be undermined by reduced livelihoods and health of
19 people in agriculture and food-related sectors (Sections 5.12.3, 5.12.4), diminished ecosystem services
20 provided by pollinators, the soil biome (Section 5.4.3), and water systems, and climate-mitigation related
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1 policies that solely focus on reducing GHG emissions without considering their potential to increase
2 competition with food production for scarce land and water (Section 5.13.3).
3
4
5 5.3 Methodologies and Associated Uncertainties
6
7 Chapter text draws on previous IPCC reports, other reports (i.e., HLPE, FAO, IPBES, and Traffic), and
8 literature published since 2014. This section highlights key trends in research topics and methods since AR5.
9
10 5.3.1 Methodologies for Assessing Impacts and Risks
11
12 Since AR5, there are more examples of observed impacts from past climate change in cropping systems
13 (Section 5.4.1), pastoral systems (Section 5.5.1), forests (Section 5.6.1), fisheries (Section 5.8.1) and in
14 mixed farming systems (Section 5.10.1). These assessments of observed impacts make use of historical data
15 on climate, production area and yield to attribute the role of climate in driving changes in suitability,
16 production, yield, food quality or Total Factor Productivity (Ortiz-Bobea et al., 2021). Observations across
17 the global food-systems have been analysed (Cottrell et al., 2019), with the advantage that unexpected
18 impacts due to changes in seasonality and biotic interactions can be detected. Quantitative analysis is only
19 possible in places with adequate historical data, in many cases studies rely on qualitative assessments, often
20 drawing on farmers perceptions of climate impacts.
21
22 Projecting future climate impacts relies on modelling that combines climate data with data from
23 experimental studies testing how species respond to each climate factor. In cropping and forest systems, a
24 network of experimental studies with plants exposed to elevated CO2 concentrations, ozone and elevated
25 temperature provides data on the fundamental responses to climate and atmospheric conditions (i.e., free-air
26 carbon dioxide enrichment (FACE) and temperature free-air controlled enhancement (T-FACE) systems).
27 FACE results have been combined and assessed more extensively since AR5 (Bishop et al., 2014; Haworth
28 et al., 2016; Kimball, 2016; Ainsworth and Long, 2021; SM5.3). Field-based FACE studies have several
29 advantages over more enclosed testing chambers, although results from more controlled experiments and
30 coordination between different methods continue to give new insights into crop responses to climate change
31 and variability (Drag et al., 2020; Ainsworth and Long, 2021; Sun et al., 2021). Experimental results have
32 limitations and can be difficult to scale up (Porter et al., 2014; Haworth et al., 2016), but generally the
33 conclusions follow known plant responses (Lemonnier and Ainsworth, 2018). As highlighted in AR5, there
34 is a scarcity of FACE infrastructure in the tropics and subtropics (Leakey et al., 2012; Lemonnier and
35 Ainsworth, 2018; Toreti et al., 2020). One area that has been further investigated is the negative impact of
36 elevated CO2 on crop nutritional value, which has important implications for human nutrition (Scheelbeek et
37 al., 2018; Smith and Myers, 2018; Toreti et al., 2020; Ainsworth and Long, 2021). Increasingly,
38 experimental studies seek to examine the interaction between climatic factors such as temperature, drought
39 and ozone, or the responses of understudied food-systems, crop species, cultivars, and management
40 interventions (Kimball, 2016; Ainsworth and Long, 2021). The use of experimental data to improve
41 projections has also expanded in other systems. There has been an increased focus on the impact of warming
42 on livestock health and productivity (5.5.2). Aquatic system studies have incorporated projected impacts on
43 physiology, distribution, phenology, and productivity (5.8.3).
44
45 Modelling approaches differ widely and serve different purposes (Table 5.2; Porter et al., 2014; Jones,
46 2017a). The use of process-based and statistical modelling alongside remote sensing and other spatial data
47 has grown. Projections increasingly draw on a combination of modelling approaches and coordinated efforts
48 for model intercomparisons and ensemble techniques, using standardized emission scenarios (RCPs). For
49 major crops, models of global yield impacts from CO2 concentration, air temperature and precipitation, have
50 been refined and compared (Challinor et al., 2014; Iizumi et al., 2017; Ruane et al., 2017; Zhao et al., 2017;
51 Rojas et al., 2019). Despite advances since AR5, modelling is still constrained by limited data from field
52 experiments (Ruane et al., 2017). Increasingly, studies attempt to incorporate effects of elevated CO2, ozone,
53 and climate extremes (Barlow et al., 2015; Schauberger et al., 2019a; Vogel et al., 2019), as well as attempts
54 to incorporate more complex interactions with soil and crop management (Basso et al., 2018; Smith et al.,
55 2020b). However, only a few models consider crop protein content and other quality factors (Nuttall et al.,
56 2017; Asseng et al., 2019). Some models take account of the impacts of climate on the timing of key
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1 biological events (phenology) in the target species, however incorporating biotic interactions with pests,
2 pathogens, and pollinators remains a challenge (Table 5.2; Sections 5.4.1, 5.4.2).
3
4 In addition to productivity projections, research also draws on climate suitability estimates (Table 5.2). These
5 compare the known climate suitability of species and habitats with projected climate conditions across
6 different locations. Such projections are useful especially for incorporating movement of pests and pathogens
7 but cannot be applied in isolation if non-climate constraints are not considered. As different research groups
8 use different assumptions and data inputs, more coordination is needed if suitability projections are to be
9 compared globally (SM5.3).
10
11 Increasingly, projections look across different disciplines and across multiple components of the food-
12 system, including livestock, fisheries and mixed farming systems (Campbell et al., 2016; Mbow et al., 2019).
13 Major timber species have been modelled, with projected impacts on productivity, duration of rotation and
14 distribution (i.e., climate suitability) (Albert et al., 2018). Livestock systems are influenced by plant
15 productivity projections via their feedstock, e.g., rangeland cattle impacted by changes in net primary
16 production (NPP) (Boone et al., 2018). Direct climate impacts on animals are also projected, using indices
17 based on direct observations (Section 5.5.3). Since AR5, Fish-MIP has allowed for global intercomparisons
18 and ensemble projections of marine fisheries (Fisheries and Marine Ecosystem Model Intercomparison
19 Project), and projections capturing interactions from multiple food systems (e.g., Inter-Sectoral Impact
20 Model Intercomparison Project (ISIMIP); Sections 5.8, 5.10).
21
22 Global simulations have uncovered important differences between regions (Deryng et al., 2016; Blanchard et
23 al., 2017). Efforts to coordinate and combine regional and global modelling studies allow for greater insight
24 into regional differences in climate change impacts, e.g., the Coordinated Global and Regional Assessments
25 (CGRA) performed by the Agricultural Model Intercomparison and Improvement Project (AgMIP)
26 (Blanchard et al., 2017; Müller et al., 2017; Rosenzweig et al., 2018; Ruane et al., 2018; Lotze et al., 2019).
27 Increasingly, multi-model intercomparisons are used to evaluate global gridded crop models' performance
28 and sensitivity to temperature, water, nitrogen, and CO2 within AgMIP, with the focus mostly on major
29 annual crops (Valdivia et al., 2015; Ruane et al., 2017; Müller et al., 2021a). Differences in model type,
30 structures and input data can result in large variation in projections, particularly for the response of crops to
31 elevated CO2 and temperature (5.4.3.1), methods for quantifying and minimizing this uncertainty have been
32 developed, but improvement is still needed (Li et al., 2014b; Asseng et al., 2015; Zhao et al., 2017; Folberth
33 et al., 2019; Tao et al., 2020; Müller et al., 2021a; Ruane et al., 2021). The use of multi-model
34 intercomparisons has widened the range of uncertainties but has increased the robustness of impact
35 assessments (Asseng et al., 2013; Challinor et al., 2014; Zhao et al., 2017). Model outputs are strongly
36 influenced by decisions over which factors to include, e.g., including drought impacts can result in positive
37 yield projections switching to neutral or negative values (Gray et al., 2016; Jin et al., 2018). Models are also
38 limited in their ability to incorporate socio-economic drivers and extreme events (Porter et al., 2014;
39 Campbell et al., 2016; Ruane et al., 2017; Jagermeyr and Frieler, 2018; Webber et al., 2018; Schewe et al.,
40 2019).
41
42 For long-term projections and integrated assessments, a large component of uncertainty remains the ability to
43 represent socio-economic responses to climate change and the degree to which these will mitigate or
44 exacerbate climatic changes (Valdivia et al., 2015; Prestele et al., 2016; Arneth et al., 2019). This includes
45 the potential adaptation responses of food producers. Models that incorporate alternative socio-economic
46 responses offer one solution (e.g., AgMIP) (Nelson et al., 2014; Von Lampe et al., 2014; Wiebe et al., 2015;
47 Rosenzweig et al., 2018; van Zeist et al., 2020). Another approach is the use of solution-oriented scenarios to
48 compare the effectiveness of adaptation options (Le Mouël and Forslund, 2017; Arneth et al., 2019), or to
49 quantify the time period in which adaptation responses will become essential (Challinor et al., 2016; Rojas et
50 al., 2019). Others point to the necessity of managing food systems within the context of uncertainty
51 (Campbell et al., 2016).
52
53
54 Table 5.2: A comparison of modelling approaches and their application in climate change impact projections. Model
55 types are categorised by: food system, with labels representing the food systems from this chapter where each model
56 type is used ([CROP], [TREE], [LIVES], [FISH], [MIX], [FOOD]); scale over which each model type is usually
57 applied (local [()], regional [( )], global [( )], or a combination of these); and sensitivity to climate change where the
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1 colour intensity indicates the ability of each model type to incorporate each of the listed factors. After (Van Wijk et al.,
2 2014; Kanter et al., 2018; Thornton, 2018). Integrated assessment models are discussed in the main text.
Description Applications for each food-system Scale Sensitivity to climate change
factors and responses
Climate
CO2
Biotic
Adaptation
System
responses
Use simple equations to link agricultural Comparing regions; matching crops to regions;
Agroclimatic performance to key climate factors, such as early warning systems: e.g. Agro-ecological
indices drought or heat stress, or summarising zones, Ecocrop, Palmer Drought Severity Index (( ))
agricultural requirements using multiple
{CROP}.
Empirical environmental descriptors.
Statistical models Use quantitative associations between Productivity and production area projections;
agricultural performance and climate, based annual climate variability; attribution: e.g.
on past observations. Can include Traditional: regression, statistical emulators (( ))
projections for biotic factors such as pest {CROP} {TREE} {LIVES} {FISH}; e.g.
and disease. Spatial suitability models /niche models: MaxEnt,
CLIMEX, Ecocrop {CROP} {TREE} {FISH}.
Vegetation focused Use combinations of land-surface energy Productivity projections; interactions with non-
and soil water balance models to simulate climate variables (e.g. CO2): e.g. PEGASUS,
Process-based (dynamic simulation models) the growth of crop species along with natural Agro-IBIS, DayCent, LPJmL, LPJ-GUESS,
vegetation, typically using plant and crop ORCHIDEE {CROP} {TREE}. ( )
functional types.
Use mechanistic models based on the known Productivity projections; matching tree species to
responses of species to key environmental locations; species interactions; interactions with
descriptors over time. Typically based on non-climate variables (e.g.CO2); adaptation
Species focused detailed information for a particular species projections: e.g. point-based versions: APSIM,
within a region, but also applied to mixed AquaCrop, DayCent, DSSAT, EPIC, Infocrop,
systems such as agroforestry and globally. SARRA-H, STICS {CROP} IBIS {TREE} (( ))
LIVSIM, RUMINANT {LIVES} Fish-MIP
{FISH} Yield-SAFE, WaNuLCAS, Hi-sAFe
{MIX}; e.g. global gridded version: pDSSAT,
pAPSIM, GEPIC, GLAM, MCWLA,
PEGASUS, SARRA-O {CROP}.
Mathematical representations of systems Adaptation projections; food security
Optimization with regard to key indicators, constraints, projections; livelihood projections; trade-offs;
methods
and objectives. Allows prioritisation of live cycle assessment: e.g. Global Timber Model ()
different climate change response options {TREE} CSAP toolkit, FarmDESIGN
using the defined indicators. {CROP} {MIX} {FOOD}
Economic Used to integrate the broad impacts of Adaptation projections; food security
(Econometric,
Economic surplus, climate change with other economic drivers, projections; livelihood projections: e.g. GFPM
to quantify the economic costs and assess {TREE} FUND 3.8, DICE 2010, IMPACT ( )
Integrated models the value of adaptation/mitigation {FOOD}
interventions.
Household and Use detailed site-specific data to generate Adaptation projections (case specific);
village models
rules that describe the current behaviour of behavioural responses; trade-offs; participatory
stakeholders such as households or villages. monitoring: e.g. DECUMA, PALM, MPMAS,
Can be integrated with other model MIDAS, TOA-MD {LIVES} {MIX} {FOOD} (())
approaches to consider climate response
and adaptation interventions.
3
4
5
6 5.3.2 Methodologies for Assessing Vulnerabilities and Adaptation
7
8 Methods for monitoring vulnerability and adaptation are under-researched but have increased since AR5.
9 Increasingly, projections move from individual crops, to assessing risks across the food systems and the
10 relative vulnerability of different systems (Campbell et al., 2016; Gil et al., 2017; Lipper et al., 2017;
11 Richardson et al., 2018). Adaptation options can be considered as parameters in integrated models, such as
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1 those used in ISI-MIP, while others use systematic assessments of case studies, e.g., the application of agent-
2 based household models to assessments of adaptation in livestock systems (Section 5.5.4). Quantitative
3 studies are less common than qualitative assessments and there is a need to combine modelling and
4 qualitative approaches more effectively (Beveridge et al., 2018a; Vermeulen et al., 2018).
5
6 The food system is dynamic with changes in management practices driven by many factors including climate
7 adaptation (Iizumi, 2019; Iizumi et al., 2021a). Adaptation potential, such as expected advances in crop
8 breeding, are often not explicitly accounted for in modelling studies, but more recent studies do quantify the
9 potential for adaptation (Iizumi et al., 2017; Tao et al., 2017; Aggarwal et al., 2019; Minoli et al., 2019). To
10 account for this complexity, case studies rely on data derived from the perception and practices of
11 stakeholders who are engaged in adaptation (usually autonomous adaptation) (Hussain et al., 2016; Lipper et
12 al., 2017; Ankrah, 2018; Sousa-Silva et al., 2018). Case studies use a range of different indicators to monitor
13 climate response options, making quantitative comparisons more difficult (Gil et al., 2017; Vermeulen et al.,
14 2018). However, systematic comparisons have provided valuable insights (Descheemaeker et al., 2018;
15 Shaffril et al., 2018; Aggarwal et al., 2019; Bene et al., 2019), e.g., the sustainable livelihood framework has
16 been applied widely to diverse aquatic systems (Bueno and Soto, 2017; Barange and Cochrane, 2018) and
17 the Livelihood Vulnerability Index is well used across systems (Section 5.14). Coordinated efforts such as
18 the AgMIP also provide systematic assessments (Blanchard et al., 2017; Lipper et al., 2017; Antle et al.,
19 2018). Nonetheless, the full effectiveness of different adaptation options is difficult to assess given that many
20 impacts have not yet occurred (due to the cumulative nature of impacts and the inertia in the climate system
21 (Stocker et al., 2013; Zickfeld et al., 2013).
22
23 Transformation of the food system that addresses all dimensions of ecosystem services is discussed in this
24 chapter, including risk management and the communication of uncertainties (Section 5.14). The focus is on
25 flexible approaches to risk and uncertainty, assessing trends, drivers, and trade-offs under different future
26 scenarios (Campbell et al., 2016).
27
28
29 5.4 Crop-based Systems
30
31 Crops such as cereals, vegetables, fruit, roots, tubers, oilseeds, and sugar account for about 80 % of the
32 dietary energy supply (FAO, 2019f). Crops are a significant source of food and income for about 600 million
33 farms in the world, 90 % of which are family farms (Lowder et al., 2019). Previous assessment reports
34 focused on yields of staple crops such as maize, wheat and rice, but studies are emerging on climate change
35 impacts on other crops.
36
37 5.4.1 Observed Impacts
38
39 5.4.1.1 Observed impacts on major crops
40
41 AR5 Chapter 7 stated with confidence that warmer temperatures have benefited agriculture in the high
42 latitudes, and more evidence has been published to support the statement. Typical examples include pole-
43 ward expansion of growing areas and reduction of cold stress in East Asia and North America (Table
44 SM5.1).
45
46 Recent warming trends have generally shortened the life cycle of major crops (high confidence) (Zhang et
47 al., 2014; Shen and Liu, 2015; Ahmed et al., 2018; Liu et al., 2018c; Tan et al., 2021). Some studies,
48 however, observed prolonged crop growth duration despite the warming trends (Mueller et al., 2015; Tao et
49 al., 2016; Butler et al., 2018; Zhu et al., 2018b) due to shifts in planting dates and/or adoption of longer-
50 duration cultivars in mid to high latitudes. Conversely, in mid-to-low latitudes in Asia, a review study found
51 that farmers favoured early maturing cultivars to reduce risks of damages due to drought, flood and/or heat
52 (Shaffril et al., 2018), suggesting that region-specific adaptations are already occurring in different parts of
53 the world (high confidence).
54
55 Global yields of major crops per unit land area have increased 2.5 - 3-fold since 1960. Plant breeding,
56 fertilisation, irrigation, and integrated pest management have been the major drivers, but many studies have
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1 found significant impacts from recent climate trends on crop yield (high confidence) (Figure 5.3; See Section
2 5.2.1 for the change attributable to anthropogenic climate change).
3
4 Climate impacts for the past 20-50 years differ by crops and regions. Positive effects have been identified for
5 rice and wheat in Eastern Asia, and for wheat in Northern Europe. The effects are mostly negative in Sub-
6 Saharan Africa, South America and Caribbean, Southern Asia, Western and Southern Europe. Climate
7 factors that affected long-term yield trends also differ between regions. For example, in Western Africa, 1°C-
8 warming above preindustrial climate has increased heat and rainfall extremes, and reduced yields by 10-20%
9 for millet, and 5-15 % for sorghum (Sultan et al., 2019). In Australia, declined rainfall and increased
10 temperatures reduced yield potential of wheat by 27%, accounting for the low yield growth between 1990
11 and 2015 (Hochman et al., 2017). In Southern Europe, climate warming has negatively impacted yields of
12 almost all major crops, leading to recent yield stagnation (Moore and Lobell, 2015; Agnolucci and De Lipsis,
13 2020; Brás et al., 2021).
14
15
16
17 Figure 5.3: Synthesis of literature on observed impacts of climate change on productivity by crop type and region. The
18 figure draws on >150 articles categorised by: agriculture total factor productivity including literature estimating all
19 agricultural outputs in a region; major crop species including literature assessing yield changes in the four major crops;
20 crop categories including productivity changes (yield, quality, and other perceived changes) in a range of crops with
21 different growth habits. The assessment uses literature published since AR5, although the timespan often extends prior
22 to 2014. The direction of the effect and the confidence are based on the reported impacts and attribution, and on the
23 number of articles. See SM5.1 and SM5.2 for details.
24
25
26 Ortiz-Bobea et al. (2021) analysed agricultural Total Factor Productivity (TFP), defined as the ratio of all
27 agricultural outputs to all agricultural inputs, and found that while TFP has increased between 1961 and
28 2015, the climate change trends reduced global TFP growth by a cumulative 21% over a 55-year period
29 relative to TFP growth under counterfactual non-climate change conditions. Greater effects (30- 33%) were
30 in Africa, Latin America and the Caribbean (Figure 5.3).
31
32 Climate variability is a major source of variation in crop production (Ray et al., 2015; Iizumi and
33 Ramankutty, 2016; Frieler et al., 2017; Cottrell et al., 2019)(Table SM5.1). Weather signals in yield
34 variability are generally stronger in productive regions than in the less productive regions (Frieler et al.,
35 2017), where other yield constraints exist such as pests, diseases, and poor soil fertility (Mills et al., 2018;
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1 5.2.2). Nevertheless, yield variability in less productive regions has severe impacts on local food availability
2 and livelihood (high confidence) (FAO, 2021).
3
4 Climate-related hazards that cause crop losses are increasing (medium evidence, high agreement) (Cottrell et
5 al., 2019; Mbow et al., 2019; Brás et al., 2021; FAO, 2021; Ranasinghe et al., 2021). Drought-related yield
6 losses have occurred in about 75% of the global harvested area (Kim et al., 2019b) and increased in recent
7 years (Lesk et al., 2016). Heatwaves have reduced yields of wheat (Zampieri et al., 2017) and rice (Liu et al.,
8 2019b). The combined effects of heat and drought decreased global average yields of maize, soybeans, and
9 wheat by 11.6, 12.4, and 9.2% (Matiu et al., 2017). In Europe, crop losses due to drought and heat have
10 tripled over the last five decades (Brás et al., 2021), pointing to the importance of assessing multiple stresses.
11 Globally, floods also increased in the past 50 years, causing direct damages to crops and indirectly reduced
12 yields by delaying planting, which cost 4.5 billion USD in the 2010 flood in Pakistan and 572 million USD
13 in the 2015 flood in Myanmar (FAO, 2021).
14
15
16 [START BOX 5.1 HERE]
17
18 Box 5.1: Evidence for Simultaneous Crop Failures due to Climate Change
19
20 Simultaneous yield losses across major producing regions can be a threat to food security but had not been
21 quantified by the time of AR5. Large-scale sea surface temperature (SST) oscillations greatly influence
22 global yield of major crops (high confidence) (Anderson et al., 2019b; Najafi et al., 2019; Ubilava and
23 Abdolrahimi, 2019; Heino et al., 2020; Iizumi et al., 2021b) and food prices (Ubilava, 2018). Some studies
24 showed that crop yields in different regions covaried with SST oscillations, suggesting occurrences of tele-
25 connected yield failures (crop losses caused by related factors in distant regions; Table Box 5.1.1) (medium
26 confidence). Evidence is still limited that synchronised crop failures are increasing with ongoing climate
27 change.
28
29
30 Table Box 5.1.1: A summary of peer-review papers detecting synchronised yield losses
Regions/ Period Observed impacts Climate Evide Evidenc Reference
Commodities studied driver nce e for
for increasi
multi ng risks
ple due to
bread multiple
baske breadba
t sket
failur failures
es
Global 1961- Not only yields of each crop Sea surface High NA Najafi et al.
breadbaskets for 2013 (2019)
maize, rice, covaried in many countries, but temperatur
sorghum and
soybean also that of different crops, e
maize in particular, covaried anomalies
with other crops. (SST),
atmospheri
c and
oceanic in-
dices, air
temperatur
e
anomalies
(AT) and
Palmer
Drought
Severity
Index
(PDSI)
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Global Climate modes (El Niño Climate Medi NA Anderson et
breadbaskets for Southern Oscillation (ENSO), modes um al. (2019b)
wheat, soybean, the Indian Ocean Dipole (IOD), (1983
and maize tropical Atlantic variability )
(TAV), and the North Atlantic
Oscillation (NAO) ) account for
18, 7, and 6% of global maize,
wheat, and soybean production
variability. ENSO events
sometimes offset yield
reductions in some places by
increases in other places (e.g.,
Soybean yields in the United
States and southeast South
America).
Since 1961, ENSO in 1983 was
the only climate mode that
showed global synchronous
crop failures.
Global Climate modes induce yield Climate Medi NA Heino et al.
breadbaskets for variability in major modes um NA (2020)
wheat, soybean, breadbaskets. e.g. ENSO affects
and maize about half of maize and wheat Climate Medi medium Ubilava and
areas. IOD and ENSO influence modes um Abdolrahimi
67 maize 1961- what in Australia. ENSO affects (Sea (2019)
producing 2017 soybean in northern South surface medi
countries America. temperatur um Gaupp et al.
SST anomalies from the 1980 e), (2020)
Global 1967- 2010 base period in the Niño3.4 Precipitati
breadbasket (the 2012 region, a rectangular area on
United States, bounded by 120W170W and
Argentina, 5S5 is used as a driver. Unspecifie
Europe, Maize yields are tele-connected d
Russia/Ukraine, among the south-eastern tier of
China, India, Sub-Saharan Africa, as well as
Australia, Central America, South Asia,
Indonesia, and and Australia. A 1-degree
Brazil) increase in SST reduced maize
yield by up to 20% in these
countries.
Likelihood of simultaneous
climate risks increased from
1967-1990 to 1991-2012 in the
global breadbasket (Lower 25th
yield deviation percentile events
at province level) for wheat,
soybean maize, but not rice.
Likelihood of simultaneous
climate risks increased from
1967-1990 to 1991-2012 in
China (Lower 25th yield
deviation percentile events at
province level)
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Global Synchronous yield losses among unspecifie medi medium Mehrabi and
major breadbaskets within each d um Ramankutty
commodity, such as maize and (2019)
soybean decreased between
1961 and 2008. In contrast,
synchronous yield variation
between crops has increased.
Under a scenario of
synchronization of all four
crops, the global maximum
production losses for rice,
wheat, soybean, and maize are
estimated to reach between
-17% and -34%.
1
2
3 [END BOX 5.1 HERE]
4
5
6 5.4.1.2 Observed impacts on other crops (vegetables, fruit, nut, and fibre)
7
8 The impact of climate change on these diverse crop types is under-researched and uncertain (Manners and
9 van Etten, 2018; Alae-Carew et al., 2020), there are reports of positive impacts in some cases but overall, the
10 observed impacts are negative across all crop categories (Figure 5.3).
11
12 Above-ground annual crops consumed as vegetables, fruits, or salad are essential for food security and
13 nutrition (5.12). In temperate regions, climate change can result in higher yields (Potopová et al., 2017;
14 Bisbis et al., 2018), while in subtropical/tropical regions, negative impacts from heat and drought take
15 precedence (Scheelbeek et al., 2018). Different species have different sensitivities to heat and drought
16 (Prasad et al., 2017; Scheelbeek et al., 2018) and to combinations of stresses (Zandalinas et al., 2018).
17 Above-ground vegetables are especially vulnerable to heat and drought stress during pollination and fruit set,
18 resulting in negitive impacts on yiled (Daryanto et al., 2017; Sita et al., 2017; Brás et al., 2021)and harvest
19 quality (Mattos et al., 2014; Bisbis et al., 2018). Growers have already seen negative impacts from the
20 expansion of pest and disease agents due to warming (Section 5.4.1.3; Figure 5.3).
21
22 Below-ground vegetables include starchy roots and tubers that form a regular diet in many parts of the
23 tropics and sub-tropics. Warming and climate variability has altered the rate of tuber development with yield
24 impacts varying by location, including yield increases in some cases (Shimoda et al., 2018; Ray et al., 2019).
25 These crops are considered stress tolerant but are more sensitive to drought than cereals (Daryanto et al.,
26 2017). Impacts on water supply are critical as root crops are water-demanding for long periods, and highly
27 sensitive to drought and heat events during tuber initiation (Dua et al., 2013; Potopová et al., 2017; Brás et
28 al., 2021).
29
30 Among perennial tree crops, only grapevine, olive, almond, apple, coffee, and cocoa have received
31 significant research attention. Concerns about climate impacts on harvest quality are widespread (Figure 5.3)
32 (Barnuud et al., 2014; Bonada et al., 2015). In higher-latitude regions, the primary concern is the effect of
33 temperature variability on harvest stability, pests and diseases and phenology (including fulfilment of winter
34 chill requirements and risks due to early emergence in spring), (El Yaacoubi et al., 2014; Ramírez and
35 Kallarackal, 2015; Santos et al., 2017; Gitea et al., 2019). In lower-latitude regions, information is limited,
36 but studies are focused on increased tree mortality and yield loss due to drought, heat, and impacts from
37 variability in the timing of the wet and dry seasons (Glenn et al., 2013; Ramírez and Kallarackal, 2015); see
38 Box 5.7). In fruit trees, warming and climate variability have already affected fruit quality, such as acidity
39 and texture in apples, or skin colour in grape berries (Sugiura et al., 2013; Sugiura et al., 2018). The
40 reliability and stability of harvests has been impacted by climate variability, changes in the distribution of
41 pests and pathogens (Seidel, 2014; Bois et al., 2017), and by the mismatch of important phenological events
42 (such as bud emergence and flowering) (Guo and Shen, 2015; Legave et al., 2015; Ito et al., 2018; Vitasse et
43 al., 2018). Perennial crops are particularly vulnerable to these impacts as they are exposed throughout the
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1 year, with little potential for growers to adjust planting date or location. Negative impacts via disruption to
2 phenology and pest dynamics are best studied in grapevine (see Box 5.2).
3
4 Among the fibre crops, cotton is particularly well studied. As cotton is heat tolerant and yield increases with
5 extra plant growth, positive effects of increasing temperature are expected, but observed impacts have been
6 mixed due to negative impacts on phenology and plant water status (Traore et al., 2013; Chen et al., 2015a;
7 Cho and McCarl, 2017). Negative impacts of climate change due to proliferation of the pest cotton bollworm
8 are widely reported (Ouyang et al., 2014; Huang and Hao, 2020).
9
10 The impacts of climate change on water availability (rainfall and irrigation supply) are an emerging issue.
11 Increased occurrence of drought combined with limited access to irrigation water is already a key constraint,
12 e.g., Californian almonds are predicted to increase their potential geographical range under climate warming
13 (Parker, 2018), yet a trend of increasing drought has already resulted in trees being removed due to lack of
14 access to irrigation water (Keppen and Dutcher, 2015; Kerr et al., 2018; Reisman, 2019).
15
16 5.4.1.3 Observed impacts on pests, diseases, and weeds
17
18 AR5 and SRCCL indicated that more frequent outbreaks and area expansion of pests and diseases are serious
19 concerns under climate change but are under-researched because of the difficulties in assessing multi-species
20 interactions (Porter et al., 2014; Mbow et al., 2019). High-quality historical and current observational data to
21 detect changes in pests and diseases attributable to recent trends in climate are still limited.
22
23 Bebber (2013) found significant poleward expansions of many important groups of crop pests and pathogens
24 since 1960, with an average shift of 2.7 km yr-1. Different pest species populations respond differently to
25 ongoing climate change, with some shifting, contracting, or expanding their current distribution range and
26 others persisting or disappearing in their current range (high confidence). These asymmetric distribution
27 changes can create novel species combinations or decouple existing ones (Pecl et al., 2017; Hobbs et al.,
28 2018), but their consequences on future crop production and food security are hard to predict. Multi-species
29 climate change experiments are rare (Bonebrake et al., 2018) but one study shows that under future climates,
30 different pest assemblages of interacting species may alter levels of damage to crops compared to that by
31 only one species (Crespo-Perez et al., 2015). Some studies highlight the importance of location-specific
32 species interactions for more realistic projections of pest distribution, performance, and damage to crops,
33 which in turn would allow more effective prevention and pest control strategies (Wilson et al., 2015;
34 Carrasco et al., 2018).
35
36 Weeds are recognized as a primary constraint on crop production (Oerke, 2006), rangelands (DiTomaso et
37 al., 2017) and forests (Webster et al., 2006). Climate change could favour the growth and development of
38 weeds over crops with negative consequences for desired plants in managed systems (medium evidence, high
39 agreement) (Peters et al., 2014; Ziska and McConnell, 2016). First, changes in temperature and precipitation
40 alter the range, composition, and competitiveness of native and invasive weeds (Bradley et al., 2010).
41 Second, rising concentrations of CO2 enhance growth of C3 species (~85% of plant species, including many
42 weeds) (Ogren and Chollet, 1982; Ziska, 2003), and increase plant water use efficiency with potentially
43 strong effects on invasive plant species establishment (Smith et al., 2000; Belote et al., 2004; Blumenthal et
44 al., 2013).
45
46 Some invasive species within unmanaged areas will expand further, proliferate and be more competitive
47 under climate change as they may benefit from increased resource ability (e.g., additional CO2, enhanced
48 precipitation) (Bradley et al., 2010; Kathiresan and Gualbert, 2016; Merow et al., 2017; Ramesh et al., 2017;
49 Waryszak et al., 2018), which will make chemical weed-control more problematic (medium evidence, high
50 agreement) (Waryszak et al., 2018; Ziska, 2020). The range of other invasive weeds may become static, or
51 even decline (Bradley et al., 2016; Buckley and Csergo, 2017). A recent meta-analysis also supports that
52 invasive plants respond more favourably to elevated CO2 concentrations and elevated temperatures than
53 native plants (Korres et al., 2016; Liu et al., 2017). Movement of invasive species into low fertility areas,
54 however, could provide resource opportunities, especially if agriculture in those areas is limited
55 (Randriambanona et al., 2019).
56
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1 Rising CO2 concentrations and climate change could reduce herbicide efficacy (medium evidence, high
2 agreement). These reductions may be associated with physical environmental changes (precipitation, wind
3 speed) that influence herbicide coverage (Ziska, 2016), as well as direct effects of CO2 on plant biochemistry
4 and herbicide resistance (Refatti et al., 2019). Increasing CO2 levels and altered temperature and
5 precipitation, are therefore projected to affect all aspects of weed biology (Peters et al., 2014; Ziska and
6 McConnell, 2016), including establishment (Bradley et al., 2016), competition (Fernando et al., 2019),
7 distribution, (Castellanos-Frías et al., 2016), and management (Waryszak et al., 2018).
8
9 A warmer climate increases the need for pesticides (Shakhramanyan et al., 2013; Ziska, 2014; Delcour et al.,
10 2015; Zhang et al., 2018). Increases in temperature and CO2 concentration may reduce pesticide efficiency
11 by altering its metabolism, or accelerating detoxification (Matzrafi et al., 2016; Matzrafi, 2019). Intense
12 rainfall also reduces persistence (Delcour et al., 2015). Invasive pests and pathogens impose an additional
13 cost for the society (Bradshaw et al., 2016). Rapid and large-scale dispersal of pests is already a major threat
14 to food security, as exemplified by the recent outbreak of desert locusts (see Box 5.8), indicating the
15 importance of international cooperation. Taken together, the need for control of pests, disease and weeds will
16 increase under climate change (medium evidence, high agreement). The use of toxic agricultural chemicals
17 also has human health and environmental risks (Whitmee et al., 2015; IPBES, 2019). Surveillance for
18 monitoring pest distribution and damages, climate-relevant pest-risk analysis, and climate-smart strategies
19 for controlling pests with minimal impacts on human and environmental health are important tools in the
20 face of climate change (IPPC Secretariat, 2021).
21
22 5.4.1.4 Observed impacts of ozone on crops
23
24 Tropospheric (i.e., the lowest 610 km of the atmosphere) ozone exacerbates negative impacts of climate
25 change (high confidence) (Mattos et al., 2014; Chuwah et al., 2015; McGrath et al., 2015; Bisbis et al., 2018;
26 Mills et al., 2018; Scheelbeek et al., 2018). Ozone is an air pollutant and short-lived greenhouse gas that
27 affects air quality and global climate. It is a strong oxidant that reduces physiological functions, yield and
28 quality of crops and animals. Surface ozone concentration has increased substantially since the late 19th
29 century (Cooper et al., 2014; Forster et al., 2021; Gulev et al., 2021; Naik et al., 2021)and in some locations
30 and times reaches levels that harm plants, animals, and human (high confidence) (Fleming et al., 2018).
31
32 Mills (2018) estimated global distributions of current yield losses of major crops due to ozone, pest and
33 diseases, heat, and aridity (Figure 5.4). Ozone-induced yield losses in 2010-2012 averaged 12.4, 7.1, 4.4, and
34 6.1 % for soybean, wheat, rice, and maize, respectively. Spatial variation in yield losses is similar among
35 different stresses; areas with a large loss due to ozone are also at high risk of yield losses due to pest and
36 diseases and heat. Many vegetable crops are also susceptible to ozone, which will adversely impact quality
37 and quantity (Mattos et al., 2014; Bisbis et al., 2018; Scheelbeek et al., 2018).
38
39
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1
2 Figure 5.4: The global effects of five biotic and abiotic stresses on soybean and wheat. All data are presented for the
3 1 × 1° (latitude and longitude) grid squares where the mean production of soybean or wheat was >500 tonnes
4 (0.0005 Tg). The effect of each stress on yield is presented as a Yield Constraint Score (YCS) on a scale of 15, where
5 5 is the highest level of stress from ozone, pests and diseases, heat stress and aridity (Mills et al., 2018). Data are
6 available at Sharps et al.,(2020). See Annex I: Global to Regional Atlas for all four crops.
7
8
9 The estimated yield loss does not account for interactions with other climatic factors. Temperatures enhance
10 not only ozone production but also ozone uptake by plants, exacerbating yield and quality damage. Burney
11 (2014) estimated current yield losses due to the combined effects of ozone and heat in India at 36% for wheat
12 and 20 % for rice. Schauberger et al. (2019a) found global yield losses, ranging from 2 to 10 % for soybean
13 and 0 to 39 % for wheat with a model that accounts for temperature, water, and CO2 concentration on ozone
14 uptake.
15
16 5.4.2 Assessing Vulnerabilities within Production Systems
17
18 Since AR5, vulnerability assessment has become a pivotal component of risk analysis associated with
19 climate hazards, climate change and climate variability (UNDRR, 2019). Vulnerability assessment can be
20 sectoral or regional but involves social and ecological indicators. This section presents examples of
21 vulnerability assessment to climatic hazards and social vulnerabilities.
22
23 5.4.2.1 Vulnerability to climatic hazards
24
25 Drought is a major risk component in cropping systems globally, with substantial economic loss (Kim et al.,
26 2019b), livelihood impacts (Shiferaw et al., 2014; Miyan, 2015), and ultimately health risks such as
27 malnutrition (Phalkey et al., 2015; Cooper et al., 2019). Vulnerability to drought can be estimated with a
28 range of indicators (Hagenlocher et al., 2019). Meza (2020) showed that drought risks could be exacerbated
29 or moderated by regional differences in vulnerability (Figure 5.5). For instance, high-level risks observed in
30 southern Africa, western Asia, and central Asia result from high vulnerability (low coping capacity), whereas
31 risk levels are relatively low despite the high exposure by relatively high adaptive capacity to drought in
32 other regions.
33
34
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2 Figure 5.5: Hazard and exposure indicator score (a), vulnerability index (b) and drought risk index (c), for rainfed
3 agricultural systems between 1986 and 2015. Drought hazard indicator is defined as the ratio of actual crop
4 evapotranspiration to potential crop evapotranspiration, calculated for 24 crops. Vulnerability index is the country-scale
5 weighted average of a total of 64 indicators including social and ecological susceptibility indicators, and coping
6 capacity. Risk index is calculated by multiplying hazard/exposure indicator score and vulnerability index (Meza et al.,
7 2020).
8
9
10 Regional-scale assessment also highlights the importance of adaptive capacity. For instance, rice and maize
11 production in Viet Nam Mekong Delta has high exposure to multiple climate hazards such as flooding, sea-
12 level rise, salinity intrusion, and drought (Parker et al., 2019). Risks can be moderated by a relatively high
13 adaptive capacity because of infrastructure, resources, and high education levels (Parker et al., 2019).
14 Another regional study demonstrated that erratic rains and high temperatures in southern and south-eastern
15 Africa increased the vulnerability of agricultural soils, thereby exacerbating impacts of prolonged and
16 frequent droughts (Sonwa et al., 2017a; See also Box 5.4).
17
18 Farm-scale assessment exemplifies context-sensitive vulnerability to climate hazards. Studies of coffee
19 growers in Central America demonstrated that key vulnerability indicators varied greatly between regions
20 and between farms, ranging from a lack of labour, postharvest infrastructure, conservation practices and
21 transport that limits access to market, technical and financial assistance (Baca et al., 2014; Bouroncle et al.,
22 2017). These region- and scale-specific vulnerability indicators assist in identifying ways to enhance
23 resilience to climate hazards (high confidence).
24
25 5.4.2.2 Inequalities in cropping systems- other crops and regional disparities
26
27 While those working with major crops have benefited from the release of new cultivars, those growing other
28 crops are typically reliant on a heritage cultivars or landraces. While Indigenous knowledge and local
29 smallholder knowledge and practices play an important role in supporting agrobiodiversity which provides
30 genetic diversity resistant to climate-related stresses, a global and national focus in international research,
31 subsidies and support for a few crop species has contributed to an overall decline in agrobiodiversity (FAO,
32 2019e; Song et al., 2019) Similarly, there is a lack of agronomic innovation and research to service `minor'
33 crops (Moriondo et al., 2015; Manners and van Etten, 2018). Even some high value commodities grown
34 outside high-income countries suffer from imbalances in the focus of available credit, research, and
35 innovation (Section 5.4.4.3; Glover, 2014; Fischer, 2016; Farrell et al., 2018). There is a possibility that a
36 lack of adaptive capacity and policy support will drive these growers to move away from these diverse crops,
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1 further reducing the resilience of food systems by increasing risk of crop loss from pests, disease and drought
2 and potential loss of Indigenous or local knowledge (Section 5.13.5, Table Box 5.1.1). In the Andean
3 Altiplano of Bolivia, for example, Indigenous farmers have traditionally managed a diverse set of native
4 crops which are drought and frost-tolerant, using cultural practices of seed selection and exchange, but have
5 faced an increase in pests and diseases and a decline of traditional crops due to climate change related
6 stresses, out-migration and intensification drivers (Meldrum et al., 2018).
7
8 5.4.2.3 Gender and other social inequalities
9
10 Social inequalities such as gender, ethnicity, and income level, which vary by time and place and may
11 overlap, can compound vulnerability to climate change for producers within cropping systems (high
12 confidence) ( Table 5.3, Arora-Jonsson, 2011; Djoudi et al., 2013; Carr and Thompson, 2014; Mbow et al.,
13 2019; Rao et al., 2019a; Nyantakyi-Frimpong, 2020a). Rather than binary and static categories (i.e., men vs
14 women), social vulnerabilities are dynamic and intersect; to understand vulnerability the specific socio-
15 cultural identities, political and environmental context needs to be studied in relation to climate stress
16 (Thompson-Hall et al., 2016; Rao et al., 2019a; Nyantakyi-Frimpong, 2020a).
17
18
19 Table 5.3: Examples of social inequalities in cropping systems that compound climate change vulnerability.
Social inequality How social inequality increases vulnerability to climate change in cropping
systems
Gender inequality can · Men and women have different access to and decision-making control over
create and worsen social resources such as seeds, systemic differences in land tenure and agricultural
vulnerability to climate employment, and their responsibilities, workloads and response to climate
change impacts within stresses differ due to systemic gender inequities and socio-cultural norms,
cropping systems (high which intersect with other inequities (e.g., income level, ethnicity) to
confidence) (Carr and compound vulnerability (Rao et al., 2019a; Ebhuoma et al., 2020; Nyantakyi-
Thompson, 2014; Sugden et Frimpong, 2020a).
al., 2014; Nyantakyi-
Frimpong and Bezner-Kerr, · In a study in northern Ghana, for example, poor widows with poor health had
2015; Rao et al., 2019a; fewer resources to rely on during droughts than married women, particularly
Ebhuoma et al., 2020; those married to local leaders; in contrast, due to gendered expectations, during
Nyantakyi-Frimpong, 2020a; floods low-income men suffered greater consequences (Nyantakyi-Frimpong,
see Cross-Chapter Box 2020a).
GENDER in Chapter 18).
· Adaptation strategies such as migration can compound that vulnerability, but
importantly the specific gendered vulnerability intersects with other
inequalities which are context specific (Sugden et al., 2014; Nyantakyi-
Frimpong, 2020a; Cross-Chapter Box MIGRATE in Chapter 7).
Globally, smallholder food · In part because of limited policy, infrastructure and institutional support, low
producers are more credit access, viable markets and limited political voice in policy debates
vulnerable than large-scale (HLPE, 2013; Karttunen et al., 2017; Mbow et al., 2019; Nyantakyi-Frimpong,
producers to climate change 2020a).
impacts (high confidence).
· Smallholder producers' vulnerability may be increased by heavy reliance on
one crop for income, particularly if the crop requires significant capital
investments (medium confidence) (Toufique and Belton, 2014; Craparo et al.,
2015; Ovalle-Rivera et al., 2015).
· For example, smallholder coffee producers in southern Mexico and Central
America are more vulnerable due to a range of factors, including unstable and
low coffee prices, limited institutional support for small-scale producers, low
negotiation capacity and access to markets, and heavy reliance on one crop for
income (Economic Commission for Latin America and the Caribbean and
System, 2014; Ovalle-Rivera et al., 2015; Ruiz Meza, 2015; Hannah et al.,
2017; Bacon et al., 2021). Pest and disease outbreaks such as coffee leaf rust,
extreme climatic events, ongoing conflict, poor governance, and low viability
of livelihoods increased migration and high levels of food insecurity for this
group (Robalino et al., 2015; Hannah et al., 2017; Donatti et al., 2019) which
also varied by institutional and farm level responses, land size and income
level (Quiroga et al., 2020; Bacon et al., 2021).
Farmworkers are another · Farmworkers often experience job insecurity, food insecurity, poor working
social group with heightened conditions, poverty, and social marginalization. Climate change impacts can
compound their vulnerability, for example by worsening working conditions
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vulnerability to climate through increased temperatures and humidity (Section 5.12.3.1), or increase
change (medium confidence). unreliability of work due to rainfall irregularity, flooding or drought, and can
put them more at risk during climatic extreme events such as wildfires (Turhan
et al., 2015; Greene, 2018; Mendez et al., 2020; Tigchelaar et al., 2020).
1
2
3 5.4.3 Projected Impacts
4
5 5.4.1.1 Advances in the characterisation of the effects of elevated atmospheric CO2
6
7 Elevated CO2 concentrations stimulate photosynthesis rates and biomass accumulation of C3 crops, and
8 enhance crop water use efficiency of various crop species including C4 crops (high confidence) (Kimball,
9 2016; Toreti et al., 2020). Perennial crops and root crops may have a greater capacity for enhanced biomass
10 under elevated CO2 concentrations, although this does not always result in higher yields (Glenn et al., 2013;
11 Kimball, 2016).
12
13 Recent FACE studies found that the effects of elevated CO2 are greater under water-limited conditions
14 (medium confidence) (Manderscheid et al., 2014; Fitzgerald et al., 2016; Kimball, 2016), which was
15 generally reproduced by crop models (Deryng et al., 2016). However, drought sometimes negates the CO2
16 effects (Jin et al., 2018).
17
18 There are significant interactions between CO2, temperature, cultivars, nitrogen and phosphorous nutrients
19 (Kimball, 2016; Toreti et al., 2020): Positive effects of rising CO2 on yield are significantly reduced by
20 higher temperatures for soybean, wheat and rice (medium confidence) (Ruiz-Vera et al., 2013; Cai et al.,
21 2016; Gray et al., 2016; Hasegawa et al., 2016; Obermeier et al., 2016; Purcell et al., 2018; Wang et al.,
22 2018). In aboveground vegetables, elevated CO2 can in some cases reduce the impact of other climate
23 stressors, while in others the negative impacts of other abiotic factors negate the potential benefit of elevated
24 CO2 (Bourgault et al., 2017; Bourgault et al., 2018; Parvin et al., 2018; Parvin et al., 2019). Significant
25 variation exists among cultivars in yield response to elevated CO2, which is positively correlated with yield
26 potential in rice and soybean, suggesting the potential to develop cultivars for enhanced productivity under
27 future elevated [CO2] (Ainsworth and Long, 2021).
28
29 Elevated CO2 reduces some important nutrients elements such as protein, iron, zinc, and some vitamins in
30 the grains, fruit or vegetables to varying degrees depending on crop species and cultivars (high confidence)
31 (Mattos et al., 2014; Myers et al., 2014; Dong et al., 2018; Scheelbeek et al., 2018; Zhu et al., 2018a; Jin et
32 al., 2019; Ujiie et al., 2019). This is of particular relevance for fruit and vegetable crops given their
33 importance in human nutrition (high confidence) ( see Section 5.12.4 for potential impacts on nutrition;
34 Nelson et al., 2018; Springmann et al., 2018). Recent experimental studies (Section 5.3.2), however, show
35 some complex and counteracting interactions between CO2 and temperature in wheat, soybean, and rice; heat
36 stress negates the adverse effect of elevated CO2 on some nutrient elements (Macabuhay et al., 2018; Kohler
37 et al., 2019; Wang et al., 2019b). The CO2 by temperature interaction for grain quality needs better
38 quantitative understandings to predict food nutritional security in the future.
39
40 5.4.3.2 Projected impacts on major crop production
41
42 AR5 Chapter 7 estimated the crop yield reduction globally of about 1% per decade due to climate change
43 (Porter et al., 2014), similar to that in the previous assessment reports (Porter et al., 2019). Additional
44 research confirms that climate change will disproportionately affect crop yields among regions with more
45 negative than positive effects being expected in most areas, especially in currently warm regions including
46 Africa, Central and South America (high confidence).
47
48 A systematic literature search between 2014 and 2020 resulted in about 100 peer-reviewed papers that
49 simulated crop yields of four major crops (maize, rice, soybean, and wheat) using CMIP5 data (Hasegawa et
50 al., 2021b). Most studies focus on the relative change in crop yields due to climate change, but do not
51 consider technological advances. Nevertheless, they provide useful insights into time-, scenario-, and
52 warming-degree-dependent impacts of climate change.
53
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1 The impact of climate change on crop yield without adaptation projected in the 21st century is generally
2 negative even with the CO2 fertilisation effects, with the overall median per-decade effect being -2.3% for
3 maize, -3.3% for soybean, -0.7% for rice, and -1.3% for wheat, which are consistent with previous IPCC
4 assessments (Porter et al., 2014). The effects vary greatly within each crop, timeframe, and RCP, but show a
5 few common features across crops (Figure 5.6a). Differences in the projected impacts between RCPs are not
6 pronounced by mid-century. From then onward, the negative effect becomes more pronounced under
7 RCP8.5, notably in maize. Rice yields show less variation across models than other crops presumably
8 because simulations are mostly under irrigated conditions. A part of the uncertainty in the projection is due
9 to regional differences (Figure 5. 6b). Negative impacts on cereals are projected in Africa and Central and
10 South America at the end of the century, which agrees with the previous studies (Aggarwal et al., 2019;
11 Porter et al., 2019).
12
13 The differences due to regions, RCPs, and timeframes are related to the current temperature level and degree
14 of warming (Figure 5.7). The projected effects of climate change are positive where current annual mean
15 temperatures (Tave) are below 10 °C, but they become negative with Tave above around 15 °C. At Tave>20°C,
16 even a small degree of warming could result in adverse effects. In maize, negative effects are apparent at
17 almost all temperature zones. A new study using the latest climate scenarios (CMIP6) and global gridded
18 crop model ensemble projected that climate change impacts on major crop yields appear sooner than
19 previously anticipated, mainly because of warmer climate projections and improved crop model sensitivities
20 (Jägermeyr et al., 2021).
21
22
23
24 Figures 5.6: Projected yield changes relative to the baseline period (2001-2010) without adaptation and with CO2
25 fertilization effects (Hasegawa et al., 2021b). The box is the interquartile range (IQR) and the middle line in the box
26 represents the median. The upper- and lower-end of whiskers are median 1.5 × IQR ± median. Open circles are values
27 outside the 1.5 × IQR. (a) at different time periods (Near Future, NF, Baseline-2039; Mid Century, MC, 2040-2069;
28 End of Century, EC, 2070-2100) under three representative concentration pathways (RCPs), and (b) at different regions
29 at EC.
30
31
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2 Figure 5.7: Projected yield changes relative to the baseline period (2001-2010) without adaptation and with CO2
3 fertilization effects (Hasegawa et al., 2021b). (a) Mid-century (MC, 2040-2069) and end-century (EC, 2070-2100)
4 projections under three RCP scenarios as a function of current annual temperature (Tave), (b) as a function of global
5 temperature rise from the baseline period by three Tave levels. See Figure. 5.6 for legends.
6
7
8 As noted in Section 5.3.1, most simulations do not fully account for responses to pests, diseases, long-term
9 change in soil, and some climate extremes (Rosenzweig et al., 2014), but studies are emerging to include
10 some of these effects. For example, based on the temperature response of insect pest population and
11 metabolic process, global yield losses of rice, maize, and wheat are projected to increase by 10 25 % per
12 degree of warming (Deutsch et al., 2018). Rising temperatures reduce soil carbon and nitrogen, which in turn
13 exacerbate the negative effects of + 3 °C warming on yield from 9 to 13 % in wheat and from 14 to 19 % in
14 maize (Basso et al., 2018).
15
16 A few studies have examined possible occurrences of tele-connected yield losses (5.4.1.2) using future
17 climate scenarios. Tigchelaar (2018) estimated that for the top four maizeexporting countries, the
18 probability that simultaneous production losses greater than 10% occur in any given year increases from 0 to
19 7% under 2°C-warming and to 86% under 4 °C-warming. Gaupp (2019) estimated that risks of simultaneous
20 failure in maize would increase from 6% to 40% at 1.5 °C and to 54% at 2 °C-warming, respectively, relative
21 to the historical baseline climate. Large-scale changes in SST are the major factors causing simultaneous
22 variation in climate extremes, which are projected to intensify under global warming (Cai et al., 2014; Perry
23 et al., 2017). Consequently, risks of multi-breadbasket failures will also increase (medium confidence).
24 Further examination is needed for the effects of spatial patterns of these extremes on breadbaskets in relation
25 to SST anomalies under more extreme climate scenarios.
26
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1 Future surface ozone concentration is highly uncertain (Fiore et al., 2012; Turnock et al., 2018); it is
2 projected to increase under RCP8.5 and to decrease under other RCPs depending largely on different
3 methane emission trajectories because methane is an important precursor of ozone. Methane, therefore,
4 reduces crop yield both from climate warming and ozone increase (Avnery et al., 2013). Shindell (2016)
5 estimated yield losses of four major crops (to be 25 ± 11% by 2100 under RCP8.5, as a net balance of the
6 positive effect of CO2 (15± 2%) and negative effects of warming (35 ± 10%) and ozone (4.0 ± 1.3%), and
7 that 62% of the yield loss was attributable to methane. This points to the importance of reducing methane
8 and other precursors of ozone as an effective adaptation strategy (medium evidence, high agreement).
9
10 5.4.3.3 Projected impacts on other crops
11
12 Yield projections for crops other than cereals indicate mostly negative impacts on production due to a range
13 of climate drivers (high confidence), with yield reductions similar to that of cereals expected in tropical,
14 subtropical and semi-arid areas (Mbow et al., 2019). Springmann et al. (2016), compared the projected
15 global food availability for different food groups under the SSP2 2050 scenario and found reductions in
16 availability were similar in cereals, fruit and vegetables, and root and tubers (with legumes and oilseed crops
17 showing a smaller reduction).
18
19 Fruit and vegetables have not been subject to extensive or coordinated yield projections (Figure 5.8). Yield
20 projections have been performed for individual crops and locations (Ruane, 2014; Adhikari et al., 2015;
21 Awoye et al., 2017; Ramachandran et al., 2017); but more often crop suitability models have been used
22 (SM5.3). Zhao(2019) introduced a modelling approach that could be used to generate yield projections for a
23 wider range of annual crops. The discussion here also draws on reviews of more restricted experimental
24 studies. Negative impacts of climate change on crop production are expected across many cropping systems
25 (Figure 5.8). Apart from the direct effects of elevated carbon dioxide, most changes are expected to have
26 negative effects on crop production. Changes in temperature and rainfall are most often mentioned as drivers
27 of climate impacts, but expected changes in phenology, pests and diseases are also raising concerns.
28 (Scheelbeek et al., 2018) synthesized projections for vegetables and legumes, based on their response to
29 climate factors under experimental conditions; in most cases the magnitude of the changes is comparable to
30 the RCP 8.5 2100 forecasts. Scheelbeek et al. (2018) projected yield changes of: +22.0% (+11.6% to
31 +32.5%) for a 250 ppm increase in CO2 concentration; -34.7% (-44.6% to -24.9%) for a 50 % reduction in
32 water availability; -8.9% (-15.6% to -2.2%) for a 25 % increase in ozone concentration; -31.5% for a 4°C
33 increase in temperature (in papers with a baseline temperature of >20°C). Overall, impacts are expected to be
34 largely negative in regions where the temperature is currently above 20°C, while some yield gains are
35 expected in cooler regions (provided that water availability and other conditions are maintained). Scheelbeek
36 et al. (2018), did not consider changes in pest and disease pressure, which are projected to increase with
37 warming (see SM5.3).
38
39
40
41 Figure 5.8: Synthesis of literature on the projected impacts of climate change on different cropping systems. The
42 assessment includes projections of impacts on crop productivity over a range of emission scenarios and time periods.
43 The projected impacts are disaggregated by the different climate and climate-related drivers. Impacts are reported as
44 positive, negative or mixed. The assessment draws on >60 articles published since AR5. The confidence is based on the
45 evidence given in individual articles and on the number of articles. See SM5.2 information for details.
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1
2
3 Systematic assessments of climate response for root crops as a group are lacking (Raymundo et al., 2014;
4 Knox et al., 2016; Manners and van Etten, 2018). Climate suitability is projected to increase for tropical root
5 crops (SM5.3) and some studies have found that root crops will be less negatively impacted than cereals, but
6 there is no consensus on this (Brassard and Singh, 2008; Adhikari et al., 2015; Schafleitner, 2016; Manners
7 et al., 2021). For potato, Raymundo et al. (2018) projected global yield reductions of 2-6% by 2055 under
8 different RCPs, but with important differences among regions; tuber dry weight may experience reductions
9 of 50 to 100% in marginal growing areas such as central Asia, while increases of up to 25% are expected in
10 many high-yielding environments. Projections show yield increases of 6% per 100 ppm elevation in CO2 but
11 declines of 4.6% per °C and 2% per 10% decrease in rainfall (Fleisher et al., 2017). Jennings et al. (2020),
12 projected an overall increase in global potato production, but only if widespread adoption of adaptation
13 measures is achieved. Although increases in CO2 could produce positive yield responses, the effects of
14 temperature may offset these potential benefits (Dua et al., 2013; Raymundo et al., 2014). Warming offers
15 the potential of longer growing seasons but can also have negative impacts through disrupted phenology and
16 interactions with pests (Figure 5.8, Bebber, 2015; Pulatov et al., 2015).
17
18 Global yield modelling is lacking for woody perennial crops. Experimental studies suggest negative impacts
19 on yields due to reduced water supply and increased soil salinity, as well as from warming and ozone
20 (although evidence was limited for these) (Alae-Carew et al., 2020). Increasing CO2 is expected to increase
21 yields, but only where other factors, such as warming, do not become yield-limiting (Alae-Carew et al.,
22 2020). Many local projections include large uncertainty because of a lack of observational data and reliable
23 parametrization (Moriondo et al., 2015; Mosedale et al., 2016; Kerr et al., 2018; Mayer et al., 2019b). Most
24 perennial crop models have found large negative impacts on yield and suitability, although CO2 fertilisation
25 and phenology are not always considered (Lobell and Field, 2011; Glenn et al., 2013). Perennial crops are
26 often grown in dryland areas where rainfall or irrigation water can be critical (Mrabet et al., 2020). Valverde
27 (2015) found that yield losses in the Mediterranean region were largely driven by reduced rainfall, with
28 maximum estimated yield losses of 5.4% for grape, 14.9% for olive and 27.2% for almond under a relatively
29 hot and dry scenario (by 20412070). Moriondo (2015) highlight the need for perennial crop models to
30 incorporate phenology and extreme climate events. Equally challenging is the need to estimate the impact of
31 biotic changes, particularly climate-driven movement of pests and diseases (Ponti et al., 2014; Bosso et al.,
32 2016; Schulze-Sylvester and Reineke, 2019; Section 5.5.2.4 ).
33
34 For cotton, experimental studies suggest positive impacts from rising CO2 and temperature (Zhang et al.,
35 2017a; Jans et al., 2021), but projections show mixed impacts on yield, including large negative impacts in
36 warmer regions due to heat, drought and the interaction of temperature with phenology (Yang et al., 2014;
37 Williams et al., 2015; Adhikari et al., 2016; Rahman et al., 2018). Climate change is also expected to
38 increase the demand for irrigation water, which will likely limit production (Jans et al., 2021). There are also
39 concerns that fibre quality may deteriorate (e.g., air permeability of compressed cotton fibers) (Luo et al.,
40 2016).
41
42 Higher temperatures and altered moisture levels are expected to present a food safety risk, particularly for
43 above ground harvested vegetables (Figures 5.8; 5.10). Warmer and wetter weather is anticipated to increase
44 fungal and microbial growth on leaves and fruit, while altered flooding regimes increase the risk of crop
45 contamination (Liu et al., 2013; Uyttendaele et al., 2015). This is also true for perennial crops, e.g., warming
46 and climate variability can increase fungal contamination of grapes including those associated with
47 mycotoxins (Battilani, 2016; Paterson, 2018).
48
49
50 [START BOX 5.2 HERE]
51
52 Box 5.2: Case Study: Wine
53
54 Wine growing regions cover 7.4 million ha with a value of 35 billion USD in 2018 (OIV, 2019). Important
55 regions (Italy, France, Spain, United States, Argentina, Australia, South Africa, Chile, Germany, China,
56 Argentina) are located in areas where mean annual temperature roughly varies between 10 and 20 °C
57 (Schultz and Jones, 2010; Mosedale et al., 2016).
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1
2 Temperature is the primary determinant for vine development. Recent warming trends have advanced
3 flowering, maturity, and harvest (high confidence) (Koufos et al., 2014; Cook and Wolkovich, 2016; Hall et
4 al., 2016; Ruml et al., 2016; van Leeuwen and Destrac-Irvine, 2017; Koufos et al., 2020; Wang et al., 2020b;
5 Wang and Li, 2020), and wine growing regions have expanded outside the normal temperature bounds of
6 locally grown varieties (limited evidence, high agreement) (Kryza et al., 2015; Irimia et al., 2018). Milder
7 winters have affected harvest in ice-wine growing regions (Pickering et al., 2015). Higher temperatures have
8 mixed effects depending on site, but generally decreases grape quality (Barnuud et al., 2014; Morales et al.,
9 2014; Sweetman et al., 2014; Kizildeniz et al., 2015; Kizildeniz et al., 2018). Warming increases sugar
10 accumulation and decreases acidity (Leolini et al., 2019). Secondary metabolites are negatively affected
11 (Biasi et al., 2019; Tesli et al., 2019). Developmental phases are projected to proceed faster in response to
12 warming (high confidence) (Fraga et al., 2016a; Fraga et al., 2016b; García de Cortázar-Atauri et al., 2017;
13 Costa et al., 2019; Molitor and Junk, 2019; Sánchez, 2019). However extreme high temperatures may have
14 inhibitory effects on development (Cuccia et al., 2014).
15
16 In some cases, irrigation is required, and more frequent droughts are a key concern for yield and fruit quality
17 (Morales et al., 2014; Bonada et al., 2015; Kizildeniz et al., 2015; Salazar-Parra, 2015; Kizildeniz et al.,
18 2018; Funes et al., 2020). Water stress reduces shoot growth and berry size, and increases tannin and
19 anthocyanin content (van Leeuwen and Darriet, 2016). However, controlled water stress produces positive
20 impacts on wine quality, increasing skin phenolic compounds (van Leeuwen and Destrac-Irvine, 2017). The
21 level of stress will depend on soil type, texture and organic matter content (Fraga et al., 2016a; Fraga et al.,
22 2016b; Bonfante, 2017; García de Cortázar-Atauri et al., 2017; Leibar et al., 2017; Costa et al., 2019; Molitor
23 and Junk, 2019; Sánchez, 2019). Increases in water demands with potential negative effects from increased
24 soil salinity are among the most common effects of climate change in irrigated regions (medium evidence,
25 high agreement) (Mirás-Avalos et al., 2018; Phogat et al., 2018).
26
27 Rising CO2 will have mixed effects on vine growth and quality (medium evidence, high agreement)
28 (Martínez-Lüscher et al., 2016; Edwards et al., 2017; van Leeuwen and Destrac-Irvine, 2017). Rising CO2
29 concentrations will negatively affect wine quality by reducing anthocyanin concentration and colour
30 intensity (Leibar et al., 2017).
31
32 Suitability responses to warming are region-specific. In regions where low temperature is a limiting factor,
33 warming will enable growers to grow a wider range of varieties and obtain better-quality wines (high
34 confidence) (Fuhrer et al., 2014; Mosedale et al., 2015; Mosedale et al., 2016; Meier et al., 2018; Jobin
35 Poirier et al., 2019; Maciejczak and Mikiciuk, 2019). Subtropical and Mediterranean regions will experience
36 major declines in fruit quality for high-quality wines (high confidence) (Resco et al., 2016; Lazoglou et al.,
37 2018; Cardell et al., 2019; Fraga et al., 2019a; Fraga et al., 2019b; Tesli et al., 2019). These changes will
38 also affect wine tourism (Nunes and Loureiro, 2016).
39
40 Impacts on suitability may reshape the geographical distribution of wine regions. Viability of the wine-
41 growing regions will depend on the knowledge of local climatic variability (Neethling et al., 2019;
42 Rességuier et al., 2020) and the implementation of adaptation strategies such as use of adapted plant material
43 rootstocks, cultivars and clones, viticultural techniques (e.g., changing trunk height, leaf area to fruit weight
44 ratio, timing of pruning), irrigation, enological interventions to control alcohol and acidity, as well as policy
45 incentives and support (Callen et al., 2016; Ollat and Leeuwen, 2016; van Leeuwen and Destrac-Irvine,
46 2017; Merloni et al., 2018; Alikadic et al., 2019; del Pozo et al., 2019; Fraga et al., 2019b; Santillan et al.,
47 2019; Morales-Castilla et al., 2020; Marín et al., 2021).
48
49 [END BOX 5.2 HERE]
50
51
52 [START BOX 5.3 HERE]
53
54 Box 5.3: Pollinators
55
56 Climate change will reduce the effectiveness of pollinator agents as species are lost from certain areas, or the
57 coordination of pollinator activity and flower receptiveness is disrupted in some regions (high confidence)
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1 (Potts et al., 2010; Gonzalez-Varo et al., 2013; Polce et al., 2014; Kerr et al., 2015; Potts et al., 2016; Settele
2 et al., 2016; Giannini et al., 2017; Mbow et al., 2019). A modelling study estimates that complete removal of
3 pollinators could reduce global fruit supply by 23%, vegetables by 16%, and nuts and seeds by 22%, leading
4 to significant increases in nutrient-deficient population and malnutrition-related diseases (Smith and Haddad,
5 2015), highlighting the importance of this ecosystem service for human health.
6
7 Bees are an essential agricultural pollinator, widely recognized for their role in the fertilisation of many
8 domesticated plants. The observed wide-spread decline in native bees and honeybee colony numbers,
9 particularly in the U.S. and Europe, has been associated with a number of environmental stressors in addition
10 to climate change, such as neonicotinoids and varroa mites, and has raised concerns regarding plant-
11 pollinator networks, the stability of pollination services, global food production and the prevalence of
12 malnutrition (Williams and Osborne, 2009; Potts et al., 2010; Chaplin-Kramer et al., 2014).
13
14 Any climatic influence on floral phenology or physiology could, potentially, alter bee biology. At present
15 there is evidence that climate change induced asynchrony in pollen and pollinators can occur (Stemkovski et
16 al., 2020). In addition, the nutritional composition of floral pollen may also affect the bee's health at the
17 global level (low evidence). For example, the goldenrod (Solidago spp.), a ubiquitous pollen source for bees
18 just prior to winter, has experienced a ~30% drop in protein since the onset of CO2 emissions from the
19 industrial revolution (Ziska et al., 2016).
20
21 Climate extremes could pose risks to pollinator when species tolerance is exceeded, with subsequent
22 reduction in populations and potential extirpation (Nicholson and Egan, 2020; Soroye et al., 2020). The rate
23 of climate change may induce potential mismatches in the timing of flowering and pollinator activity
24 depending on the species (Bartomeus et al., 2011). For instance, Miller-Struttmann (2015) showed that long-
25 tongued bumblebees may be at a disadvantage as warming temperatures are reducing their floral hosts,
26 making generalist bumblebees more successful.
27
28 Overall, there is medium confidence that long-term mutualisms may be impacted directly by CO2 increases in
29 terms of nutrition, or by temperature and other climatic shifts that may alter floral emergence relative to
30 pollinator life cycles. Additional research is needed to further our understanding of the biological basis for
31 these effects, and their consequence for pollination services.
32
33 [END BOX 5.3 HERE]
34
35
36 5.4.3.4 Observed and projected impacts on cultural ecosystem service
37
38 Cultural ecosystem services (CES) are those non-material benefits, such as aesthetic experiences, recreation,
39 spiritual enrichment, social relations, cultural identity, knowledge and other values (Millennium Ecosystem
40 Assessment, 2005), which support physical and mental health and human well-being (Chan et al., 2012;
41 Triguero-Mas et al., 2015). CES in agricultural and wild landscapes include recreational activities, access to
42 wild or cultivated products, and cultural foods, spiritual rituals, heritage and memory dimensions, and
43 aesthetic experiences (Daugstad et al., 2006; Calvet-Mir et al., 2012; Ruoso et al., 2015). Relative to other
44 ecosystem services, CES in agricultural landscapes has had less research (Merlín-Uribe et al., 2012; Milcu et
45 al., 2013; Bernues et al., 2014; Plieninger et al., 2014; van Berkel and Verburg, 2014; Ruoso et al., 2015;
46 Quintas-Soriano et al., 2016). Agricultural heritage is a key aspect of CES and plays an important role in
47 maintaining agrobiodiversity (Hanacek and Rodríguez-Labajos, 2018).
48
49 Climate change is projected to have negative impacts on Cultural ecosystem services (medium confidence)
50 (Table 5.4). There is limited evidence that climate change has been the main driver affecting CES of
51 agroecosystems confounded by other drivers such as migration and changing farming patterns (Hanacek and
52 Rodríguez-Labajos, 2018; Dhakal and Kattel, 2019). Recent studies observed declines in CES in Alpine
53 pastures and floodplains in Europe in part due to climate change impacts (Probstl-Haider et al., 2016;
54 Schirpke et al., 2019). Another study estimated that the scenic beauty enjoyed by those who visit the
55 vineyards in central Chile will decline by 18-28% by 2050 due to a combination of reduced precipitation,
56 increased temperatures, and natural fire cycles (Martinez-Harms et al., 2017). More research is needed,
57 however, particularly on cultural heritage, spiritually significant places, and in low-income countries.
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1
2
3 Table 5.4: Projected Impacts on CES from Climate Change.
Region CES Climate Change Projected impacts from References
Scenario climate change
Central Chile, Aesthetic RCP 2.6 and 8.5. Increased temperature, Martinez-
South America experience of reduced precipitation and Harms et al.
scenic beauty in increased fires will damage (2017)
vine-growing scenic beauty of vineyards.
region. Participatory scenario
analysis estimated
reduction in aesthetic
experience from scenic
beauty by 18-28% by 2050
for RCP 2.6, with greater
impacts under RCP 8.5.
Mountainous Cultural and Temperature + 1.5 °C Some decline in CES, with Kirchner et
regions of Austria aesthetic from 2008 to 2040 and 4 tradeoffs between diversity al. (2015)
experiences in precipitation scenarios and cultural ecosystem
alpine pastures and (High, similar, seasonal services and provisioning
diverse agricultural shift and Low). services depending upon
landscapes the scenario.
Forest and Recreation, scenic Regional scenarios, do Not anticipated to be Gorn et al.
agricultural landscape beauty not specify RCPs. significantly changed by (2018)
landscapes in and spiritual value climate change under most
southern Saxony- of agricultural scenarios, except for
Anhalt in Germany landscapes and intensification scenario,
forests. which would lead to a
decline in the forest cultural
services as they provide
important historical and
cultural ties.
Northeast Austria Tourism, Increased temperature Increased agricultural Probstl-
floodplains recreation, cultural by 2050 and 2100 and intensification due to shifts Haider et al.
(grasslands and heritage. seasonal shifts in in climate and decline in (2016)
wetlands) precipitation. CES is predicted, based on
farmer interviews.
Mount Kenya, Tourism, Not specified Glacier disappearance may Evaristus
Kenya recreation, spiritual lead to reduced mountain (2014)
and cultural values. trekking and other tourism
and recreational activities.
Philippines Nature-based Not specified Risk of typhoon, drought Hidalgo
tourism in agri- and strong wind, grass fire, (2015)
tourism heavy rains. Anticipated to
increase vulnerability in
terms of human health
services and energy use in
tourism.
4
5
6 [START BOX 5.4 HERE]
7
8 Box 5.4: Soil Health
9
10 Soil health, defined as an integrative property that reflects the capacity of soil to respond to land
11 management, continues to support provisioning ecosystem services (Kibblewhite et al., 2008). Climate
12 change will have significant impacts on soil health indicators such as soil organic matter (SOM). For
13 example, precipitation extremes can reduce soil biological functions, and increase surface flooding,
14 waterlogging, soil erosion and susceptibility to salinization (Herbert et al., 2015; Chen and Mueller, 2018;
15 Akter et al., 2019; Sánchez-Rodríguez et al., 2019).
16
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1 The most significant threat to soil health is the loss of SOM (FAO and ITPS, 2015). SOM holds a great
2 proportion of the nutrients, and regulates important soil physical, chemical, and biological processes, such as
3 cation exchange capacity, pH-buffering, soil structure, water-holding capacity, and microbial activity (FAO
4 and ITPS, 2015). Soils also hold the largest terrestrial organic carbon stock, 3-4 times greater than the
5 atmosphere (Stoorvogel et al., 2017). At the global scale, climate and vegetation are the main drivers of soil
6 carbon (SOC) storage (Wiesmeier et al., 2019). While organic matter input is the primary driver of SOC
7 stocks (Fujisaki et al., 2018), temperature and soil moisture play a key role in SOC storage at the local scale
8 (Carvalhais et al., 2014; Doetterl et al., 2015). Soil type, land-use and management practices also play
9 important roles at the local scale.
10
11 Increase in soil temperature will negatively impact SOC, but primarily in higher latitudes (medium
12 confidence) (Carey et al., 2016; Qi et al., 2016; Feng et al., 2017; Gregorich et al., 2017; Hicks Pries et al.,
13 2017; Melillo et al., 2017; Hicks Pries et al., 2018). Experiments have shown that warming can accelerate
14 litter mass loss and soil respiration (Lu et al., 2013) and reduces the soil recalcitrant C pool (Chen et al.,
15 2020). SOC losses may speed up soil structural degradation, changes in soil stoichiometry and function
16 (Hakkenberg et al., 2008; Tamene et al., 2019), with downstream effects on aquatic ecosystems. The rate and
17 extent of SOC losses vary greatly depending on the scale of measurement (local to global), soil properties,
18 climate, land-use, and management practices (Sanderman et al., 2017; Wiesmeier et al., 2019).
19
20 Adoption of practices that build SOC can improve crop resilience to climate change-related stresses such as
21 agricultural drought. Iizumi and Wagai (2019) found that a relatively small increase in topsoil (030 cm)
22 SOC could reduce drought damages to crops over 70% of the global harvested area. The effects of increasing
23 SOC are more positive in drylands due to more efficient use of rainwater, which can increase drought
24 tolerance (Iizumi and Wagai, 2019). Similarly, Sun et al. (2020) found that relative to local conventional
25 tillage, conservation agriculture has a win-win outcome of enhanced C sequestration and increased crop yield
26 in arid regions. However, the impact of no-till may be minimal if not supplemented with residue cover and
27 cover crops. As such this is a highly debated area where some authors argue that no-till has limited effect and
28 the evidence outside drylands is weak. Furthermore, the use of crop residues is constrained by its alternative
29 uses (e.g., fuel, livestock feed, etc.) in much of the developing world. Practices that build up SOC may
30 encourage soil microbial populations, which in turn can increase yield stability under drought conditions
31 (Prudent et al., 2020).
32
33 Soil C sequestration is an important strategy to improve crop and livestock production sustainably that could
34 be applied at large scales and at a low cost, if there was adequate institutional support and labour, using
35 agroforestry, conservation agriculture, mixed cropping, and targeted application of fertiliser and compost
36 (high confidence) (Paustian et al., 2016; Kongsager, 2018; Nath et al., 2018; Woolf et al., 2018; Corbeels et
37 al., 2019; Kuyah et al., 2019; Corbeels et al., 2020; Muchane et al., 2020; Sun et al., 2020; Nath et al., 2021).
38 For example, a widespread adoption of agroforestry, conservation agriculture, mixed cropping, and balanced
39 application of fertiliser and compost by India's small landholders could increase annual C sequestration by
40 70130 Tg CO2e (Nath et al., 2018; Nath et al., 2021).
41
42 [END BOX 5.4 HERE]
43
44
45 5.4.4 Adaptation Options
46
47 Adaptation strategies in crop production range from field and farm-level technical options such as crop
48 management and cultivar/crop options to livelihood diversification and income protection such as index-
49 based insurance. This section assesses crop management options for different crop types. Feasibility of
50 adaptation options in various systems are addressed in Section 5.14.
51
52 5.4.4.1 Adaptation options for major crops
53
54 Crop management practices are the most commonly studied adaptation measures (Shaffril et al., 2018;
55 Hansen et al., 2019a; Muchuru and Nhamo, 2019), but quantitative assessments are mostly limited to
56 existing agronomic options such as changes in planting schedules, cultivars, and irrigation (Beveridge et al.,
57 2018a; Aggarwal et al., 2019). This section draws on the global dataset used in Sections 5.4.3.2 (Hasegawa
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1 et al., 2021b) to estimate adaptation potential, defined as the difference in simulated yields with and without
2 adaptations. A caveat to the analysis is that the dataset includes management options if the literature treats
3 them as adaptation. They include intensification measures such as fertilizer and water management, not
4 allowing for physical and economic feasibility.
5
6 The overall adaptation potential of existing farm management practices to reduce yield losses averaged 8%
7 in mid-century and 11% in end-century (Figure 5.9), which is insufficient to offset the negative impacts from
8 climate change, particularly in currently warmer regions (Section 5.4.3.2). Emission scenarios, crop species,
9 regions, or adaptation options do not show discernible differences. Combinations of two or more options do
10 not necessarily have greater adaptation potential than a single option, though a fair comparison is difficult in
11 the dataset from independent studies. One regional study in West Africa found that currently promising
12 management would no longer be effective under future climate, suggesting the need to evaluate effectiveness
13 under projected climate change.
14
15 A global-scale meta-analysis estimated a 3-7% yield loss per degree increase in temperature (Zhao et al.,
16 2017). Two global-scale studies using multiple global gridded crop models found that growing-season
17 adaptation through cultivar changes offsets global production losses up to 2°C of temperature increase
18 (Minoli et al., 2019; Zabel et al., 2021). While these studies do not account for CO2 fertilisation effects,
19 another global-scale study with the CO2 fertilisation effects (Iizumi et al., 2020) showed that residual damage
20 (climate change impacts after adaptation) would start to increase almost exponentially from 2040 toward the
21 end of the century under RCP 8.5. The cost required for adaptation and due to residual damage is projected
22 to rise from US$63 billion at 1.5°C to US$80 billion at 2°C and to US$128 billion at 3°C (Iizumi et al.,
23 2020). All these global studies project that risks and damages are greater in tropical and arid regions, where
24 crops are exposed to heat and drought stresses more often than in temperate regions (Sun et al., 2019;
25 Kummu et al., 2021; SM5.4). There are still large uncertainties in the crop model projections (Müller et al.,
26 2021a), but these (Iizumi et al., 2020) multiple lines of evidence suggest that warming beyond +2 °C
27 (projected to be reached by mid-century under high emission scenarios) will substantially increase the cost of
28 adaptation and the residual damage to major crops (high confidence). The residual damage will prevail much
29 sooner in currently warmer regions, where the effect of even a modest temperature increase is greater
30 (Section 5.4.3.2).
31
32
(a)
33
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(b)
1
2 Figure 5.9: Adaptation potential, defined as the difference between yield impacts with and without adaptation in
3 projected impacts (Hasegawa et al., 2021b). (a) projections under three RCP scenarios by regions and (b) by options at
4 mid-century (MC, 2040-2069) and end-century (EC, 2070-2100). n is the number of simulations. See Figure 5.6 for
5 legends.
6
7
8 Most crop modelling studies on adaptation are still limited to a handful of options for each crop type
9 (Beveridge et al., 2018a). A range of other options are possible not just to reduce yield losses but to diversify
10 risks to livelihoods, which are partially assessed in Sections 5.4.4.4 and 5.14.1. Current modelling
11 approaches are not suited for the assessment of multiple dimensions of adaptation options. New studies are
12 emerging that evaluate multiple options for productivity, sustainability, and greenhouse gas emission (Xin
13 and Tao, 2019; Smith et al., 2020b), but local- and household-scale assessment, taking account of future
14 climatic variability, needs to be enhanced (Beveridge et al., 2018a).
15
16 5.4.4.2 Adaptation options for other crops
17
18 Across this diverse group of cropping systems distinct adaptation options and adaptation limits have emerged
19 (Figure 5. 10; Acevedo et al., 2020; Berrang-Ford et al., 2021b). Some crop types have already seen
20 widescale implementation of climate adaptation (e.g., grapevines), while others show little evidence of
21 preparation for climate change (e.g., leafy salad crops). Many adaptation responses are shared with the major
22 crops, but prominent options such as plant breeding are under-utilized and there is a lack of evidence for
23 assessing adaptation for many crops (Bisbis et al., 2018; Gunathilaka et al., 2018; Manners and van Etten,
24 2018). Figure 5.11 assesses several adaptation options based on the perceived importance of each in the
25 literature. Fruit and vegetable crops tend to be more reliant on ecosystem services in the form of pollination,
26 biocontrol, and other resources (water, nutrients, microbes, etc.), and ecosystem-based adaptation options are
27 prominent. The range of crops means that there is great potential for crop switching, but cultural and
28 economic barriers will make such options difficult to implement, with barriers to entry for production and
29 marketing (Waha et al., 2013; Magrini et al., 2016; Kongsager, 2017; Rhiney et al., 2018). Perennial crops
30 are exposed to a wide range of climate factors throughout the year and have significant barriers to
31 implementing some of the common adaptation options, such as relocation or replacing tree species/cultivar,
32 agronomic interventions on-farm are well used in high value tree crops and provide some climate resilience,
33 but longer-term options will be needed (Glenn et al., 2013; Mosedale et al., 2016; Gunathilaka et al., 2018;
34 Sugiura, 2019).
35
36 Many fruit and vegetable crops are water demanding, and adaptation responses relating to water management
37 and access to irrigation water are crucial. Rainwater storage and deficit irrigation techniques are frequently
38 mentioned as adaptation options and can minimise the burden on off-farm water supplies (Bisbis et al., 2018;
39 Acevedo et al., 2020).
40
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1
2
3 Figure 5.10: Synthesis of literature on the implementation of on-farm adaptation options across different cropping
4 systems. Adaptation options that have been implemented by growers are considered `tested', while those that have not
5 are considered `untested'. Untested options are those that appear in studies as suggestions by stakeholder or experts, but
6 were not implemented within the study. The assessment draws on >200 articles published since AR5. The confidence is
7 based on the evidence given in individual articles and on the number of articles. See SM5.2 for details.
8
9
10 5.4.4.3 Cultivar improvements
11
12 As stated in AR5, cultivar improvements are one effective countermeasure against climate change (Porter et
13 al., 2014; Challinor et al., 2016; Atlin et al., 2017). Plant breeding biotechnology for climate change
14 adaptation draws upon modern biotechnology and conventional breeding, with the latter often assisted by
15 genomics and molecular markers. Plant breeding biotechnology will contribute to adaptation for large scale
16 producers (high confidence). However, in addition to inconsistencies in meeting farmer expectations, a
17 variety of socio-economic and political variables strongly influence, and limit, uptake of climate-resilient
18 crops (Acevedo et al., 2020; Rhoné et al., 2020).
19
20 Genome sequencing significantly increases the rate and accuracy for identifying genes of agronomic traits
21 that are relevant to climate change, including adaptation to stress from pests and disease, temperature, and
22 water extremes (high confidence) (Brozynska et al., 2016; Scheben et al., 2016; Voss-Fels and Snowdon,
23 2016). Access to this information where it is needed and in practical timeframes, as well as the expertise to
24 use it will limit the sharing of benefits by the most vulnerable groups and countries (high agreement, limited
25 evidence) (Heinemann et al., 2018).
26
27 Genetic improvements for climate change adaptation using modern biotechnology have not reliably
28 translated into the field (Hu and Xiong, 2014; Nuccio et al., 2018; Napier et al., 2019), but good progress has
29 been made by conventional breeding. Desirable traits that adapt plants to environmental stress are inherited
30 as a complex of genes each of which makes a small contribution to the trait (Negin and Moshelion, 2017).
31 Adaptation by conventional breeding requires making rapid incremental changes in the best germplasm to
32 keep pace with the environment (Millet et al., 2016; Atlin et al., 2017; Cobb et al., 2019). Further
33 improvements would be difficult without in situ and ex situ conservation of plant genetic resources to
34 maintain critical germplasm for breeding (Dempewolf et al., 2014; Castañeda-Álvarez et al., 2016).
35
36 Despite the advances in sequencing, phenotyping remains a significant bottleneck (Ghanem et al., 2015;
37 Negin and Moshelion, 2017; Araus and Kefauver, 2018), the emergence of high-throughput phenotyping
38 platforms may reduce this bottle neck in future. Emerging modern biotechnology such as gene/genome
39 editing may in the future increase the ability to better translate genetic improvements into the field (medium
40 agreement, limited evidence) (Puchta, 2017; Yamamoto et al., 2018; Friedrichs et al., 2019; Kawall, 2019;
41 Zhang et al., 2019).
42
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1 Other breeding approaches assisted by genomics have been making steady gains in introducing traits that
2 adapt crops to climate change (high confidence). DNA sequence information is used to identify markers of
3 desirable traits that can be enriched in breeding programs, as well as to quantify the genetic variability in
4 species (Gepts, 2014; Brozynska et al., 2016; Voss-Fels and Snowdon, 2016). However, breeding for
5 smallholder farmers and the stresses caused by climate change is unlikely to be addressed by the private
6 sector and will require more public investment and adjusting to the local social-ecological system (Glover,
7 2014; Heinemann et al., 2014; Acevedo et al., 2020). Modern biotechnology has not demonstrated the scale
8 neutrality needed to serve smallholder dominated agroecosystems, due to a combination of the kinds of traits
9 and restrictions that come from the predominant intellectual property rights instruments used in their
10 commercialization, as well as the focus on a small number of major crop species (medium confidence)
11 (Fischer, 2016; Montenegro de Wit et al., 2020).
12
13 Globally, there is a notable lack of programs aimed specifically at breeding for climate resilience in fruits
14 and vegetables, although there have been calls to begin this process (Kole et al., 2015). Breeding for climate
15 resilience in vegetables has great potential given the range of crop species available. Tolerance to abiotic
16 stress is reasonably advanced in pulses (Araújo et al., 2015; Varshney et al., 2018), but examples of
17 translation to commercial cultivars are still limited (Varshney et al., 2018; Varshney et al., 2019). The
18 infrastructure for germplasm collection, maintenance, testing, and breeding lags behind that of major crops
19 (partly because of the large number of species involved) (Keatinge et al., 2016; Atlin et al., 2017).
20
21 Participatory plant breeding (PPB) facilitates interaction between Indigenous and local knowledge systems
22 and scientific research and can be an effective adaptation strategy in generating varieties well adapted to the
23 socio-ecological context and climate hazards (high confidence) (Table 5.5, Westengen and Brysting, 2014;
24 Humphries et al., 2015; Anderson et al., 2016; Migliorini et al., 2016; Leitão et al., 2019; Ceccarelli and
25 Grando, 2020; Singh et al., 2020).
26
27
28 Table 5.5: Participatory plant breeding as cultivar improvement adaptation method.
Region Crop(s) used for breeding Results
West Africa Sorghum and pearl millet · Released sorghum and millet varieties which were selected
for climate variability (e.g., drought), low soil fertility,
pest and disease resistance, gendered preferences for
processing, and nutrition (Camacho-Henriquez et al.,
2015; Weltzien et al., 2019).
· Farmers who adopted these varieties increased yield,
income and food security, alongside increased technical
knowledge of plant breeding, and increased breeders'
understanding of local farmers' varietal requirements
(Trouche et al., 2016).
· Joint learning with scientists led to increased genetic gain
both in terms of operational scale and focused breeding for
diverse farmer priorities (Weltzien et al., 2019).
South Potato · PPB with Indigenous Quechua and Aymara farmers
America resulted in potato varieties with traits from wild relatives,
(Andes) with yield stability, higher yields under low input use and
disease resistance under climate change impacts such as
increased hail or frost events and upward expansion of
pests and diseases (Camacho-Henriquez et al., 2015;
Scurrah et al., 2019).
Asia Maize · PPB done primarily with women farmers, led to 1500
(southwest landraces safeguarded, 12 farmer-preferred varieties
China) released and 30 landraces released, bred for improved
yield (15-20% increases), drought resistance, taste, market
potential and other priority traits (Song et al., 2019).
· Studies suggest PPB improved farmer knowledge, income,
and access to resilient seeds, and strengthened institutions
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such as women-led farmer cooperatives and a Farmer Seed
Network of China (Song et al., 2019).
1
2
3 5.4.4.4 Integrated approach to enhance agroecosystem resilience
4
5 Diversifying agricultural systems is an adaptation strategy that can strengthen resilience to climate change,
6 with socio-economic and environmental co-benefits, but tradeoffs and benefits vary by socio-ecological
7 context (high confidence) (Table 5.6, M'Kaibi et al., 2015; Bellon et al., 2016; Jones, 2017b; Schulte et al.,
8 2017; Jarecki et al., 2018; Jones et al., 2018; Luna-Gonzalez and Sorensen, 2018; Sibhatu and Qaim, 2018;
9 Renard and Tilman, 2019; Rosa-Schleich et al., 2019; Bozzola and Smale, 2020; Mulwa and Visser, 2020).
10 Crop diversification alongside livestock, fish and other species can be applied at various scales in a range of
11 systems, from rainfed or irrigated to urban and home gardens in multiple spatial and temporal arrangements
12 such as mixed planting, intercrops, crop rotation, diversified management of field margins, agroforestry
13 (Section 5.10.1.3) and integrated crop livestock systems (Section 5.10.1.1, Isbell et al., 2017; Kremen and
14 Merenlender, 2018; Dainese et al., 2019; Rosa-Schleich et al., 2019; Hussain et al., 2020; Renwick et al.,
15 2020; Tamburini et al., 2020; Snapp et al., 2021; see Section 5.14 and Cross-Chapter Box NATURAL in
16 Chapter 2).
17
18 Diversification improves regulating and supporting ecosystem services such as pest control, soil fertility and
19 health, pollination, nutrient cycling, water regulation and buffering of temperature extremes (high
20 confidence) (Barral et al., 2015; Prieto et al., 2015; Tiemann et al., 2015; Schulte et al., 2017; Beillouin et al.,
21 2019a; Dainese et al., 2019; Kuyah et al., 2019; Tamburini et al., 2020), which can in turn mediate yield
22 stability and reduced risk of crop loss according to socio-ecological contexts and time since adoption (high
23 confidence) (Prieto et al., 2015; Roesch-McNally et al., 2018; Sida et al., 2018; Williams et al., 2018; Birthal
24 and Hazrana, 2019; Degani et al., 2019; Amadu et al., 2020; Bowles et al., 2020; Li et al., 2020; Sanford et
25 al., 2021).
26
27 Agroecosystem diversification often has variable impacts depending on crop combination, agro-ecological
28 zone and soil types and rigorous assessments of adaptive gains with traditional and locally diversified
29 systems and potential trade-offs still need to be conducted across socioecological contexts. The quantitative
30 upstanding will assist in enhancing multiple benefits of diversification tailored for each condition (Table
31 5.6). Progress is also needed via breeding and/or agronomy to adapt underutilized as well as major food
32 crops to diversified agroecosystems and optimize management of nutrients, pest and disease pressure and
33 other socio-ecological constraints (Araújo et al., 2015; Foyer et al., 2016; Adams et al., 2018; Pang et al.,
34 2018).
35
36 Managing for diversity and flexibility at multiple scales is central to developing adaptive capacity. Policies
37 to support diversification include shifting subsidies towards diversified systems, public procurement for
38 diverse foods for schools and other public institutions, investment in shorter value chains, lower insurance
39 premiums and payments for ecosystem services that include diversification (Sorensen et al., 2015; Guerra et
40 al., 2017; Nehring et al., 2017; Valencia et al., 2019). Integrated landscape approaches involving multiple
41 stakeholders (Reed et al., 2016) including urban governments can support diversification at a regional scale
42 through public and private sector investment in extension services, regional supply chains, agritourism and
43 other incentives for diversified landscapes (Milder et al., 2014; Münke et al., 2015; Sorensen et al., 2015;
44 Pérez-Marin et al., 2017; Caron et al., 2018; 5.14.1.5).
45
46
47 Table 5.6: Agroecosystem diversification practices, climate change adaptation mechanisms, tradeoffs, co-benefits and
48 constraints to implementation.
Agroecosystem diversification practice and Benefits, tradeoffs and constraints to implementation with
Mechanism for climate change adaptation examples.
Crop diversification · Crop diversification reduces cereal crop sensitivity to
- Diversifying revenue streams and food precipitation variability, yield losses and crop insurance
supply (portfolio effect). payouts under drought (high confidence) (McDaniel et al.,
- Can impact multiple plant and soil 2014; Williams et al., 2016; Iizumi and Wagai, 2019;
biological and physicochemical properties Renwick et al., 2020; Huang et al., 2021; Kane et al., 2021)
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associated with building soil organic · For example, a study in Canada comparing diversified
matter, improving soil structure and water rotations to monoculture corn found significant positive
conservation yield impacts, yield stability and increased soil organic
carbon under both RCP4.5 and RCP8.5 by 2100 (Jarecki et
al., 2018).
· Diverse agroecosystems with a range of native, neglected
and introduced species, often maintained through
Indigenous knowledge and farmer seed systems, offer
adaptation opportunities in some regions (medium evidence,
high agreement) (Bezner Kerr, 2014; Westengen and
Brysting, 2014; Camacho-Henriquez et al., 2015; Ghosh-
Jerath et al., 2015; Adhikari et al., 2017; Li and Siddique,
2018; Scurrah et al., 2019).
· Diversified landscapes can also enhance cultural ecosystem
services, by supporting cultural heritage crops, recreational
and aesthetic experiences (medium confidence) (Novikova
et al., 2017; Martínez-Paz et al., 2019; Alcon et al., 2020).
· Diversified cropping systems often require new knowledge,
equipment access to inputs and viable markets for new
products (van Zonneveld et al., 2020). Barriers to
diversification, or those which support agroecosystem
simplification include environmental constraints such as
elevation or soil type, along with institutional constraints
such as low research investment, limited policy support,
subsidies that encourage monocrops, poor market access,
market instability and limited access to seeds (Kaushal and
Muchomba, 2015; DeLonge et al., 2016; Burchfield and de
la Poterie, 2018).
Legume diversification can be effective for both · Can increase food security and nutrition by increasing
mitigation and adaptation, by reducing use of cereal productivity and stability in intercropped systems,
nitrogen derived from fossil fuels, and meat diversify diets, and increase income in crop sales (high
consumption, and providing ecosystem services agreement, medium evidence) (Snapp et al., 2019; Steward
through nutrient cycling, increasing soil et al., 2019; Renwick et al., 2020), but legume production
biological activity and erosion control (Snapp et may be constrained by pest, disease, limited access to
al., 2019). genetic material, market access and food preferences
(Anders et al., 2020).
Organic amendments, no/low tillage or crop · Higher organic matter does not consistently improve soil
residue retention may increase diversity in soil hydraulic properties (Minasny and McBratney, 2018;
biological organisms, which might be important in Basche and DeLonge, 2019),
building resilience to multiple stresses such as
drought and pest pressure (Furze et al., 2017; · Can decrease yield variability under dry conditions and
Blundell et al., 2020; de Vries et al., 2020; Stefan et increase rainfed annual crop yield productivity (high
al., 2021; Yang et al., 2021). agreement) (Pittelkow et al., 2014; Williams et al., 2016;
Williams et al., 2018; Degani et al., 2019; Steward et al.,
2019; Bowles et al., 2020; Marini et al., 2020; Sanford et
al., 2021).
Livestock integration. Inclusion of legumes and · Benefits to productivity and stability of annual crop yields
other forage into crop rotation allows mixed crop and in some contexts (see Section 5.10.3, strong agreement,
livestock operations to mitigate farm-level risk and medium evidence) (Stark et al., 2018; Peterson et al., 2020;
ecosystem buffering de Albuquerque Nunes et al., 2021).
Traditional and locally adapted mixed cropping and Benefits: Resilience to extreme events such as hurricanes
agroforestry practices which include leguminous can be promoted by supporting ecosystem functions to
trees can improve soil fertility and microclimate mitigate impacts and accelerate recovery (high agreement,
(Sida et al., 2018; Amadu et al., 2020). medium evidence) (Altieri et al., 2015; Simelton et al.,
2015; Sida et al., 2018; Perfecto et al., 2019).
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· Can increase food security, livelihoods, and productivity,
but local context and resource availability must be
considered to optimize species arrangement and benefits
and can have considerable implementation barriers and
costs (high confidence) (see Sections 5.10.3, 5.14 and
Cross-Chapter Box NATURAL in Chapter 2). (Altieri et
al., 2015; Simelton et al., 2015; Sida et al., 2018; Perfecto
et al., 2019).
1
2
3 5.5 Livestock-based Systems
4
5 Livestock systems may be classified as industrial (monogastric, ruminant), grassland-based in which crop-
6 based agriculture is absent or minimal (pastoralism, agro-pastoralism), mixed rainfed combining mostly
7 rainfed cropping with livestock, and mixed irrigated systems with a significant proportion of irrigated
8 cropping interspersed with livestock. Livestock systems are located widely across all regions of the world,
9 and animal-sourced food provides humans with 39% of their protein and 18% of their calorie intake (FAO,
10 2019f). Some 400 million people depend on livestock for a substantial part of their livelihood (Robinson et
11 al., 2011).
12
13 5.5.1 Observed Impacts
14
15 Climate change affects livestock productivity and production in many ways (Porter et al., 2014; Rojas-
16 Downing et al., 2017). Evidence is accumulating that rising temperatures are increasing heat stress in
17 domestic species and affecting productivity (high confidence) (Das et al., 2016b; Godde et al., 2021).
18
19 5.5.1.1 Pastoral systems
20
21 Many grassland-based livestock systems are vulnerable to climate change and increases in climate variability
22 (high confidence) (Dasgupta et al., 2014; Sloat et al., 2018; Stanimirova et al., 2019). Decadal vegetation
23 changes from warming and drying trends have been detected in North American grasslands, with
24 implications for species composition, rangeland quality and economic viability of grazing livestock
25 (Rondeau et al., 2018; Reeves et al., 2020). Feed quality in South Asian grasslands has been negatively
26 affected, reducing food security (Rasul et al., 2019). Increased grassland degradation has been observed in
27 parts of Inner Mongolia (Nandintsetseg et al., 2021). Changing seasonality, increasing frequency of drought
28 and rising temperatures are affecting pastoral systems globally (high confidence). These and other drivers are
29 reducing herd mobility, decreasing productivity, increasing incidence of vector borne diseases and parasites,
30 and reducing access to water and feed (high agreement, medium evidence) (López-i-Gelats et al., 2016;
31 Vidal-González and Nahhass, 2018; de Leeuw et al., 2020).
32
33 5.5.1.2 Livestock distribution and climate variability
34
35 There is limited evidence of observed distributional changes in livestock species because of climate changes.
36 Asian buffalo and yak breeds in China over the past 50 years have shifted distribution due partly to increases
37 in heat stress (Wu, 2015; Wu, 2016). Nepalese cattle numbers have declined, attributed to increases in the
38 number of hot days (Koirala and Shrestha, 2017).
39
40 Climate variability has been identified as the primary cause of vegetation cover changes in Tibet since 2000
41 (Lehnert et al., 2016). Increasing inter-annual variability is a driver of farm extensification in Mediterranean
42 dairy systems (Dono et al., 2016). In Australian rangelands (Godde et al., 2019) and dairy systems (Harrison
43 et al., 2016; Harrison et al., 2017), increasing rainfall variability contributes more to stocking rate and
44 profitability variability than changes in mean rainfall.
45
46 5.5.1.3 Diseases and disease vectors
47
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1 Climate change is affecting the transmission of vector-borne diseases (Hutter et al., 2018; Semenza and Suk,
2 2018) and parasites (Rinaldi et al., 2015) in high latitudes (high confidence). Different processes link climate
3 change and infectious diseases in domesticated livestock: some show a positive association between
4 temperature and range expansion of arthropod vectors that spread the bluetongue virus. Others show a
5 contraction, such as tsetse flies that transmit trypanosome parasites of several livestock species. Positive
6 associations have been found between temperature and the spread of pathogens such as anthrax, and
7 droughts and El Niño-Southern Oscillation (ENSO) weather patterns and Rift Valley fever outbreaks in East
8 Africa (Bett et al., 2017). Observed range expansion of economically important tick disease vectors in North
9 America (Sonenshine, 2018) and Africa (Nyangiwe et al., 2018) are presenting new public health threats to
10 humans and livestock.
11
12 5.5.2 Assessing Vulnerabilities
13
14 5.5.2.1 Rising temperature and heat stress
15
16 Most domestic livestock have comfort zones in the range 10-30°C, depending on species and breed (Nardone
17 et al., 2006). At higher temperatures, animals eat 35% less per additional degree of temperature, reducing
18 their productivity and fertility. Heat stress suppresses the immune and endocrine system, enhancing
19 susceptibility of the animal to disease (Das et al., 2016b). Recent stagnation in dairy production in West
20 Africa and China may be associated with increased periods of high daily temperatures (low confidence)
21 (Rahimi et al., 2020; Ranjitkar et al., 2020). Increases in the productive capacity of domestic animals can
22 compromise thermal acclimation and plasticity creating further loss. Escalating demand for livestock
23 products in LMICs may necessitate considerable adaptation in the face of new thermal environments
24 (medium confidence) (Collier and Gebremedhin, 2015; Theusme et al., 2021). Heat effects on productivity
25 have been summarised for pigs (da Fonseca de Oliveira et al., 2019), sheep and goats (Sejian et al., 2018),
26 and cattle (Herbut et al., 2019). The direct effects of higher temperatures on the smaller ruminants (sheep and
27 goats) are relatively muted, compared with large ruminants; goats are better able to cope with multiple
28 stressors than sheep (Sejian et al., 2018). Under SSP5-8.5 to mid-century, land suitability for livestock
29 production will decrease because of increased heat stress prevalence in mid and lower latitudes (high
30 confidence) (Thornton et al., 2021).
31
32 5.5.2.2 Livestock water needs
33
34 Livestock production may account for 30 percent of all water (blue, green and grey) used in agriculture
35 (Mekonnen and Hoekstra, 2010) and can negatively affect water quality. Cropland feed production accounts
36 for 38% of crop water consumption (Weindl et al., 2017). High-input livestock systems may consume more
37 water than grazing or mixed systems, though water used per kg beef produced, for example, depends on
38 country, context, and system (Noya et al., 2019). In systems where feed production is rainfed, livestock and
39 crop water productivity may be comparable (Haileslassie et al., 2009). Direct water consumption by
40 livestock is <1-2% of global water consumption (Hejazi et al., 2014). Rising temperatures increase animal
41 water needs, potentially affecting access of herders and livestock to drinking water sources (Flörke et al.,
42 2018).
43
44 5.5.2.3 Rising temperatures and livestock disease
45
46 Climate change will have effects on future distribution, incidence, and severity of climate-sensitive
47 infectious diseases of livestock (high confidence) (Bett et al., 2017). In an assessment of climate sensitivity
48 of European human and domestic animal infectious pathogens, 63% were sensitive to rainfall and
49 temperature, and zoonotic pathogens were more climate-sensitive than human- or animal-only pathogens
50 (McIntyre et al., 2017). Over the last 75 years, >220 emerging zoonotic diseases, some associated with
51 domesticated livestock, have been identified, several of which may be affected by climate change,
52 particularly vector-borne diseases (Vaillancourt and Ogden, 2016; see Cross-Chapter Box ILLNESS in
53 Chapter 2). Walsh et al. (2018) identified both temperature and rainfall as influential factors in predicting
54 increasing anthrax outbreaks in northern latitudes. Growing infectious disease burdens in domesticated
55 animals may have wide-ranging impacts on the vulnerability of rural livestock producers in the future,
56 particularly related to human health and projected increases in zoonoses (high confidence) (Bett et al., 2017;
57 Heffernan, 2018; Rushton et al., 2018; Meade et al., 2019).
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FINAL DRAFT Chapter 5 IPCC WGII Sixth Assessment Report
1
2 5.5.2.4 Livestock and socio-economic vulnerability to climate change
3
4 There is limited evidence about the role of livestock in addressing socio-economic vulnerability. Although
5 agriculture in parts of North America has become more sensitive to climate over the last 50 years, livestock
6 have helped to moderate this effect, being less sensitive to increasing temperatures than some specialised
7 crop systems (Ortiz-Bobea et al., 2018). Increasing frequency and severity of droughts will affect the future
8 economic viability of grassland-based livestock production in the North American Great Plains (Briske et al.,
9 2021). Purchasing more forage and selling more livestock have reduced household vulnerability in semi-arid
10 parts of China over the last 35 years (Bai et al., 2019). A greater focus on sheep production away from
11 cropping has increased the resilience of farming systems in Western Australia in low-rainfall years, although
12 with mixed environmental effects (Ghahramani and Bowran, 2018). More insights are needed as to where
13 and how livestock can affect the vulnerability of farmers and pastoralists.
14
15 5.5.2.5 Effects of climate on the health and vulnerability of livestock keepers
16
17 Vulnerability to the health impacts of climate change will be shaped by existing burdens of ill-health and is
18 expected to be highest in poor and socio-economically marginalized populations (high agreement, limited
19 evidence) (Labbé et al., 2016). As well as projected changes in infectious disease burdens, labour capacity in
20 a warming climate is anticipated to decrease further, beyond the >5% drop estimated since 2000 (Watts et
21 al., 2018). Loss of labour capacity may greatly increase the vulnerability of subsistence livestock keepers
22 (high agreement, limited evidence).
23
24 5.5.2.6 Gender and other social inequalities
25
26 Vulnerability to climate change depends on demography and social roles (Mbow et al., 2019). Gender
27 inequalities can act as a risk multiplier, with women being more vulnerable than men to climate change-
28 induced food insecurity and related risks (high confidence) (Cross-Chapter Box GENDER in Chapter 18).
29 Women and men often have differential and unequal control over different productive assets and the benefits
30 they provide, such as income from livestock (Ngigi et al., 2017; Musinguzi et al., 2018). Indigenous
31 livestock keepers can be more vulnerable to climate change, partly due to on-going processes of land
32 fragmentation (Hobbs et al., 2008), historical land dispossession, discrimination, and colonialization,
33 creating greater levels of poverty and marginalization (Stephen, 2018). Adaptation actions may also be
34 affected by gender and other social inequalities (Balehey et al., 2018; Dressler et al., 2019). Men and women
35 heads of household may access institutional support for adaptation in different ways (Assan et al., 2018).
36 Further research is warranted to evaluate alternative gendered and equity-based approaches that can address
37 differences in adaptive capacity within communities.
38
39 5.5.3 Projected Impacts
40
41 There is limited evidence on future impact of climate change on livestock production, particularly in LMICs
42 (Rivera-Ferre et al., 2016).
43
44 5.5.3.1 Impacts on rangelands, feeds, and forages
45
46 Uncertainties persist regarding estimates of net primary productivity (NPP) in grazing lands (Fetzel et al.,
47 2017; Chen et al., 2018b), so estimation of climate change impacts on grasslands is challenging. Mean global
48 annual NPP is projected to decline 10 gC m-2 yr-1 in 2050 under RCP8.5, although herbaceous NPP is
49 projected to increase slightly (Boone et al., 2018; see Figure 5.11). Similar estimates were made by (Havlik
50 et al., 2014): large increases in projected NPP in higher northern latitudes (21% increase in the US and
51 Canada) and large declines in western Africa (-46% in western Africa) and Australia (-17%). The cumulative
52 effects of impacts on forage productivity globally are projected to result in 7-10% declines in livestock
53 numbers by 2050 for warming of ~2°C, representing a loss of livestock assets ranging from USD 10 to 13
54 billion (Boone et al., 2018). Changes to African grassland productivity will have substantial, negative
55 impacts on the livelihoods of >180 million people.
56
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1 Increases in above-ground NPP, and woody cover at the expense of grassland, are projected in some of the
2 tropical and subtropical drylands (Doherty et al., 2010; Ravi et al., 2010; Saki et al., 2018), in Mediterranean
3 wood-pastures (Rolo and Moreno, 2019), and in the northern Great Plains of North America (Klemm et al.,
4 2020). Godde et al. (2021) projected that woody encroachment would occur on 51% of global rangeland area
5 by 2050 under RCP8.5. The future makeup of grasslands under climate change is uncertain, given the
6 variation in responses of the component species; though this variation may provide a climate buffer (Jones,
7 2019) (low confidence). C4 grass species are regarded as less responsive to elevated carbon dioxide than C3
8 species, though this is not always the case (Reich et al., 2018).
9
10 There are other interactions between climate change and grazing effects on grasslands. Li (2018a) reported
11 strong negative responses of NPP and species richness to 4°C warming, a 50% precipitation decrease, and
12 high grazing intensity. Changes in grassland composition will inevitably change their suitability for different
13 grazing animal species, with switches from herbaceous grazers such as cattle to goats and camels to take
14 advantage of increases in shrubland (Kagunyu and Wanjohi, 2014). Rangeland feed quality may also be
15 reduced via invasive species of lower quality than native species (Blumenthal et al., 2016).
16
17
18
19 Figure 5.11: Regional percent changes in land cover and soil carbon from ensemble simulation results in 2050 under
20 emissions scenario RCP8.5 compared with 1971-2000. Plant responses were enhanced by CO2 fertilization. The larger
21 chart (lower left) shows mean changes for all rangelands, and all charts are scaled to -60 to +60 percent change. Shown
22 are annual net primary productivity (ANPP), herbaceous net primary productivity (HNPP), bare ground, herbaceous
23 (herb), shrub, and tree cover, soil organic carbon (soil carbon), aboveground live biomass (A. L. biomass), and
24 belowground live biomass (B. L. biomass). Regions as defined by the United Nations Statistics Division. The bar for
25 aboveground live biomass in Western Asia (*) is truncated and was 82%. (Boone et al., 2018).
26
27
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1 Warming and water deficits impair the quality and digestibility of a C4 tropical forage grass, Panicum
2 maximum, because of increases in leaf lignin (Habermann et al., 2019). A metanalysis Dellar (2018) of
3 climate change impacts on European pasture yield and quality found an increase in above-ground dry weight
4 under increased CO2 concentrations for forbs, legumes, graminoids and shrubs with reductions in N
5 concentrations in all plant functional groups. Temperature increases will increase yields in Alpine and
6 northern areas (+82.6%) but reduce N concentrations for shrubs (-13.6%) and forbs (-18.5%).
7
8 Increased temperatures and CO2 concentrations may increase herbaceous growth and favour legumes over
9 grasses in mixed pastures (He et al., 2019). These effects may be modified by changes in rainfall patterns,
10 plant competition, perennial growth habits, and plantanimal interactions. The cumulative effect of these
11 factors is uncertain. Large, persistent declines in forage quality are projected, irrespective of warming, under
12 elevated CO2 conditions (600 ppm and +1.5°C day/3°C night temperature increases) in North American
13 grasslands (Augustine et al., 2018). Rising CO2 concentrations may result in losses of iron, zinc, and protein
14 in plants by up to 8 percent by 2050 (Smith and Myers, 2018). Little information is available on possible
15 impacts on carbon-based micronutrients, such as vitamins. About 57% of grasses globally are C3 plants and
16 thus susceptible to CO2 effects on their nutritional quality (Osborne et al., 2014). These impacts will result in
17 greater nutritional stress in grazing animals as well as reduced meat and milk production (quality and
18 quantity) (high confidence, medium evidence).
19
20 5.5.3.2 Impacts of increased temperature on livestock
21
22 Recent research confirms the seriousness of the heat stress issue (medium evidence, high agreement).
23 Considerable increases are projected during this century in the number of "extreme stress" days per year for
24 cattle, chicken, goat, pig and sheep populations with SSP5-8.5 but many fewer with SSP1-2.6 (Thornton et
25 al., 2021: Figure 5.12; see Cross-Chapter Box MOVING PLATE in this Chapter). Resulting impacts on
26 livestock production and productivity may be large, particularly for cattle throughout the tropics and
27 subtropics and for goats in parts of Latin America and much of Africa and Asia. Pigs are projected to be
28 particularly affected in the mid-latitudes of Europe, East Asia, and North America. (Lallo et al., 2018)
29 estimated that global warming of 1.5°C and 2°C may exceed limits for normal thermo-regulation of livestock
30 animals and result in persistent heat stress for animals in the Caribbean. Breed differences in heat stress
31 resistance in dairy animals are now being quantified (Gantner et al., 2017), as are effects on sow
32 reproductive performance in temperate climates (Wegner et al., 2016). Estimates of losses in milk production
33 due to heat stress in parts of the USA, UK and West Africa to the end of the century range from 1-17%
34 (Hristov et al., 2018; Fodor et al., 2018; Wreford and Topp, 2020; Rahimi et al., 2020). Much larger losses in
35 dairy and beef production due to heat stress are projected for many parts of the tropics and subtropics: these
36 could amount to USD 22 billion per year for dairy and USD 38 billion per for beef to end-century under
37 SSP5-8.5, approximately 7% and 20% of the global value of production of these commodities in constant
38 2005 dollars.
39
40 In many LMICs, poultry contribute significantly to rural livelihoods including via modest improvements in
41 nutritional outcomes of household children (de Bruyn et al., 2018). Rural poultry are generally assumed to be
42 hardy and well adapted to stressful environments, but little information exists regarding their performance
43 under warmer climates or interactions with other production challenges (Nyoni et al., 2019).
44
45 5.5.3.3 Impacts on livestock diseases
46
47 The impacts of climate change on livestock diseases remain highly uncertain (medium evidence, high
48 agreement). Bett et al. (2017) showed positive associations between rising temperature and expansion of the
49 geographical ranges of arthropod vectors such as Culicoides imicola, which transmits bluetongue virus. A 1-
50 in-20-year bluetongue outbreak at present-day temperatures is projected to increase in frequency to 1-in-5- to
51 1-in-7 years by the 2050s, under RCP4.5 and RCP8.5, although animal movement restrictions can prevent
52 devastating outbreaks (Jones et al., 2019).
53
54 The prevalence and occurrence of some livestock diseases are positively associated with extreme weather
55 events (high confidence). There are high risks of future Rift Valley Fever (RVF) outbreaks under both
56 RCP4.5 and RCP8.5 this century in East Africa and beyond (Taylor et al., 2016; Mweya et al., 2017).
57
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1 Few studies explicitly consider the biotic and abiotic factors that interact additively, multiplicatively, or
2 antagonistically to influence host-pathogen dynamics (Cable et al., 2017). Integrative concepts that aim to
3 improve the health of people, animals, and the environment such as One Health may offer a framework for
4 enhancing understanding of these complex interactions (Zinsstag et al., 2018). Much remains unknown
5 concerning disease transmission dynamics under a warming climate (Heffernan, 2018), highlighting the need
6 for effective monitoring of livestock disease (Brito et al., 2017; Hristov et al., 2018).
7
8
9
10 Figure 5.12: Change in the number of days per year above "extreme stress" values from 2000 to the 2090s for SSP5-
11 8.5, estimated using the Temperature Humidity Index (THI). Mapped for species current global distribution (Gilbert et
12 al., 2018) (grey areas, no change). (Thornton et al., 2021), Also see Annex 1: Global to Regional Atlas.
13
14
15 5.5.3.4 Impacts on livestock and water resources
16
17 Water resources for livestock may decrease in places because of increased runoff and reduced groundwater
18 resources, as well as decreased groundwater availability in some environments (AR5). Increased
19 temperatures will cause changes in river flow and the amount of water stored in basins, potentially leading to
20 increased water stress in dry areas such as parts of the Volta River Basin (Mul et al., 2015). Toure (2017)
21 estimated decreases in groundwater recharge rates of 49% and of stored groundwater by 24% to the 2030s in
22 the Klela basin in Mali under both RCP4.5 and RCP8.5, with potentially serious consequences for water
23 availability for livestock and irrigation.
24
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1 Water intake by livestock is related to species, breed, animal size, age, diet, animal activity, temperature, and
2 physiological status of animals (Henry et al., 2018). Direct water use by cattle may increase by 13% for a
3 temperature increase of 2.7°C in a sub-tropical region (Harle et al., 2007). Changes in water availability may
4 arise because of decreased supply or increased competition from other sectors. Availability changes may be
5 accompanied by shifts in water quality, such as increased levels of microorganisms and algae, that can
6 negatively affect livestock health (Naqvi et al., 2015). In arid lands, projected decreases in water availability
7 will severely compromise reproductive performance and productivity in sheep (Naqvi et al., 2017). In
8 higher-input livestock systems, water costs may increase substantially owing to increased competition for
9 water (Rivera-Ferre et al., 2016).
10
11 5.5.3.5 Livestock and climate variability
12
13 Information on future climate variability changes on livestock system productivity does not exist yet.
14 Increases in climate variability may increase food insecurity in the future, mediated through increased crop
15 and livestock production variability (Thornton and Herrero, 2014) in LMICs. Rainfall variability increases in
16 pastoral lands have been linked to declining cattle numbers (Megersa et al., 2014). Changes in future climate
17 variability may have large negative impacts on livestock system outcomes (Sloat et al., 2018; Stanimirova et
18 al., 2019); these effects can be larger than those associated with gradual climate change (limited evidence,
19 medium agreement) (Godde et al., 2019). In grasslands, (Chang et al., 2017) (Europe) and Godde et al.
20 (2020) (globally) projected increases in biomass inter-annual variability, the worst effects occurring in
21 rangeland communities that are already vulnerable. Ways in which climate variability impacts have been
22 addressed in the past, such as via herd mobility, may become increasingly unviable in the future (Hobbs et
23 al., 2008).
24
25 5.5.3.6 Societal impacts within the production system
26
27 Livestock play important social (Kitalyi et al., 2005) and cultural (Gandini and Villa, 2003) roles in many
28 societies. Climate change will negatively affect the provisioning of social benefits in many of the world's
29 grasslands (medium confidence). Examples include moving to semi-private land ownership models, driven in
30 part by climate change, that are changing social networks and limiting socio-ecological resilience in pastoral
31 systems in East Africa (Kibet et al., 2016; Bruyere et al., 2018) and Asia (Cao et al., 2018a); altering
32 traditional food, resource and medicine sharing mechanisms in West Africa (Boafo et al., 2016); and the
33 limited ability of current livestock systems to satisfy societies' demand for cultural ecosystem services in
34 Northwest Europe (Bengtsson et al., 2019). The societal impacts of climate change on livestock systems may
35 interact with drivers of change and increase herders' vulnerability via processes of sedentarization and land
36 fragmentation, both of which may result in decreased animal access to rangelands (Adhikari et al., 2015;
37 Cross-Chapter Box MOVING PLATE this Chapter). Stronger linkages are needed between ecosystem
38 service and food security research and policy to address these challenges (Gentle and Thwaites, 2016;
39 Bengtsson et al., 2019).
40
41 5.5.4 Adaptation in Livestock-based Systems
42
43 Livestock adaptation options are increasingly being studied with methods such as agent-based household
44 models (Hailegiorgis et al., 2018), household models that disaggregate climate scenarios as well as
45 differentiating farms of varying types and farmer attributes (Descheemaeker et al., 2018), new meso-scale
46 grassland models (Boone et al., 2018), and modelling approaches that capture decision making at the farm
47 level for sample populations (Henderson et al., 2018).
48
49 Many grassland-based livestock systems have been highly resilient to past climate risk, providing a sound
50 starting point for current and future climate change adaptation (Hobbs et al., 2008). These adaptations
51 include more effective matching of stocking rates with pasture or other feed production; adjusting herd and
52 watering point management to altered seasonal and spatial patterns of forage production; managing diet
53 quality, which also helps reduce enteric fermentation in ruminants and thus greenhouse gas emissions (using
54 diet supplements, legumes, choice of introduced pasture species and pasture fertility management); more
55 effective use of silage, rotational grazing or other forms of pasture spelling; fire management to control
56 woody thickening; using better-adapted livestock breeds and species; restoration of degraded pastureland;
57 migratory pastoralist activities; and a wide range of biosecurity activities to monitor and manage the spread
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1 of pests, weeds, and diseases (Herrero et al., 2015; Godde et al., 2020). Combining adaptations can result in
2 increases in benefits in terms of production and livelihoods over and above those attainable from single
3 adaptations (high confidence) (Bonaudo et al., 2014; Thornton and Herrero, 2015; ul Haq et al., 2021).
4
5 The adaptations that livestock keepers have been undertaking in Asia (Hussain et al., 2016; Li et al., 2017)
6 and Africa (Belay et al., 2017; Ouédraogo et al., 2017) are largely driven by their perceptions of climate
7 change. Keeping two or more species of livestock simultaneously on the same farm can confer economic and
8 sustainability benefits to European farmers (Martin et al., 2020). Some livestock producers are changing and
9 diversifying management practices, improving access to water sources, increased uptake of off-farm
10 activities, trading short-term profits for longer-term resilience benefits and migrating out of the area (Hussain
11 et al., 2016; Berhe et al., 2017; Merrey et al., 2018; Thornton et al., 2018; Espeland et al., 2020). Others are
12 adopting more climate-resilient livestock species such as camels (Watson et al., 2016a), using climate
13 forecasts at differing time scales, and benefiting from innovative livestock insurance schemes, though
14 challenges remain in their use at scale (Dayamba et al., 2018; Hansen et al., 2019a; Johnson et al., 2019).
15
16 In West Africa, cattle and small ruminant producers and traders are changing strategies in response to
17 emerging market opportunities as well as to multiple challenges including climate change (Gautier et al.,
18 2016; Ouédraogo et al., 2017). Niles (2017) found that reduced food insecurity in 12 countries was
19 associated with livestock ownership, providing cash for food purchases. Livestock ownership or switching to
20 smaller, local breeds does not automatically translate into positive nutrition outcomes for women and
21 children, although it may if communities see such animals as suitable for husbandry by women (Chanamuto
22 and Hall, 2015); the relationship is complex (Nyantakyi-Frimpong and Bezner-Kerr, 2015; Dumas et al.,
23 2018).
24
25 Options for adapting domestic livestock systems to increased exposure to heat stress (Table 5.7) include
26 breeding and crossbreeding strategies, species switching, low-cost shading alternatives and ventilation and
27 building-design options (Chang-Fung-Martel et al., 2017; Godde et al., 2021). In utero exposure to heat
28 stress may increase adaptive capacity in later life, though the underlying mechanisms are incompletely
29 understood (Skibiel et al., 2018). For confined livestock systems in temperate regions, the economic
30 consequences of adapting to heat stress are still being quantified.
31
32 New research is investigating the prospects for accelerating traditional and novel breeding processes for
33 animal traits that may be effective in improving livestock adaptation as well as production (Stranden et al.,
34 2019; Barbato et al., 2020). Even if the technical challenges of using new tools such as CRISPR-Cas9 for
35 genome editing in livestock are overcome, the granting of societal approval to operate in this research space
36 may be elusive (Herrero et al., 2020; Menchaca et al., 2020).
37
38
39 Table 5.7: Selected adaptations to heat stress in livestock systems.
Adaptation Example Reference
Breeding for heat Sheep and cattle farming systems in southern Australia Moore and
stress tolerance under SRES A2. Projected not to improve livestock Ghahramani (2014)
productivity by 2070, even in drier locations.
"Slick hair" In the Caribbean, introduction of a "slick hair" gene into (Ortiz-Colón et al.
breeding Holstein cows by crossbreeding with Senepols to increase (2018)
thermo-tolerance and productivity. An integrated approach
to heat-stress adaptation will still be needed, including
shading strategies, for example.
Crossbreeding Crossbreeding with Indigenous sheep breeds as an Wilkes et al. (2017)
adaptation option in Mongolia produced some benefits in
productivity and improved adaptation to winter cold. Best
combined with other improved management interventions.
In general, effectiveness of crossbreeding as an adaptation
strategy will be dependent on context.
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Species switching
Switching from large ruminants to more heat-resilient goats Silanikove and
for dairy production in Mediterranean systems to adapt to Koluman (2015)
increasing heat stress.
Switching from cattle to more heat- and drought-resilient Wako et al. (2017)
camels in pastoral systems of southern Ethiopia as an
adaptation to increasing drought.
Shading, fanning, Low-capital relief strategies (shading with trees or different York et al. (2017)
bathing types of shed; bathing animals several times each day;
installing electric fans in sheds) are effective at reducing Pezzopane et al.
heat stress impacts on household income in smallholder (2019)
dairy systems in India.
Different tree arrangements in silvopastoral systems in
Brazil were effective in reducing thermal loads by up to
22% for animals compared with full-sun pasture.
Ventilation & A wide range of different ventilation systems, cooling Vitt et al. (2017)
cooling systems systems and building designs for confined and seasonally Derner et al. (2018),
confined intensive livestock systems (pigs, poultry, beef, Hempel and Menz
dairy) in temperate regions. Economic consequences and (2019), Mikovits et al.
profitability of different options under different RCPs are (2019), Schauberger et
still being assessed. al. (2019b)
In utero exposure to Potential as an adaption option is uncertain, as there are
heat stress different effects of in utero heat stress exposure and the
mechanisms are not completely understood:
· Cows may be better adapted to heat stress conditions at Ahmed et al. (2017)
maturity via improved regulation of core body Monteiro et al. (2016),
temperature. Boddicker et al. (2014)
· Cow milk yield at first lactation was reduced
· Nutrient partitioning and carcass composition were
altered in pigs
1
2
3 5.5.4.1 Contributions of Indigenous knowledge and local knowledge
4
5 Indigenous knowledge has a role to play in helping livestock keepers adapt (medium confidence), though the
6 transferability of this knowledge is often unclear. Pastoralists' local knowledge of climate and ecological
7 change can complement scientific research (Klein et al., 2014), and local knowledge can be mobilised to
8 inform adaptation decision-making (Klenk et al., 2017). While Indigenous weather forecasting systems
9 among pastoralists in Ethiopia (Balehegn et al., 2019; Iticha and Husen, 2019) and Uganda (Nkuba et al.,
10 2020) are effective, synergies can be gained by combining traditional and modern knowledge to help
11 pastoralists adapt. Sophisticated knowledge of feed resources among agro-pastoralists in West Africa is
12 being used to increase system resilience (Naah and Braun, 2019). Understanding local knowledge for
13 adaptation can present research challenges, for which new multi-disciplinary research methods may be
14 needed (Reyes-Garcia et al., 2016; Roncoli et al., 2016). In particular, the complexities of knowledge,
15 practice, power, local governance and politics need to be addressed (Hopping et al., 2016; Scoville-Simonds
16 et al., 2020).
17
18
19 [START BOX 5.5 HERE]
20
21 Box 5.5: Alternative Sources of Protein for Food and Feed
22
23 Alternative protein sources for human food and livestock feed are receiving considerable attention.
24 Laboratory or "clean meat" is one potential contributor to the human demand for protein in the future
25 (SRCLL). Such technology may be highly disruptive to existing value chains but could lead to significant
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1 reduction in land use for pastures and crop-based animal feeds (Burton, 2019; Rosenzweig et al., 2020). The
2 impacts on GHG emissions depend on the meat being substituted and the trade-off between industrial energy
3 consumption and agricultural land requirements (Mattick et al., 2015; Alexander et al., 2017; Rubio et al.,
4 2020b; Santo et al., 2020). Livestock feeds can make use of other protein sources: insects are generally rich
5 in protein and can be a significant source of vitamins and minerals. Black soldier fly, yellow mealworm and
6 the common housefly have been identified for potential use in feed products in the EU, for example
7 (Henchion et al., 2017). Replacing land-based crops in livestock diets with some proportion of insect-derived
8 protein may reduce the GHG emissions associated with livestock production, though these and other
9 potential effects have not yet been quantified (Parodi et al., 2018; Section 5.13.2). Other sources are high-
10 protein woody plants such as paper mulberry (Du et al., 2021) and algae, including seaweed. While
11 microalgae and cyanobacteria are mainly sold as a dietary supplement for human consumption, they are also
12 used as a feed additive for livestock and aquaculture, being nutritionally comparable to vegetable proteins.
13 The potential for cultivated seaweed as a feed supplement may be even greater: some red and green
14 seaweeds are rich in highly digestible protein. Asparagopsis taxiformis, for example, also decreases methane
15 production in both cattle and sheep when used as a feed supplement (Machado et al., 2016; Li et al., 2018b).
16 Novel protein sources may have considerable potential for sustainably delivering protein for food and feed
17 alike, though their nutritional, environmental, technological, and socio-economic impacts at scale need to be
18 researched and evaluated further.
19
20 [END BOX 5.5 HERE]
21
22
23 5.6 Forestry Systems
24
25 Forests play a vital role in the ecology of the planet, including climate regulation and provide a range of
26 important ecosystem services within their local landscape. Moreover, they are essential to the well-being of
27 millions of people around the world. Forests are sources of food contributing about 0.6% of global food
28 consumption and provide important products, such as timber and non-timber forest products (NTFPs) (FAO,
29 2014). Indigenous Peoples and local communities are estimated to manage at least 17% of total carbon (or
30 293×109 Mg) stored in forest in sixty-four assessed countries (RRI, 2018a). While small in number,
31 numerous local communities around the world are highly or entirely dependent on forests for their food
32 supply (Karttunen et al., 2017). An estimated 9 percent of the world's rural population is lifted above the
33 extreme poverty line because of income from forest resources (World Bank, 2016). Additionally, forest
34 income plays a particularly important role in diversifying the income sources of poor households, reducing
35 their vulnerability to loss from one source of income. This section covers an assessment of the impacts of
36 climate change on forestry production systems and the adaptation options available. Non-timber forest
37 products will be covered in the next section.
38
39 5.6.1 Observed Impacts
40
41 The IPCC AR5 stated that there is high confidence that numerous plants and animal species have already
42 migrated, changed their abundance, and shifted their seasonal activities as a results of climate change (Settele
43 et al., 2014). The report highlighted the widespread deaths of trees in many forested areas of the world.
44 Forest dieback could significantly affect wood production among other impacts.
45
46 The Special Report on Climate Change and Land (SRCCL) (Barbosa et al., 2019) concluded that climate
47 change will have positive and negative effects on forests, with varying regional and temporal patterns. For
48 example, the SRCCL noted the increasing productivity in high latitude forests such as those in Siberia. In
49 contrast, negative impacts are already being observed in other regions such as increasing tree mortality due
50 to wildfires.
51
52 In the past years, tree mortality continued to increase in many parts of the world. Large pulses of tree
53 mortality were consistently linked to warmer and drier than average conditions for forests throughout the
54 temperate and boreal biomes (high confidence) (Sommerfeld et al., 2018; Seidl et al., 2020). Long-term
55 monitoring of tropical forests indicates that climate change as begun to increase tree mortality and alter
56 regeneration (Hubau et al., 2020; Sullivan et al., 2020). Climate related dieback has also been observed due
57 to novel interactions between the life cycles of trees and pest species (Kurz et al., 2008; Lesk et al., 2017;
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1 Sambaraju et al., 2019). A recent example of the impacts of climatic extremes is the European drought of
2 2018 (Buras et al., 2020), which led to a significant browning of the vegetation and resulted in widespread
3 tree mortality (high confidence) (Brun et al., 2020; Schuldt et al., 2020). This brought markets for conifer
4 timber close to a collapse in parts of Europe, posing considerable challenges for timber-based forestry and
5 leading to cascading impacts on society (Hlásny et al., 2021). Overall, there is robust evidence and medium
6 agreement that provisioning services of boreal and temperate forests are affected negatively by forest
7 disturbances, while for cultural services only limited evidence with medium agreement exists (Thom and
8 Seidl, 2016).
9
10 Increasingly, climate impacts on the recovery of forests after disturbance are observed: Using data from the
11 past 20 years and 33 wildfires, it has been shown that post-fire regeneration of Pinus ponderosa and
12 Pseudotsuga menziesii in the western United States has declined because of climate change and increased
13 severity of fires (Davis et al., 2019). However, the observed patterns of post-disturbance recovery vary with
14 region, with reduced tree regeneration reported for the Western US (Stevens-Rumann and Morgan, 2019;
15 Turner et al., 2019) but robust recovery observed in Canada (White et al., 2017) and Central Europe (medium
16 confidence) (Senf et al., 2019).
17
18 Also, the distribution and traits of trees are increasingly influenced by climate change, with impacts for local
19 ecosystem service supply. In the United States, a study of 86 tree species/groups over the past three decades
20 showed that more tree species have shifted westward (73%) than poleward (62%) in their abundance (Fei et
21 al., 2017). This was due more to changes in moisture availability than to changes in temperature. As climate
22 has warmed, trees are growing faster with longer growing seasons. However, a study of forests in Central
23 Europe revealed that wood density has decreased since the 1870s (Pretzsch et al., 2018). This means that
24 increasing tree growth might not directly translate to increased total biomass and carbon sequestration.
25
26 5.6.2 Projected Impacts
27
28 AR5 stated that other stressors such as human-driven land use change and pollution will continue to be the
29 main causes of forest cover change in the next three decades (Settele et al., 2014). In the second half of this
30 century, it was projected that climate change will be a strong stressor of change in forest ecosystems. Many
31 forest species may not be able to move fast enough to adjust to new climate conditions. In some cases, a
32 warmer climate could lead to extinction of species.
33
34 The SR15 concluded that limiting warming to 1.5°C will be more favourable to terrestrial ecosystems,
35 including forests relative to a 2°C warming (Hoegh-Guldberg et al., 2018). In general, a 2°C warming could
36 lead to two times more area of biome shifts compared to a 1.5°C warming. As a result, keeping a cooler
37 average global temperature will lead to lower extinction risks. The special report supports the AR5
38 conclusion that a warmer planet will impact wide swaths of forests adversely. For example, higher
39 temperatures will promote fire, drought, and insect disturbances. Consistent with AR5, SRCCL projected
40 that tree mortality will increase with climate change (Barbosa et al., 2019). In addition, forests will be more
41 exposed to extreme events such as extreme heat, droughts, and storms. The incidence of forest fires will
42 likewise increase.
43
44 Additional evidence since the above reports were published supports their overall conclusions. For example,
45 at the global scale, modelling the vulnerability of 387 forest ecoregions under future climate change (to 2080
46 using the average of five GCMs and RCP 4.5 and 8.5) across different biomes, biogeographical realms and
47 conservation statuses showed that 8.8% of global forest ecoregions are highly vulnerable in a low-
48 greenhouse-gas-concentration scenario, and 32.6% of the global forest ecoregions were highly vulnerable in
49 the high-greenhouse-gas-concentration scenario (Wang et al., 2019a). Furthermore, a recent synthesis of the
50 literature suggests that climate change will result in younger and shorter forests globally (McDowell et al.,
51 2020). In Asia, a systematic review of climate change impacts on tropical forests revealed that future climate
52 may lead to changes in species distribution, forest structure and composition as well as phenology (Deb et
53 al., 2018).
54
55 Overall, studies indicate both negative and positive climate change impacts on forest production systems.
56 Some forests in the US could benefit slightly from CO2 fertilisation (using IGSM-CAM and MIROC3.2 till
57 2100) resulting in increased productivity especially for hardwoods (Beach et al., 2015). A study across
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1 Europe showed that both productivity gains (mostly in Northern and Central Europe, up to +33%) and losses
2 (predominately in Southern Europe, up to -37%) are possible until the end of the 21st century (Reyer et al.,
3 2017). The study further indicated that disturbances would reduce gains and exacerbate losses of productivity
4 throughout Europe under climate change (Reyer et al., 2017). For Central and Eastern Canada, decreasing
5 biomass production is projected as a result of increasing disturbance from wildfire and drought (Brecka et
6 al., 2020). Climate-induced disturbances could also reduce the temporal stability of ecosystem service supply
7 (Albrich et al., 2018), increasing the volatility of timber markets (medium confidence). More broadly, climate
8 change could lead to abrupt changes and the crossing of tipping points, resulting in profoundly altered future
9 forest development trajectories (Turner et al., 2020). Some studies suggest that such threshold could already
10 be crossed at relatively low warming levels of +2°C (Elkin et al., 2013; Albrich et al., 2020), with substantial
11 implications for ecosystem service supply (limited evidence, high agreement).
12
13 Regional studies on the potential future effects of climate change on forest production systems indicate
14 diverse impacts. In Germany, drier conditions in 2070 (RCP 8.5; GCMs INM-CM4, ECHAM6 and
15 ACCESS1.0) are expected to benefit the mean annual increment at biological rotation age of Scots pine and
16 oak, while beech might suffer losses of up to 3 m3ha1yr1 depending on climate scenario and region (Albert
17 et al., 2018). In India, 46% of the forest grid points were found to have high, very high, or extremely high
18 vulnerability under future climate in the short term (2030s) under both RCP 4.5 and 8.5, increasing to 49 and
19 54%, respectively, in the long term (2080s) (Sharma et al., 2017). In addition, forests in the higher rainfall
20 zones show lower vulnerability as compared to drier forests under future climate, which is in contrast to dry
21 forests in Central and South America cited above. Warming and drying trends are projected to reduce timber
22 production in the neotropics in some cases (Hiltner et al., 2021). Also in India, a study using CMIP (RCP4.5
23 and 8.5 with two time slices 20212050 and 20702099) shows how forests in five districts in Himachal
24 Pradesh in Western Himalayan region are vulnerable to global warming (Upgupta et al., 2015). In the Guiana
25 Shield, climate projections under RCP 2.5 and 8.5 led to decreasing the basal area, above-ground fresh
26 biomass, quadratic diameter, tree growth and mortality rates of tropical forests (Aubry-Kientz et al., 2019).
27 In Central Africa, projections under RCP 4.5 and 8.5 showed a general increase in growth, mortality and
28 recruitment leading to a strong natural thinning effect, with different magnitudes across species (Claeys et
29 al., 2019).
30
31 On a global and regional scale, there is limited evidence and high agreement (medium confidence) that
32 climate change will increase global and regional supply of timber and other forest products. To date, there
33 are eight studies assessing the total economic impacts of climate change on the forestry sector at the global
34 level. Some of them have assumed only flow effects of climate change by using the projected changes in
35 yields of forest types from integrated economic models (Perez-Garcia et al., 1997; Perez-Garcia et al., 2002;
36 Buongiorno, 2015), while other studies have assumed both flow and stock effects by accounting for changes
37 in forest yields, dieback effects and biomes migration (Sohngen et al., 2001; Lee and Lyon, 2004; Tian et al.,
38 2016; Favero et al., 2018; Favero et al., 2021).
39
40 According to these studies, global timber supply will increase as the result of an increase in global forest
41 growth under climate change scenarios (medium confidence). Some studies indicate that timber supply is
42 projected to increase more in tropical and subtropical areas because of the assumed availability of short-
43 rotation species which are likely to make adaptation easier for forest owners in these regions relative to
44 others (Sohngen et al., 2001; Perez-Garcia et al., 2002; Tian et al., 2016) while others indicate that temperate
45 areas will experience the largest increase in supply (Favero et al., 2018; Favero et al., 2021). The results are
46 very sensitive to the climate change scenarios tested, the climate and vegetation models used and the climate
47 drivers that are considered. For example, Tian et al.(2016) and Favero et al.(2018; 2021) used the same
48 economic model (the global timber model) but different climate scenarios and vegetation models, obtaining
49 different results.
50
51 The increasing supply induces lower global timber prices (medium confidence). Studies estimate that the
52 prices are likely to decline between 1% to 38% in 2100 with respect to a no climate change scenario
53 depending on the model and the climate change scenario assumed (climate change is represented as a change
54 in greenhouse gas concentration, global average temperature or radiative forcing) (Favero et al., 2018;
55 Favero et al., 2021). Clearly, further studies are needed considering a wider set of vegetation and climate
56 models and incorporating the impacts of extreme events (such as droughts and wildfires).
57
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1 There are a number of national and regional scale studies exploring the impact of climate change on yields
2 and markets of wood products, with mixed results. In Finland, it is projected that timber yield in the north
3 will increase in Scots pine and birch stands by 33145% and 42123%, compared to the current climate,
4 depending on the GCM and thinning regime using a 90-year rotation (10 individual GCM projections under
5 the RCP4.5 and RCP8.5 forcing scenarios) (ALRahahleh et al., 2018). However, in Norway spruce stands,
6 yield could decline by up to 35%, under GFDL-CM3 RCP8.5 and increase by up to 39%, under CNRM-
7 CM5 RCP8.5, compared to the current climate.
8
9 In Germany, timber harvest was projected to increase slightly (< 10%) in 2045 using the process-based
10 forestry model (4C) driven by three management strategies (nature protection, biomass production and a
11 baseline management) and an ensemble of regional climate scenarios (RCP2.6, RCP 4.5, RCP 8.5) (Gutsch
12 et al., 2018). Similarly, average production of pulpwood in slash pine stands in the Southeastern United
13 States are projected to increase by 7.5 m3 ha-1 for all climatic scenarios using 3-PG forest growth model by
14 2100 (RCP4.5 and RCP8.5; CanESM2) (Susaeta and Lal, 2018).
15
16 5.6.3 Adaptation
17
18 AR5 notes that natural ecosystems have built-in adaptation ability (Settele et al., 2014). However, this
19 capacity will not be enough to prevent loss of forest ecosystem services because of projected climate change
20 in this century under RCP 6.0 and 8.5. Management actions could reduce the risks of impacts to forest
21 ecosystems but only up to a certain point.
22
23 A systematic review of literature revealed that successful adaptation in forest management can be achieved if
24 there are partnerships between key stakeholders such as researchers, forest managers, and local actors
25 (Keenan, 2015). Such partnerships will lead to a shared understanding of climate-related challenges and
26 more effective decisions. Forest managers in some countries of the world seem to have high awareness of
27 climate change (van Gameren and Zaccai, 2015; Seidl et al., 2016; Sousa-Silva et al., 2016). However, they
28 need more information on how they can adjust their practices in response to climate change. Institutional and
29 policy context needs to be considered to facilitate adaptation by forest managers (Sousa-Silva et al., 2016;
30 Andersson et al., 2017).
31
32 5.6.3.1 Adaptation measures in sustainable forest management
33
34 A wide range of measures exist to adapt sustainably managed forests of the boreal and temperate zone to
35 climate change (Kolström et al., 2011; Gauthier et al., 2014; Keenan, 2015). Evidence emerging since the
36 last assessment report further bolstered the notion that adapting the tree species composition to more warm-
37 tolerant and less disturbance-prone species can significantly mitigate climate change impacts (high
38 confidence) (Duveneck and Scheller, 2015; Seidl et al., 2018). Assisting the establishment of species in
39 suitable habitats is one option to achieve climate-adapted tree species compositions (Benito-Garzón and
40 Fernández-Manjarrés, 2015; Iverson et al., 2019). Furthermore, increasing the diversity of tree species within
41 stands can have positive effects on tree growth and reduce disturbance impacts (high confidence) (Neuner et
42 al., 2015; Jactel et al., 2018; Ammer, 2019). Some studies also suggest a positive effect of increased
43 structural diversity, e.g., on forest resilience (moderate confidence) (Lafond et al., 2013; Koontz et al., 2020).
44 Managing for continuous forest cover can also help to maintain the forest microclimate and buffer tree
45 regeneration and the forest floor community against climate change (high confidence) (De Frenne et al.,
46 2013; Zellweger et al., 2020). Reducing stocking levels e.g., through thinning has been found to effectively
47 mitigate drought stress (Gebhardt et al., 2014; Elkin et al., 2015; Bottero et al., 2017), yet effects vary with
48 species and ecological context (robust evidence, medium agreement) (Sohn et al., 2016; Castagneri et al.,
49 2021). Also shortened rotation periods have been suggested in response to climate-induced increases in
50 growth and disturbance (Jönsson et al., 2015; Schelhaas et al., 2015). However, recent evidence suggests that
51 these measures diminish in efficiency under climate change and can have corollary effects on other important
52 forest functions such as carbon storage and habitat quality (medium confidence) (Zimová et al., 2020). Also,
53 measures targeting landscape structure and composition have proven effective for increasing the climate
54 resilience of forest systems (medium confidence) (Aquilue et al., 2020; Honkaniemi et al., 2020). While an
55 increasing number of adaptation measures exist for sustainably managed forests, many studies highlight that
56 the lead times for adaptation in forestry are long and that some vulnerabilities might remain also after
57 adaptation measures have been implemented. Furthermore, the costs and benefits of adaptation measures
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1 relative to other goals of sustainable forest management, such as the conservation of biological diversity,
2 have to be considered (Felton et al., 2016; Zimová et al., 2020; see CCP7 5.3.1 Adaptation Response
3 Options).
4
5
6 [START BOX5.6 HERE]
7
8 Box 5.6: Contributions of Indigenous and local knowledge: an example
9
10 Indigenous and local people have long histories of adaptation to climate hazards in forests (see Eriksen and
11 Hankins, 2014; Neale et al., 2019; Bourke et al., 2020; Long et al., 2020; Williamson, 2021 for notable
12 examples in Australia and North America). In this section we present a North American example of an
13 indigenous adaptation practice developed by the Karuk Tribe in northern California. The Karuk Climate
14 Adaptation Plan focuses on the use of cultural fire as climate adaptation, places a central importance on
15 restoring human ecological caretaking responsibilities, and emphasizes the need for collaboration, public
16 education, and policy advocacy to achieve these outcomes.
17
18 The Karuk Climate Adaptation Plan utilizes a combination of western science and Karuk traditional
19 ecological knowledge. The plan centres on 22 focal species as cultural indicators as cues for human
20 responsibilities and the particular techniques of fire application across seven habitat management zones (e.g.,
21 multiple forest types as well as riverine, riparian and montane systems). These adaptations range from
22 specific prescriptions for the use of fire to lower river temperatures in acute scenarios (David et al., 2018), to
23 protocols for treatment of grasslands and the use of high elevation meadows as fuel breaks. The plan also
24 includes chapters on adaptations for tribal sovereignty, the mental and physical health effects of the changing
25 climate and the protection of critical tribal infrastructure.
26
27 One aspect of Indigenous fire knowledge featured in the Karuk Climate Adaptation Plan is the culture-
28 centric perspective on vegetation zones which are organized in relation to the elevation band in which smoke
29 inversions occur (Figure Box 5.6.1). Within this system, burn timing follows a gradient that tracks the
30 reproductive life cycles of season and elevational migrant species, the calving of elk as well as the nesting of
31 birds. Within this system, elevational migrants are indicators of when to stop burning at one location and
32 move upslope, following receding snows.
33
34 The plan also calls for the restoration of Indigenous fire science in emergency scenarios such as when rivers
35 become too hot for salmon. With such fires localized, smoke inversions cool water temperatures through a
36 variety of mechanisms including shading river systems and reducing evapo-transpiration thereby increasing
37 stream flow (David et al., 2018).
38
39
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1
2 Figure Box 5.6.1: Seasonality and elevation dynamics of cultural indicators in Karuk Cultural Management Zones
3 based in Karuk traditional ecological knowledge.
4
5
6 [END BOX 5.6 HERE]
7
8
9 5.6.3.2 Linking adaptation and mitigation through REDD+
10
11 Reducing Deforestation and Forest Degradation plus (REDD+) is a climate mitigation strategy which could
12 also provide important climate change adaptation co-benefits, e.g., sustainable forest management could
13 provide long term livelihoods to local communities and enhance resilience to climate risks (Turnhout et al.,
14 2017), but with major challenges related to REDD+ implementation and forest use remain such that it has
15 not been implemented successfully at scale (Table 5.8).
16
17
18 Table 5.8: Challenges and solutions for Reducing Deforestation and Forest Degradation (REDD+)
Challenges with REDD+ implementation Solutions for successful forest management
Legal: lack of carbon rights in national legislations There is high confidence that implementing social
(Sunderlin et al., 2018; RRI, 2018b); unclear forestland safeguards such as a Free Prior and Informed Consent
tenure systems (Resosudarmo et al., 2014);. (FPIC) is vital to adequately involving Indigenous
Peoples and local communities in REDD+ (White,
2014; Raftopoulos and Short, 2019). Indigenous
Peoples, consisting of at least 370 million people,
manage or have tenure rights over a quarter of the
world's land surface (around 38 million km2)
encompassing about 40% of the world's protected
areas (Garnett et al., 2018; RRI, 2018a).
Food security and livelihoods: Negative impacts of There is high agreement that REDD+ and other green
REDD+ on food security, agroforestry and swidden adaptation and mitigation efforts need to cooperate
agriculture (Fox et al., 2014; Holmes et al., 2017). with Indigenous Peoples and other local communities
who depend on forest resources for their livelihoods
and food security (Wallbott, 2014; Mccall, 2016;
Brugnach et al., 2017; Vanclay, 2017; Garnett et al.,
2018; Paneque-Galvez et al., 2018; Sunderlin et al.,
2018; Schroeder and Gonzalez, 2019).
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Political and socio-culural: land acquisition or `green There is low confidence as to whether community
grabbing' (Asiyanbi, 2016; Corbera et al., 2017); forestry is compatible with REDD+ (Hajjar et al.,
(mis)communicating the concept of carbon (Kent and 2021). This is mainly due to lack of carbon payments
Hannay, 2020); and lack of influence of Indigenous and and the variety of approaches to REDD+. There is
local communities' representation in global and national high confidence that restoring land access and rights
REDD+ negotiations (Wallbott, 2014; Dehm, 2016). In via transfer of formal land titles to Indigenous and
the absence of social and environmental safeguards, local communities improves biodiversity conservation
REDD+ could drive large-scale land acquisitions by and carbon sequestration.
states and corporations resulting in global land grabs (or
green grabbing), negatively affecting the food security,
livelihoods and tenure rights of Indigenous and local
communities (limited evidence, high agreement) (Carter
et al., 2017; Lund et al., 2017; Borras et al., 2020).
1
2
3 5.7 Other Natural Products
4
5 Natural products such as medicinal plants, wild food (plants, animals, mushrooms) and resins (e.g., gum arabic
6 and frankincense) have high commercial value and contribute an important source of livelihood in some
7 regions. One in six persons globally live in or near forests and many depend on forest resources for some of
8 their livelihood and needs, particularly in low- and middle-income countries (Vira et al., 2016; Newton et al.,
9 2020). The FAO has estimated that in 2011 non-wood forest products, including medicinal plants, contributed
10 over 88 billion USD to the global economy (FAO, 2014). Greater diversity in local knowledge and Indigenous
11 knowledge of natural resources supports resilience in the face of hazards, especially in environments with high
12 levels of uncertainty (Berkes et al., 2003; Blanco and Carriere, 2016).
13
14 5.7.1 Medicinal Plants
15
16 The World Health Organization lists traditional medicine as an essential component of culturally appropriate
17 healthcare (WHO, 2013). Medicinal plants make up the primary source of medicine for 70 to 95% of people
18 in low- and middle-income countries and are used widely in wealthier countries (Applequist et al., 2020).
19 Continued use of medicinal plants ensures millions of rural people have access to effective treatments for day-
20 to-day illness and infection and thus improves their health and resilience to climate change.
21
22 Indigenous Peoples largely depend on medicinal plants for their healthcare need in different parts of the world
23 (de Boer and Cotingting, 2014; Silva et al., 2020). Medicinal and aromatic plants can support the economy
24 and generate livelihood options for rural people through preparing and selling traditional medicine; collecting
25 from wild; and trade for income generation (Fajinmi et al., 2017; Zahra et al., 2020). Income from medicinal
26 plant collection increases livelihood diversification, which is widely accepted to improve resilience.
27
28 5.7.2 Resin and Gum
29
30 Resin and gum are economically important natural products: contributing 14-23% total household income in
31 parts of Ethiopia and Sudan (Abtew et al., 2014; Fikir et al., 2016), Cambodia (Sakkhamduang et al.) and
32 India (Tewari et al., 2017). They are an important source of raw material for many industries. For instance, in
33 Africa, the genus Boswellia and Commiphora, which provide frankincense and myrrh resins, provide
34 significant income generation and export value (Tilahun et al., 2015). Populations of many species that
35 provide gums and resins are declining under pressure from unsustainable harvesting and deforestation and
36 climate change may further threaten them.
37
38 In Sri Lanka, Boswellia serrata Roxb. is critically endangered or possibly extinct (Weerakoon and
39 Wijesundara 2012). In India, B. serrata populations are `vulnerable' (Chaubey et al., 2015; Brendler et al.,
40 2018), and declining in the Western Ghats (Soumya et al., 2019). Invasion of Lantana camara and Prosopis
41 juliflora has resulted in poor regeneration of Commiphorawightii in central India (Jain and Nadgauda, 2013).
42 Other resin-producing species under threat include: Daemonoropsdraco (Dragon's blood resin) in Indonesia
43 (Yetty et al., 2013; Widianingsih et al., 2019), Pinus merkusii(tusam) in Sumatra (Indonesia) (Hartiningtias
44 et al., 2020), Pinus pinaster in Spain, Pinus massonianain China, (Génova et al., 2014; Chen et al., 2015b),
45 Pistacia atlantica in Iran (Yousefi et al., 2020).
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1
2 5.7.3 Wild Foods
3
4 Wild foods can include both native and introduced species that are not cultivated or reared but may be under
5 various degrees of management by humans and may include escapees of species that are cultivated in some
6 contexts (Powell et al., 2015). Information on the use and importance of wild foods for nutrition is growing
7 but remains limited (FAO, 2019e). The AR4 covered wild food briefly in the Polar Regions and noted the
8 interrelated nature of climate change and Indigenous knowledge loss in reducing access to wild food
9 (Anisimov et al., 2001). AR5 did not address wild foods and other natural products. There is large variation
10 in the importance of wild foods (Powell et al., 2015; Rowland et al., 2017; Dop et al., 2020). A recent survey
11 of 91 countries found that 15 reported regular use of wild foods by most of the population, and 26 reported
12 regular use of wild foods by a subsection of the population (FAO, 2019e). While they contribute little to food
13 energy intake, their contribution to nutrition can be significant because most wild and forest foods
14 (vegetables, fruits, mushrooms, insects, and meat) are rich in proteins and micronutrients (Powell et al.,
15 2015). The impacts of climate change on wild foods will vary in time, space, and among species.
16
17 5.7.4 Observed and Projected Impacts
18
19 5.7.4.1 Medicinal lants
20
21 Research is limited on the effects of climate change on the distribution, productivity, or availability of
22 medicinal plants (Applequist et al., 2020), but some are facing threats due to climate change (Phanxay et al.,
23 2015; Chirwa et al., 2017; Chitale et al., 2018). Climate change is projected to impact some medicinal plant
24 species through changing temperature and precipitation, changes in pests and pathogens: unsustainable harvest
25 of high value species will significantly exacerbate these impacts (medium evidence; high agreement)
26 (Applequist et al., 2020). Table 5.9 highlights that climate change impacts on medicinal plant species will vary
27 greatly by species. Medicinal plants that grow in arid environments are also highly susceptible to climate-
28 induced change (Applequist et al., 2020). Arctic medicinal species may also be particularly at risk due to
29 climate change (Cavaliere, 2009).
30
31 Changes in range distribution will interact with detailed local knowledge and Indigenous knowledge needed
32 to harvest and use medicinal plants. Northward range shifts, for example, may mean certain plants still exist,
33 but not where they have traditionally been important as medicine, and with protected areas, possibly moving
34 suitable ranges outside of areas where plants species have sufficient protection (Kaky and Gilbert, 2017).
35 Climate-induced phenological changes are already observed as a threat to some species (Gaira et al., 2014;
36 Maikhuri et al., 2018). Other major climate-induced impacts on medicinal plants will be via the phytochemical
37 content and pharmacological properties of medical plants (Gairola et al., 2010; Das et al., 2016a). Experimental
38 trials have shown that drought stresses increase phytochemical content, either by decreasing biomass or
39 increasing metabolites production (high confidence) (Selmar and Kleinwachter, 2013; Al-Gabbiesh et al.,
40 2015).
41
42
43 Table 5.9: Observed and Predicted impacts of climate change on selected medicinal plant species.
Region Species Observed and Projected Impacts of Climate Assessment of Evidence and
Change level of agreement
Egypt, Sub- General Habitat suitability and/or range distribution medium confidence.
Saharan Africa, assessment of will shift or may be lost (Munt et al., 2016;
Spain, Central medicinal plants Yan et al., 2017; Brunette et al., 2018;
Himalaya, Chitale et al., 2018; Zhao et al., 2018;
China, Nepal Applequist et al., 2020) including in high
elevation meadows which are home to some
of the most threatened plant populations and
contain a high number of and higher
proportion of species used as medicine
compared to lower elevation habitats (Salick
et al., 2009; Brandt et al., 2013).
Hindukush Gynostemmapenta The elevated CO2 and temperature can medium confidence
Himalaya phyllum increase biomass, but the health-promoting
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Arctic Golden Root properties such as total antioxidants, medium confidence
North America (Rhodiola rosea) phenols, and flavonoids are expected to medium confidence
Asia decrease (Chang et al., 2016). medium confidence
American ginseng Population decline has been associated with
Africa (Panax drying of stream beds and alpine meadows, medium confidence
Asia quinquefolius) which are predicted to become more severe medium confidence
Gentiana under climate change
Asia rigescens (Cavaliere, 2009; Brinkman et al., 2016) medium confidence
Himalayas Modelling of the combined impact of medium confidence
Iran Alstoniaboonei climate change (warming) and harvesting medium confidence
Central pressure indicates a non-linear increase in medium confidence
America Homonoia riparia extinction risk (Souther and McGraw, 2014) medium confidence
Africa A model evaluating future climate impacts medium confidence
Himalayas Notopterygiuminc shows a westward range shift and major loss medium confidence
Iran isum of highly suitable habitats. Modelling also
shows a potential decline in quality
Himalayan yew (chemical concentration of iridoid glycoside,
Taxus wallichiana which is highest in highly suitable habitats)
due to climate change (Shen et al., 2021)
Daphne Modelling indicates that the range for this
mucronata species remains relatively stable with a
possible modest expansion at the northern
Pericón or and southern margins of the range (Asase
Mexican Mint and Peterson, 2019).
Marigold Modelling of future climate scenarios in
Tagetes lucida Yanan province, China projects that habitat
Rooibos tea suitability improves (Yi et al., 2016).
Aspalathus Modelling of future climate scenarios across
linearis the whole species range in China shows that
both the suitable area and suitability of the
Lilium habitat increase (Yi et al., 2018).
polyphyllum Modelling for future climate change shows
areas of suitable habitat will significantly
Fritillaria decrease, however, the area of marginally
imperialis suitable habitat will remain relatively stable
(Zhao et al., 2020).
Modelling shows projected shrink in
climatic niche of the species by 28% (RCP
4.5) and 31% (RCP 8.5) highlights the
vulnerability to climate change impacts
(Rathore et al., 2019).
Modelling of future climate change projects
disappearance of the species below 2000 m,
significant change in distribution between
2000-3000m and no change above 3000 m
(Abolmaali et al., 2018).
Models predict range to contract somewhat
and shift northward (Kurpis et al., 2019)
Modelling of future climate scenarios shows
substantial range contraction of both wild
and cultivated tea with range shifts south-
eastwards and upslope (Lotter and Maitre,
2014)
Habitats of this species will shrink by 38
81% under future climate scenarios and shift
towards the south-east region in western
Himalaya, India (Dhyani et al., 2021).
Modeling shows 18% and 16.5% of the
habitats may be lost due to climate change
by 2070 under RCP4.5 and RCP8.5, Further,
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Himalayas/ Snow lotus it is observed that under the current climatic medium confidence
China (Saussurea spp.) conditions, the suitable habitat may become
unsuitable in the future resulting in local medium confidence
North Africa Atlas cedar extinction (Naghipour Borj et al., 2019) medium confidence
Cedrusatlantica Climate change is a significant threat to this medium confidence
Asia / South species (Law and Salick, 2005). Laboratory medium confidence
Korea Paeonia obovata and field trials show considerable plasticity medium confidence
Iran and a wide thermal range for germination, high confidence
Salvia hydrangea which may help compensate for range Low confidence.
Patagonian, reductions under climate change (Peng et al.,
Argentina Valerianacarnosa 2019)
Western Ghats, Modelling shows a significant and rapid
India Kokum contraction of distribution range, upward
Garcinia indica elevational range shift, increased
Himalaya fragmentation, and possible disappearance
Ophiocordyceps in many North African localities (Bouahmed
Pacific islands sinensis et al., 2019)
Modelling of climate change scenarios
noni shows significant loss of suitable habitat and
(Morindacitrifoli), possible disappearance of P. obovatainin
naupaka South Korea after 2080 (Jeon et al., 2020).
(Scaevola spp.), A projected loss of habitat in the south-east
kukui (Aleurites of the range will not be compensated by the
moluccana), and northward or upward elevational range
milo (Thespesia migration (Ardestani and Ghahfarrokhi,
populnea) 2021)
Modelling for future climate scenarios
projects a 22% loss of the suitable habitat
(Nagahama and Bonino, 2020)
Predictions of Climate change impact on
habitat suitability indicate drastic reduction
in the suitability by over 10% under RCP
8.5 for the year 2050 and 2070 (Pramanik et
al., 2018)
A decline of the species is largely due to
over harvesting but ecological modelling
indicates that climate warming is also
contributing to this decline (Hopping et al.,
2018)
May be less susceptible to climate change as
they are fast growing, have high reproduction
rates, grow at sea-level (and are often salt-
tolerant) and have significant room for range
shifts (Cavaliere, 2009).
1
2
3 5.7.4.2 Wild food
4
5 5.7.4.2.1 Wild Food in the Arctic, North America, and Europe
6 Changes to the availability, abundance, access, and storage of wild foods associated with changing climate
7 are exacerbating high rates of food insecurity (high confidence) (Ford, 2009; Beaumier and Ford, 2010;
8 Herman-Mercer et al., 2019). Wild foods are central to the food systems of communities throughout the
9 Arctic and sub-Arctic (Kuhnlein et al., 1996; Ballew et al., 2006; Kuhnlein and Receveur, 2007; Johnson et
10 al., 2009) and play an essential role in people's physical and emotional health (CCP 6.2.5; 2.8) (high
11 confidence) (Loring and Gerlach, 2009; Cunsolo Willox et al., 2012). Wild foods consumed in the Arctic and
12 Northern regions include animals and a wide variety of plant foods (Wein et al., 1996; Ballew et al., 2006;
13 Kuhnlein and Receveur, 2007). Wild foods contribute most of important nutrients in the diets of Northern
14 and Arctic people (Johnson et al., 2009; Wesche and Chan, 2010; Kenny et al., 2018). However, the use of
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1 traditional wild foods is declining across the region, lowering diet quality (Rosol et al., 2016). Indigenous
2 communities in the Arctic perceive climate change related impacts on traditional wild foods, and availability
3 and access to wild foods are forecast to continue to decline (Brinkman et al., 2016). Some communities hold
4 positive views of the new opportunities a warmer climate will bring, seeing them as a favourable trade-off
5 relative to the loss of some forms of subsistence hunting (Nuttall, 2009). Climate change is causing
6 ecological changes that impact Arctic wild food availability and abundance in many different ways,
7 including changes to breeding success, migration patterns, and food webs ( Table 5.10, Markon et al., 2018).
8
9 Climate-change induced impacts of access to wild foods are also of concern in Arctic regions (high
10 confidence). Coastal and inland communities of Alaska found that 60% of climate impacts on food security
11 listed by hunters were related to access (Brinkman et al., 2016). Reduced duration, thickness and quality of
12 sea ice are some of the most cited impacts of climate change on wild food consumption (Ford, 2009; Laidler
13 et al., 2009; Downing and Cuerrier, 2011; Huntington et al., 2017; Nuttall, 2017; Fawcett et al., 2018; Ford
14 et al., 2018; Markon et al., 2018). Lack of snowfall reduces and delays the ability to travel on the land using
15 snowmobiles (Downing and Cuerrier, 2011), impacting safety of travel, time needed and costs of accessing
16 wild foods (Cold et al., 2020).
17
18 Rising temperatures and humidity are also impacting wild food storage and increasing the risk of food-borne
19 diseases (Cozzetto et al., 2013; Nuttall, 2017; Markon et al., 2018). Changes in air temperature and humidity
20 can mean that whale and fish meat no longer dry properly, or meat may spoil before hunters can get it home
21 (Downing and Cuerrier, 2011; Nuttall, 2017). Traditional permafrost ice cellars are no longer reliable
22 (Downing and Cuerrier, 2011; Nyland et al., 2017; Herman-Mercer et al., 2019). Climate-related
23 environmental change compounded with social, economic, cultural, and political change have had complex
24 but overall negative impacts on wild foods ( CCP 6.4, Lujan et al., 2018) .
25
26 Communities across other (non-Arctic) parts of North America and Europe also report declining availability
27 of wild foods with climate change among the perceived drivers for decline (medium confidence) ( Table
28 5.10, Serrasolses et al., 2016; Smith et al., 2019a). Even when climate change may not always be the primary
29 driver of loss of these wild food resources, climate may interact with other stressors to exacerbate loss of
30 wild foods (Lynn et al., 2013; Reo and Parker, 2013).
31
32 5.7.4.2.2 Wild food in the arid and semi-arid environments
33 Wild foods are also impacted by climate change in arid and semi-arid landscapes around the world (medium
34 evidence, high agreement) (Table 5.10). A number of wild species are important traditional foods of
35 Indigenous Peoples or local communities across arid regions of North America (Messer, 1972; Kuhnlein and
36 Calloway, 1977; Santos-Fita et al., 2012; Vinyeta et al., 2016), South America (e.g. Argentina, Ladio and
37 Lozada, 2004; Altrichter, 2006; Eyssartier et al., 2011), Australia (Scelza et al., 2014), the Mediterranean
38 basin (Hadjichambis et al., 2008; Powell et al., 2014), India and the Himalayas (Pingle, 1975; Gupta and
39 Sen, 1980; Delang, 2006; Bhatt et al., 2017).
40
41 Wild foods such as baobab, shea and nere from plants and animal make an important contribution to diets
42 and nutrition in arid and semi-arid regions of African (Boedecker et al., 2014; Leßmeister et al., 2015;
43 Bélanger and Pilling, 2019) and are being impacted by climate change (Moseley et al., 2015; Sango and
44 Godwell, 2015; Hitchcock, 2016) (see Chapter 9). There has been little published research on the impacts on
45 climate change on wild food in arid regions of Australia, although Aboriginal elders in one report suggested
46 that climate related changes are impacting wild food (Memmott et al., 2013).
47
48 5.7.4.2.3 Wild Food in tropical humid environments
49 Wild foods are important to many communities that live in and adjacent to humid tropical forests, but
50 climate change impacts are mixed ( Table 5.10, Dounias et al., 2007; Colfer, 2008; Powell et al., 2015;
51 Rowland et al., 2017; Reyes-García et al., 2019).. In some humid tropical forest regions, bushmeat is
52 particularly important (Golden et al., 2011; Nasi et al., 2011; Fa et al., 2015; Powell et al., 2015; Rowland et
53 al., 2017). In humid tropical regions the impact of climate change on wild food availability, access and
54 consumption is currently unclear and research is limited. There are, however, important interrelationships
55 between climate change and wild food use in humid forests. For example, the loss of large mammals to
56 bushmeat consumption and global trade will likely slow the regeneration of tropical forests in which a large
57 number of tree species are dependent on large mammals for seed dispersal (Brodie and Gibbs, 2009).
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1 Conversely, others argue that bushmeat provides local communities with an important incentive to support
2 local maintenance of forest cover and thus carbon sequestration (Bennett et al., 2007).
3
4
5 Table 5.10: Observed and Predicted impacts of climate change on selected wild food species.
Region Species Observed and Projected Impacts of Climate Change Assessment of
Evidence and
level of
agreement
Arctic region Ringed Seals Drastic declines in population size and major changes in high confidence
(Pusahispida) population structure (Hammill, 2009; Reimer et al., 2019);
habitat (dependent on snow cover or ice breathing holes for
lairs) will decline by approximately 70%, and significantly
reduce survival rates of pups (Freitas et al., 2008).
Arctic region Bearded seal Climate change affect the availability and stability of at medium
(Erignathus least 11 ice-associated species including Bearded seal. evidence, high
barbatus) Potential impacts due to climate change will reduce agreement
available habitat for birthing (Moore and Huntington, 2008;
Fink, 2017).
Arctic region Walrus Declines in the climate-vulnerable Pacific walrus high confidence
(Odobenus populations, induced by overharvesting (Taylor et al., 2018);
rosmarus) however, the species is considered highly vulnerable to loss
of sea ice (Lydersen, 2018). Possible diet changes (related to
climate-induced changes in food-web) raise concernsabout
the health of the population (Clark et al., 2019).
Arctic region Narwhal The impacts of climate change on other sea ice-associated low evidence,
(Monodon marine mammals are somewhat less clear (Moor et al., medium
monoceros) 2017). Climate change may threaten narwhal given their agreement
vulnerability to ice entrapment (Laidre and Heide-Jorgensen,
2005) and the narrow range of prey in their diet (Heide-
Jørgensen, 2018). In Greenland hunters report that narwhal
now frequent fjords and other areas where manoeuvring a
boat is difficult (Nuttall, 2017)
Arctic region Beluga Belugas are thought to be less sensitive to climate change low evidence,
(Delphinapterus than some other sea mammals but can perish in large groups low agreement
leucas) from ice entrapment. Climate impacts likely increased
human activity (noise) (O'Corry-Crowe, 2009). Changes in
migrating timing have been documented (Hsiang et al.,
2017).
Arctic region Bowhead The movements of some whale species are linked to sea medium
(Balaena surface temperatures (Moore and Huntington, 2008; confidence
mysticetus) Chambault et al., 2018). Some whale hunting communities
are now reporting that whales pass by at a time of year when
launching boats is impaired by rough weather and poor sea
ice conditions (Noongwook et al., 2007; Huntington et al.,
2017).
Artic region Other sea ice The impacts of climate change on other sea ice associated low confidence
associated marine mammals are somewhat less clear (Moor et al.,
marine 2017).
mammals (harp
seal, hooded
seal)
Arctic and Reindeer and Large herbivores are highly dependent on their food sources medium
Northern caribou such as mosses, lichens and grasses which are sensitive to confidence
regions (Rangifer climate change (Istomin and Habeck, 2016).
tarandus)
Combined impacts of climate change and other interrelated
factors suggest significant declines in caribou and reindeer
populations, although to varying extents from one population
to another (Kenny et al., 2018; Mallory and Boyce, 2018).
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Warming has led to increased plant productivity and
associated increases in body mass of some reindeer
populations (Albon et al., 2017; Mallory and Boyce, 2018).
Increasing primary production, warming will also change the
plant composition, leading to increases in woody / shrubby
vegetation which will have negative nutritional
consequences for caribou and reindeer (Elmendorf et al.,
2012; Mallory and Boyce, 2018). The loss of lichens, a key
winter food source, due to increased wildfire or replacement
by grasses and herbs that die back in the winter, may also be
detrimental to caribou and reindeer, although there is not
currently consensus on this among experts (Mallory and
Boyce, 2018).
Rain on snow and icing events during winter, which are
predicted to become more frequent, have been documented
to lead to large increases in arctic herbivore mortality
because they create an ice barrier making access to food
more difficult (Putkonen and Roe, 2003; Tyler, 2010; Stien
et al., 2012; Hansen et al., 2013; Forbes et al., 2016). Rain
on snow events may also impact reproductive success,
although recent research suggests this relationship in not
straight forward (Douhard et al., 2016).
Increased summer insect harassment is also predicted to
increase and further stress large herbivores both by the
additional parasitic load and by decreasing the amount of
time spent grazing as animals seek to outrun pests (Mallory
and Boyce, 2018).
Arctic and Moose (Alces Finally, many caribou and reindeer populations rely on sea medium
Northern alces) and freshwater ice to facilitate their movement and confidence
regions migration: loss of ice may make some populations no longer
Geese (Branta viable (Mallory and Boyce, 2018). medium
North America canadensis, The distributional changes of Rangifer populations might be confidence
Answer spp., affected by the range expansions and the northward
Arctic and Branta spp.) expansion of moose (Mallory and Boyce, 2018). This is due high confidence
Northern Berries to increases in productivity on the tundra and more frequent
regions (Vaccinium wildfire activity resulted to improve habitat quality for
spp., Rubus spp. moose in the northward.
and others) Phenological mismatch develops between the berries and
migration timing may mean that Canadian geese no longer
stop near some communities (Downing and Cuerrier, 2011).
Berries are among the most important and widely consumed
wild foods of plant origins in Arctic and northern regions
(Vaara et al., 2013; Hupp et al., 2015; Boulanger-Lapointe et
al., 2019).
Berry production will be impacted by climate change,
including snow cover, rainfall, soil moisture, air temperature,
and availability of insect pollinators (Herman-Mercer et al.,
2020) and possible risk from sea-level-rise associated soil
salinization (Cozzetto et al., 2013).
Increased growth of woody shrub vegetation, driven by
increased temperatures, can also make moving across the
land move difficult, impairing access to berry patches
(Boulanger-Lapointe et al., 2019). Conversely, a recent
modelling experiment suggested that the>2°C warming
experienced by Arctic communities over the past three
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decades has had minimal impact on overall trail access (Ford
et al., 2019).
In Alaska, communities perceive berry abundance as
declining and/ or becoming more variable (Kellogg et al.,
2010; Hupp et al., 2015). In a Gwich'in community in
Canada, Parlee and Berkes (2005) recorded that local women
perceived climate change, especially extreme weather events
as the greatest risk to traditional berry patches (cranberry,
blueberry, and cloudberry).
The expansion of trees and shrubs may cause shading and
negatively impact the productivity of berry plants (Downing
and Cuerrier, 2011; Lévesque et al., 2012).
Berries are predicted to be increasingly susceptible to
negative impacts of invasive species (which compete for
pollinators) as climate change progresses (Spellman and
Swenson, 2012) and infections (Turner and Clifton, 2009).
Suitable area of Huckleberry (Vaccinium membranaceum)
would shrink by 540% by the end of the 21st century
(Prevéy et al., 2020).
Phenological shifts are also important. Many communities
report changes in phenology including failed ripening or "all
of the berries are ripening at the same time" (Turner and
Clifton, 2009; Herman-Mercer et al., 2020). Competition
with growing populations of geese is viewed by many
communities to be an important threat to berry harvesting.
(Boulanger-Lapointe et al., 2019). In Labrador, Canada
report that changes in permafrost, vegetation, water, and
weather have had an impact on cloudberry (bakeapple)
productivity, phenology, and patch fragmentation. Moreover,
changes in summer settlement patterns (which are now
farther from berry patches) are making it more difficult for
people to respond to variations in growth and timing
(Anderson et al., 2018).
North America Salmon In Montana, USA, Crow Nation elders have noted that many Medium
(Washington (Salmonidae) of their important berry resources have been impacted by confidence
State, USA) climate change, either because they bud earlier and are then
vulnerable to cold snaps, or the timing of fruit production
North America Acorns form has changed (with many now ripening at the same time)
(California) oak trees (Doyle et al., 2013). Similarly, the Wabanaki Nations in
(Querus) Maine and Eastern Canada worry that climate change will
impact berry resources already under pressure from
dwindling territory and pollution (Lynn et al., 2013).
Indigenous communities in Washington State, USA report
devastation of their salmon fishery due to loss of glacial run
off and associated warming river and stream temperatures;
potential damage to shellfish resources due to sea level rise
and ocean acidification (Lynn et al., 2013). The Karuk
people in California have also experienced losses in salmon
(Lynn et al., 2013; Vinyeta et al., 2016).
In the arid south-west of the USA, wild foods are less widely
consumed today, but their revitalization is important to
identity and well-being of many Indigenous people. The
Karuk people of the Klamath River in California have
experienced an almost complete loss of two key traditional
wild foods: salmon and acorns, foods which once made up
50 % of a traditional Karuk diet (Lynn et al., 2013; Vinyeta
et al., 2016), as well as huckleberry (Vinyeta et al., 2016).
Using regional climate models, Kueppers (2005) showed a
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North America Wild rice major reduction in the range of two species of oak in high confidence
North America (Zizania spp.) California that are used in traditional diets. Increasing
North America frequency of severe fires in the western United States medium
North America Camas tuber threaten a number of traditional wild food resources, confidence
North America (Camassiaquam especially acorns (Vinyeta et al., 2016).
ash) Significant reductions in wild rice area in Great lakes medium
Africa havebeen associated with mining, dams, and other activities confidence
Wapato tuber but climate change may lead to further reductions (Cozzetto
(Sagittaria et al., 2013; Lynn et al., 2013) medium
latifolia) Historic changes in fire regimes, linked to changes in confidence
climate, are believed to have altered availability of the low confidence
Springbeauty important Camas tuber (Camassiaquamash) (Lepofsky et al.,
(Claytonia 2005). low confidence
lanceolate) The aquatic Sagittaria latifolia (the roots of which are
Seaweed consumed by Indigenous groups across North America) is
(Porphyraabbot vulnerable to both water salinity and temperature (Delesalle
tiae; among and Blum, 1994)
others) Claytonia lanceolata is particularly vulnerable to changes in
snow melt and other climatic changes due to advancement in
Baobab the flowering (Renner and Zohner, 2018).
(Adansonia In British Columbia, Canada, Gitga'at elders note that the
digitata) ripening of an important edible seaweed
(Porphyraabbottiae) rarely coincides with weather and
needed to process in the traditional way (drying on rocks and
then ripening and re-drying) (Turner and Clifton, 2009).
Baobab is thought to be vulnerable to climate change
because it is long-lived, can take up to 23 years to start
fruiting and leaf harvesting is often so intensive that it
depresses fruit production. Modeling study using different
records model shows the percentage of present distribution
predicted to be suitable in the future ranged varied from 5%
to 91% (Sanchez et al., 2011).
Africa Shea (Vitellaria Shea (Vitellaria paradoxa), was expanded through human Limited
paradoxa) intervention and is linked to human migration; fruit traits evidence,
North Africa such as fruit size and shape, pulp sweetness, and kernel fat medium
(Morocco) Argan (Argania content are determined both by temperature and rainfall, as agreement
Asia (Nepal) spinosa) well as human selection for preferred traits (Maranz and
Fruit species Wiesman, 2003). There is limited and conflicting evidence medium
Worldwide, and vegetables of the impacts of climatic conditions and future projected confidence
most important (e.g., Asparagus climate variations on V. paradoxa (Tom-Dery et al., 2018). Limited
in Europe and racemosus, Mixed evidence of the impact of climate and rainfall on fruit evidence,
Asia Urticadioica). production and timing is reported (Tom-Dery et al., 2018). medium
Mushrooms Fruit production was negatively correlated with mean annual agreement
temperature and positively correlated with annual rainfall high confidence
(Bondé et al., 2019).
Climate change projections suggest a 32% decrease in
habitat suitable for Argania spinosa under some scenarios
(Alba-Sánchez et al., 2015; Moukrim et al., 2019).
In Nepal, Thapa (2015) report phenological changes in semi-
domesticated fruit species, as well as decreased availability
of a number of wild plants that can be consumed as
vegetables.
Wild mushrooms production (including truffles) is closely
linked to climate factors including temperature and
precipitation as well tree growth and carbohydrate
production (Tahvanainen et al., 2016). Some species are
sensitive to high temperatures (Büntgen et al., 2012; Le
Tacon et al., 2014; Ágreda et al., 2015; Bradai et al., 2015;
Taye et al., 2016; Alday et al., 2017; Karavani et al., 2018;
Büntgen et al., 2019; Thomas and Buntgen, 2019). Models
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for some varieties suggest "declines of 78100% in
European truffle production are likely for 20712100"
(Thomas and Buntgen, 2019). For some species in norther
Europe, the season is expanding (starting earlier and/or
ending later), likely linked to warming (Büntgen et al., 2012;
Le Tacon et al., 2014; Ágreda et al., 2015; Bradai et al.,
2015; Taye et al., 2016; Alday et al., 2017; Karavani et al.,
2018; Büntgen et al., 2019; Thomas and Buntgen, 2019).
North America Acorns, nuts Matsutake mushroom (Tricholoma matsutake), highly prized high confidence
(California) and berries and in China, is sensitive to timing and amount of precipitation
other fire- and temperature (Yang et al., 2012), and suitable habitat for
dependant wild this species is predicted to significantly decrease and highly
foods suitable habitat would nearly disappear under various
climate change scenarios (Guo et al., 2017).
Low intensity traditional burning practices increased pyro-
diversity (Vinyeta et al., 2016). Climate change will
exacerbate the risks posed by exotic pathogens that attack
oak species and further reduce access to acorns, as well as
other foods founds in oak ecosystems (Voggesser et al.,
2013).
South America Aguaje, Local communities perceived a lower yield of aguaje Limited
(Amazon (Mauritia Hofmeijer et al. (2013) due to drought. Another study from evidence,
region) felxuosa), the Colombian Amazon wild food use was reported to be medium
Brazilian nut vulnerable to extreme climate events which impact species agreement
Small Islands (Bertholletiaexc migration patterns or restrict access to fishing and hunting Limited
(Papua New elsa) fishing rounds (Torres-Vitolas et al., 2019). In some humid regions evidence,
Guinea) and hunting in the range of some wild food species may be extended by medium
Australasia general climate change, such as the Brazilian nut agreement
(Australia) (Bertholletiaexcelsa) (Thomas et al., 2014).
Sweet potato Increases in the El Niño Southern Oscillation was associated Limited
Asia (Indonesia) with drought which increased sweet potato losses (Jacka, evidence,
General wild 2016) in highlands humid forest. medium
foods agreement
Aboriginal communities in North Queensland, a humid
Sago tropical region of northern Australia reported some climate
(Metroxylon impacts on wild foods, however primarily for marine
sagu) resources and those found in dry forest ecosystems
(McIntyre-Tamwoy et al., 2013).
People in a sago-dependent community in Papua Indonesia
viewed climate variation as less important than other factors
(logging, mining, infrastructure), but still expressed concerns
about salinity of water supplies, floods, and reduced hunting
success (Boissière et al., 2013).
1
2
3 5.8 Ocean-based and Inland Fisheries Systems
4
5 The livelihoods of 10 to 12 percent of the world's population depend on fisheries and aquaculture (FAO,
6 2020c). Globally, fish provide more than 3.3 billion people with 20 % of their average per capita intake of
7 animal proteins, reaching 50 % or more in countries such as Bangladesh, Cambodia, The Gambia, Ghana,
8 Indonesia, Sierra Leone, Sri Lanka, and several Small Island Developing States (FAO, 2020c). Between
9 1961 and 2017, the average annual apparent global food fish consumption increased (3.1% per year; from 9.0
10 kg per person in 1961 to 20.5 kg in 2018), exceeding the rate of increase in consumption of meat from all
11 terrestrial animals combined (2.1% annually, currently around 40 kg per person) (FAO, 2020d). Fish are a
12 rich source of protein and specific vitamins and minerals (Khalili Tilami and Sampels, 2018), and are an
13 essential food source in regions in need of nutritious, affordable food (Thilsted et al., 2016; FAO et al., 2018;
14 Hicks et al., 2019; Cross-Chapter Box MOVING PLATE this Chapter).
15
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1 Overall capture fishery production has remained relatively static since the 1990s, reaching 96.4 million tons
2 in 2018, with over 87% of the production coming from marine environments and the rest from inland
3 fisheries (FAO, 2020c). Finfish represent 85% of global marine seafood production, with small pelagic fishes
4 (anchovies, sardines, and herrings) as the major contributor. Almost 60% of the total global marine catches
5 come from China, Peru, Indonesia, the Russian Federation, the United States of America, India, Viet Nam,
6 Japan, Norway, and Chile (FAO, 2020c). Inland fisheries are found on every continent other than Antarctica
7 and provide 158 million people the equivalent of all dietary animal protein (McIntyre et al., 2016). Inland
8 production accounted for 12 million tons in 2018, with nearly 70% of capture from low-income Asian and
9 African countries (Harrod et al., 2018a).
10
11 The aquaculture and fisheries' share of GDP varies mostly from 0.01 to 10 percent (Cai et al., 2019), but the
12 relative importance in countries' economies and welfare is greater in several low-income countries,
13 especially in many African and Pacific Island states. Approximately 60 million people are directly employed
14 along in fisheries value chains, from harvesting to distribution (Vannuccini et al., 2018), around 95% of
15 those are in small-scale fisheries of low and middle-income countries, and almost half of them are women.
16
17 5.8.1 Observed Impacts
18
19 Ocean systems are already facing significant impacts of climate change. At the ocean surface, temperature
20 has on average increased by 0.88 [0.681.01] °C from 18501900 to 20112020 (Fox-Kemper et al., 2021;
21 Gulev et al., 2021). Marine heatwaves have increased in frequency over the 20th century, with an
22 approximate doubling since the 1980s (high confidence), and their intensity and duration have also increased
23 (medium confidence) (IPCC, 2021, Box 9.2). In the Northeast Pacific, for example, an intense and long-
24 lasting marine heatwave during 2013 to 2015 bridged to the strong 2015-2016 El Niño (Tseng et al., 2017)
25 resulted in over five years of warmer-than-normal temperatures affecting the migration, distribution and
26 abundance of several marine species, including fisheries resources (Cornwall, 2019; Jiménez-Quiroz et al.,
27 2019). The surface open ocean pH has declined globally over the last 40 years by 0.0030.026 pH per decade
28 (virtually certain), and a decline in the ocean interior pH has been observed in all ocean basins over the past
29 23 decades (high confidence) (Gulev et al., 2021). The ocean is losing dissolved oxygen (very likely) in the
30 range of 0.53.3% between 1970 and 2010 for the 01000 m depth stratum (Bindoff et al., 2019; Canadell et
31 al., 2021), salt content is being redistributed (very likely) (Liu et al., 2019a; Gulev et al., 2021), and vertical
32 stratification is increasing (virtually certain) (HLPE, 2017a; Fox-Kemper et al., 2021; Ranasinghe et al.,
33 2021). There is high confidence that all these new physical, chemical, and biological conditions affect marine
34 organisms' physiology, distribution, and ecology, with an overall shift in biomass and species composition
35 affecting ecosystem structure and function (Chapter 3). Under climate change, freshwater ecosystems are
36 highly exposed to eutrophication, species invasion, and rising temperatures (Lynch et al., 2016; Hassan et al.,
37 2020). Major threats to wetland fisheries include water stress, sedimentation, weed proliferation, sea-level
38 rise, and loss of wetland connectivity (Naskar et al., 2018).
39
40 Changes in aquatic ecosystems directly affect humans by altering livelihood, cultural identity and sense of
41 self, and seafood provision, quality, and safety. The state of marine fishery resources has continued to
42 decline, with the proportion of fish stocks at biologically unsustainable levels of exploitation increasing from
43 10 percent in 1974 to 34.2 percent in 2017 (FAO, 2020d). There is medium confidence that fisheries
44 production declines in different world regions can be partly attributed to climate change, along with
45 overfishing and other socio-economic factors. It has been estimated that, from 1930 to 2010, the amount of
46 fish that can be sustainably harvested from several marine fish populations has decreased by 4.1% globally
47 due to ocean warming, with some regions (East Asian Marginal Seas, the North Sea, the Iberian Coast, and
48 the Celtic-Biscay Shelf), experiencing losses of 15-35% (Free et al., 2019). There is regional variation such
49 as redistribution of fishing grounds, due to climate-induced fish species migrations (Cross-Chapter Box
50 MOVING PLATE this Chapter). In Tanzania, for example, most small-scale fishers (75 %) have reported
51 shifting fishing grounds from nearshore to offshore areas during the last decade, due to perceived combined
52 effects of overfishing and environmental impacts (Silas et al., 2020). Observed impacts in some inland
53 aquatic systems indicate substantial productivity reductions (medium confidence). For example, sustained
54 warming in Lake Tanganyika during the last 150 years has affected the biological productivity by
55 strengthening and shallowing stratification of the water column (Cohen et al., 2016). Still, over 60% of the
56 published reports on directly observed impacts of climate change on freshwater biota are on salmonids in
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1 North America and Europe, highlighting significant literature gaps for other fish species and regions (Myers
2 et al., 2017a).
3
4 There is low confidence in climate change affecting the nutritious value of seafood. Contrasting evidence
5 suggests that ocean warming and acidification could be altering the nutritional quality of commercial
6 mollusks, primarily by reducing healthy fatty acids content (Tate et al., 2017; Ab Lah et al., 2018; Lemasson
7 et al., 2019); but Coleman (2019) found no significant changes in a widely distributed coastal fish species.
8
9 In terms of food safety, there is high confidence that climate change increases the trends in seafood
10 consumption related illnesses due to biological agents such as algae-produced toxins, Ciguatera, and Vibrio
11 (Cross-Chapter Box ILLNESS in Chapter 2, Sections 5.11 and 5.12). Increased surface water warming
12 changes the occurrence, intensity, species composition, and toxicity of marine and freshwater algae and
13 bacteria, and expansion to areas where they had not been reported before (Botana, 2016; McCabe et al.,
14 2016; Griffith et al., 2019). There is limited evidence suggesting that risks linked to the bioaccumulation of
15 chemicals are also of concern, such as neurotoxic methilmercury (MeHg) and heavy metals, due to water
16 quality and trophic changes induced by climate change (Shi et al., 2016; Schartup et al., 2019).
17
18 5.8.2 Assessing Vulnerabilities
19
20 In the absence of adaptive measures, climate-induced changes in the abundances and distributions of fish
21 will impact the provision, nutrition, livelihood security of many people (high confidence) as well as regional
22 and global trade patterns (medium confidence).
23
24 5.8.2.1 Food security: provision and nutrition
25
26 The importance of seafood in food security and nutrition is increasing, largely due to its contribution as high-
27 quality food (high confidence) (Hicks et al., 2019), as seafood contains unique long-chain polyunsaturated
28 fatty acids (LC-PUFAs) and highly bioavailable essential micronutrients--vitamins (A, B and D) and
29 minerals (calcium, phosphorus, iodine, zinc, iron, and selenium). These compounds, often not readily
30 available elsewhere in diets, have beneficial effects for adult health and child cognitive development (HLPE,
31 2014). Changes in marine and freshwater fish production can have significant consequences for human
32 nutrition (Colombo et al., 2020). These changes are of particular concern in regions with few nutrition
33 alternatives, such as low-income countries in Africa, Asia, Australasia, and Central and South America (high
34 confidence) (Ding et al., 2017; Kibria et al., 2017).
35
36 Freshwater ecosystems that support most inland fisheries are under continuing threat from changes in land
37 use, water availability and pollution and other pressures that will be exacerbated by climate change (high
38 confidence) (Section 4.3.5). Declines in dissolved oxygen in freshwater are 2.75 to 9.3 times greater than
39 observed in the world's oceans (Jane et al., 2021). These systems have a relatively low buffering capacity
40 and are therefore more sensitive to climate-related shocks and variability (Harrod et al., 2018b). Freshwater
41 faunae are projected to be highly vulnerable; in the tropics because organisms are closer to approaching their
42 thermal physiological limits and in the northern hemisphere (30-50°N) because the rate of temperature
43 change is faster (Comte and Olden, 2017). The worldwide spatial confluence of productive freshwater
44 fisheries and low food security highlights the critical role of rivers and lakes in providing locally sourced,
45 low-cost, nutritious food sources (McIntyre et al., 2016).
46
47 Deltas and other wetland fisheries are extremely vulnerable to climate change and home to a large and
48 growing proportion of the world's population. In India, Ghana, and Bangladesh, where three of the most
49 populated Deltaic systems are located, subsistence fisheries provide 12 to 60% of the animal protein in
50 people´s diets (Lauria et al., 2018).
51
52 The concern over aquatic food products' safety due to climate change is increasing (high confidence). A
53 strong positive relationship exists between specific bacterial growth rates and temperature, including
54 pathogenic species of the genus Vibrio, Listeria, Clostridium, Aeromonas, Salmonella, Escherichia, and
55 others, whose distributional area is expanding with changing climate conditions (Cross-Chapter Box
56 ILLNESS in Chapter 2, Section 5.12.1).
57
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1
2 5.8.2.2 Social vulnerabilities, including gender and marginalized groups and cultural services
3
4 There is high confidence that climate change is and will continue to be a threat to the livelihood of millions
5 of fishers, with the most vulnerable being those with fewer opportunities and less income (Barange and
6 Cochrane, 2018); Section 3.4.3. The social vulnerability can differ largely between locations, even between
7 relatively close coastal or inland communities (Bennett et al., 2014; Maina et al., 2016; Ndhlovu et al., 2017;
8 Martins et al., 2019) and among inhabitants within a location, depending on factors such as access to other
9 economic activities, education, health, adults in the household, and political connections (high confidence)
10 (Senapati and Gupta, 2017; Abu Samah et al., 2019; Lowe et al., 2019).
11
12 Indigenous coastal communities consume 1.5 million to 2.8 million metric tonnes of fish per year (about 2%
13 of global yearly commercial marine catch), and reach a per capita consumption estimated to be 15 times
14 greater than that of non-Indigenous country populations (Cisneros-Montemayor et al., 2016). There is high
15 confidence that some Indigenous fishing communities are particularly vulnerable to climate change through a
16 reduced capacity to conduct traditional harvests because of limited access to, or availability of, fish resources
17 (Weatherdon et al., 2016), with consequences that include dietary shifts with significant nutritional and
18 health implications (Marushka et al., 2019), displacement and loss of cultural identity (Sullivan and
19 Rosenberg, 2018) and loss of social, economic, and cultural rights (Finkbeiner et al., 2018). Areas of high
20 risk for Indigenous Peoples include the Arctic, coastal communities with a high dependency on marine and
21 freshwater fisheries, and small island states and territories (Finkbeiner et al., 2018; Hanich et al., 2018,
22 CCP6.2.5.1).
23
24 Women play a crucial role along the entire fisheries value chain, providing labour force in industrialized and
25 small-scale fisheries all around the world (FAO, 2020d). For small-scale fisheries alone, women represent
26 about 11% of the labour force, and their activity is generally in subsistence fisheries, highlighting their role
27 in household food security (Harper et al., 2020). In general, gendered division of labour tend to cause lower
28 salaries for women and different perception and experience of risk to climate change impacts (high
29 confidence) (Lokuge and Hilhorst, 2017).
30
31 5.8.2.3 Management, economic and geopolitical vulnerabilities
32
33 Local, national, regional, and international fisheries are mostly underprepared for geographic shifts in marine
34 animals driven by climate change over the coming decades (high confidence) (Pinsky et al., 2018; Oremus et
35 al., 2020; Pinsky et al., 2020). With fisheries distribution changes, sometimes into areas dedicated to
36 different historical uses or new ventures, the current management regimes will face constraining legal
37 frameworks (Farady and Bigford, 2019; Pinsky et al., 2020), which will demand interventions in the form of
38 policies, programs, and actions, at multiple scales.(Cross-Chapter Box MOVING PLATE this Chapter).
39 Coordinated fisheries management can substantially expand capacity to respond to a changing climate
40 (Pinsky et al., 2020), but a great deal of political will, capacity building, and collective action will be
41 necessary (high confidence) (Teslic et al., 2017; Burden and Fujita, 2019; Section 5.8.4).
42
43 Today, approximately half the world's population (~4 billion out of 7.8 billion people) are assessed as being
44 currently subject to severe water scarcity for at least one month per year (medium confidence) (Box 4.1), and
45 freshwater inland fisheries are particularly vulnerable as they are given lower priority for water resources
46 than other sectors (high confidence). In some cases, this situation results in the total loss of freshwater
47 fisheries. Examples include diversion of water for agriculture, shifts from food provision to recreational
48 fisheries, conserving biodiversity, and the requirement for high-quality water for drinking water supply (
49 Section 5.13, Harrod et al., 2018a).
50
51 There is high confidence that climate change increases the risk of conflicts due to the redistribution of stocks
52 and their abundance fluctuations, with subsequent impacts on resource sharing (Spijkers and Boonstra, 2017;
53 Pinsky et al., 2018; Spijkers et al., 2018; Mendenhall et al., 2020; Pinsky et al., 2020). High vulnerability and
54 lack of adaptive capacity to climate change impacts (including fisheries-dependent livelihoods, attachment to
55 place, and pre-existing tensions) increase the risk of conflicts, including among fishery area users and
56 authorities (Ndhlovu et al., 2017; Shaffril et al., 2017; Spijkers and Boonstra, 2017; Mendenhall et al., 2020).
57 Similarly, shifts in the distribution of transboundary fish stocks under climate change alter the current
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1 sharing of resources between countries and create conflicts as well as new opportunities (Cross-Chapter Box
2 MOVING PLATE this Chapter, Spijkers and Boonstra, 2017; Pinsky et al., 2018).
3
4 5.8.3 Projected Impacts
5
6 There is medium confidence that climate change will reduce global fisheries' productivity (Section 3.4.4.2.3),
7 with more significant reductions in tropical and sub-tropical regions and gains in the poleward areas (Bindoff
8 et al., 2019; Oremus et al., 2020). Through an ensemble of marine ecosystem models and earth system
9 models, mean global animal biomass in the ocean has been estimated to decrease by 5% under the
10 Representative Concentration Pathway (RCP)2.6 emissions scenario and 17% under RCP8.5 by 2100, with
11 an average decline of 5% for every 1°C of warming (Lotze et al., 2019), affecting food provision, revenue
12 distribution, and potentially hindering the rebuilding of depleted fish stocks (Britten et al., 2017). The
13 projected declining rates result in a 5.3-7% estimated global decrease in marine fish catch potential by 2050
14 (Cheung et al., 2019), particularly accentuated in tropical marine ecosystems and affecting many low-income
15 countries (Barange and Cochrane, 2018; Bindoff et al., 2019; Cross-Chapter Box MOVING PLATE this
16 Chapter). Projections indicate that by 2060 the number of exclusive economic zones (EEZ) with new
17 transboundary stocks will increase to 46 under strong mitigation RCP2.6, and up to 60 EEZs under the
18 RCP8.5 greenhouse gas emissions scenario (Pinsky et al., 2018). Similarly, by combining six intercompared
19 marine ecosystem models, (Bryndum-Buchholz et al., 2019) projected that under the RCP8.5 scenario a total
20 marine animal biomass decline of 15%30% would occur in the North and South Atlantic and Pacific, and
21 the Indian Ocean by 2100. In contrast, polar ocean basins would experience a 20%80% increase. In the
22 eastern Bering Sea, simulations based on RCP8.5 predict declines of pollock (>70%) and cod (>35%) stocks
23 by the end of the century (Holsman et al., 2020). Temperate tunas (albacore, Atlantic bluefin, and southern
24 bluefin) and the tropical bigeye tuna are expected to decline in the tropics and shift poleward by the end of
25 the century under RCP8.5, while skipjack and yellowfin tunas are projected to increase abundance in tropical
26 areas of the eastern Pacific but decrease in the equatorial western Pacific (medium confidence) (Erauskin-
27 Extramiana et al., 2019). In the western and central Pacific, redistribution of tropical tuna due to climate
28 change is projected to affect license revenues from purse seine fishing and shift more fishing into high seas
29 areas (Bell et al., 2018a; Table 15.5). For the east Atlantic, observational evidence indicates that not only
30 will tuna distribution change with temperature anomalies, but also fishing effort distribution (Rubio et al.,
31 2020a). There is medium confidence that climate change will create new fishing opportunities when
32 exploited fish stocks shift their distribution into new fishing regions in enclosed seas, such as the
33 Mediterranean and the Black Sea (Hidalgo et al., 2018; Pinsky et al., 2018). However, in general, where land
34 barriers constrain the latitudinal shifts, the expected impacts of climate change are population declines and
35 reduced productivity (high confidence) (Oxenford and Monnereau, 2018). Besides direct impacts on the
36 abundance of fisheries-targeted species, climate-change-induced proliferation of invasive species could also
37 affect fishery's productivity (low confidence) (Mellin et al., 2016; Goldsmith et al., 2019).
38
39 Shifting marine fisheries will affect national economies (high confidence) (Bindoff et al., 2019). It has been
40 suggested that without government subsides, fishing is already non-profitable in 54% of the international
41 waters (Sala et al., 2018). Projections are that Fishing Maximum revenue potential from landed catches will
42 decrease further by 10.4% (±4.2%) by 2050 relative to 2000 under RCP8.5, close to 35% greater than the
43 decrease projected for the global maximum catch potential (7.7% ±4.4%); (Lam et al., 2016). The global
44 revenue potential loss for that period ranges from USD 6-15 billion (depending on the model), but impacts
45 may be amplified at the regional scale for fisheries-dependent and low-income countries. The maximum
46 revenue potential percentage decrease in the EEZ under RCP8.5 is estimated to be over 2.3 times larger than
47 that of the high seas (Lam et al., 2016). Ocean acidification is also expected to drive large global economic
48 impacts (medium confidence) (Cooley et al., 2015; Fernandes et al., 2017; Macko et al., 2017; Hansel et al.,
49 2020), and there is high confidence that the integrated economic consequences of all interacting climate
50 change-related factors would result in even larger losses. Changes in the frequency and intensity of extreme
51 events will also alter marine ecosystems and productivity. Marine heatwaves can lead to severe and
52 persistent impacts, from mass mortality of benthic communities to decline in fisheries catch (IPCC, 2021,
53 Box 9.2). These events have very likely doubled in frequency between 1982 and 2016 and have also become
54 more intense and longer (Smale et al., 2019; Laufkotter et al., 2020); for all future scenarios Earth System
55 Models project even more frequent, intense, and longer-lasting marine heatwaves (Eyring et al., 2021; IPCC,
56 2021, Box9.2).
57
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1 In addition to temperature and water availability stress, climate change will bring new water quality
2 challenges in freshwater systems, including increased dissolved organic carbon and toxic metal loads (high
3 confidence) (Chen et al., 2016). Harrod et al. (2018a) found that the two major inland fishery producers
4 (China and India) will face significant stress in the future, a large group of countries that produce around 60
5 percent of total yield is projected to face medium stress, and a small group of 17 countries has the least
6 severe repercussions (medium confidence). Climate warming may enhance northward colonization of water
7 bodies of commercial freshwater species in the Arctic, where there are few ecological competitors (medium
8 confidence) (Campana et al., 2020), but at the same time may also accentuate the age-truncation effect of
9 harvesting, elevating the population's vulnerability to environmental perturbations (Smalås et al., 2019).
10 Detailed information on many of the most important inland fisheries is limited.
11
12 In terms of food safety, major concerns linked to climate change include the continued trend of increasing
13 Harmful Algal Blooms (HABs), and the quantity of pollutants reaching aquatic systems (Box 3.3; section
14 5.11).
15
16 5.8.4 Adaptation
17
18 Adaptation options in land and aquatic-based culturing food production systems include both governance
19 actions and changes in the factors of production (Section 5.4.4, 5.5.4, Reverter et al., 2020). In contrast,
20 adaptation options in fisheries are primarily concentrated in the socio-economic dimension, especially
21 governance and management (Brander et al., 2018; Holsman et al., 2019), and given the scale of the
22 problem, there are relatively few intentional, well-documented examples of implemented tactical responses
23 (Bell et al., 2020).
24
25 The proportion of fisheries operating at levels that are considered biologically unsustainable by the FAO has
26 increased from 10% in 1974 to 34.2% in 2017 (FAO, 2020d). There is high confidence that reducing stresses
27 on marine ecosystems reduces vulnerability to climate change and augments resilience (Barange, 2019;
28 Woodworth-Jefcoats et al., 2019; Ogier et al., 2020). Specifically, overfishing is the most critical non-
29 climatic driver affecting the sustainability of fisheries, and therefore improving management could help
30 rebuild fish stocks, reduce ecosystem impacts, and increase the adaptive capacity of fishing (high
31 confidence); (Barange, 2019; Das et al., 2020). Pursuing sustainable fisheries practices under a low
32 emissions scenario would decrease risk by 63%; in contrast, under the most extreme RCP 8.5, both profit and
33 harvest decline relative to today even under the most optimistic assumptions about global fisheries
34 management reforms (Gaines et al., 2018; Sumaila et al., 2019; Free et al., 2020).
35
36 One adaptation strategy in the fishing sector is developing the capacity to recognize and respond to new
37 opportunities that might arise from climate change by establishing a policy and planning setting that
38 augments the fishers' flexibility to change target species of fisheries or even engage in different productive
39 activities. A key element would be the design and implementation of management schemes that consider
40 flexible permits, sharing quotas, rethinking boundaries, and reference points in response to system changes
41 (Brander et al., 2018; Cross-Chapter Box MOVING PLATE this Chapter). Large-scale distribution and
42 productivity changes of commercial fish species will demand the ability to implement cooperative fishing
43 strategies (Cisneros-Montemayor et al., 2020; Østhagen et al., 2020), and adjust multi-lateral treaties and
44 other legal instruments used for managing shared transboundary ecosystems (Butler et al., 2019; Cross-
45 Chapter Box MOVING PLATE this Chapter).
46
47 There is high confidence that making climate change and adaptive capacity a mainstream consideration in
48 global, regional, environmental, and fisheries governance structures can improve the response capacity to
49 ocean change (Gaines et al., 2018; Bindoff et al., 2019; Holsman et al., 2020; Ojea et al., 2020). For
50 example, spatial management that includes strategies such as Territorial Use Rights for Fishing (TURFs),
51 Locally Managed Marine Areas (LMMAs) and customary tenure is an approach that has climate change
52 adaptation potential in small-scale fisheries but will require adjustments in governing and managing
53 institutions that allow them to be more dynamic and flexible (Le Cornu et al., 2018). In regions where some
54 of these measures have already been tested, institutional, legal, financial, and logistical barriers to successful
55 adaptation have been encountered, such as market failures stemming from uncertainty around new or
56 emerging species, or policy barriers derived from the fact that the creation of scientific information needed to
57 change regulations is likely slower than the pace of changes in stocks (Peck and Pinnegar, 2018).
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1
2 Adaptation capacity is limited by the financial capacity of some countries (Bindoff et al., 2019). For
3 example, in West African fisheries, adaptation costs associated with replacing the loss of coastal ecosystems
4 and productivity is estimated to require 510% of countries' Gross Domestic Product (Zougmoré et al.,
5 2016). For Pacific Islands and Coastal Territories, fisheries adaptation will require significant investment
6 from local governments and the private sector (Rosegrant et al., 2016), and reducing dependence on or
7 finding alternatives to vulnerable marine resources (Johnson et al., 2020; Mabe and Asase, 2020).
8
9 Adaptive capacity is strongly associated with social capital (i.e., the networks, shared norms, values, and
10 understandings that facilitate co-operation within or among groups) (high confidence) (Stoeckl et al., 2017;
11 D'agata et al., 2020) and depends on to what extent are stakeholders aware of climate change and their
12 perception of risk (Ankrah, 2018; Martins and Gasalla, 2018; Chen, 2020). Improving information flows
13 allows for a more efficient co-management implementation (medium confidence) (Vasconcelos et al., 2020).
14 Utilization of local and Indigenous knowledge has the potential to facilitate adaptation (Bindoff et al., 2019),
15 not only because it represents actual experiences and autonomous adaptations, but also because it facilitates
16 reaching shared understanding among stakeholders and adoption of solutions. Challenges to hybridizing
17 local ecological knowledge and scientific knowledge include differences in stakeholder or governance
18 perceptions about the validity of each knowledge set and issues of expertise and trust (Harrison et al., 2018).
19 Engaging Indigenous Peoples and local communities as partners across climate research ensures this
20 knowledge is utilized, enhancing the usefulness of assessments (Bindoff et al., 2019) and facilitating the co-
21 construction and implementation of sustainable solutions (medium confidence); (Braga et al., 2020;
22 Bulengela et al., 2020). Building climate resilience in the fishing sector also involves recognizing gender and
23 other social inequities (Call and Sellers, 2019), and ensure that all stakeholders are equally involved in the
24 adaptation plans, including their design and the capacity-building training programs.
25
26 There is high confidence that for the freshwater fisheries systems, the most immediate adaptation option is
27 the effective linkage of fisheries management to the adaptation plans of other sectors, especially water
28 management (hydropower, irrigation, and the commitment to maintaining environmental flows) (Harrod et
29 al., 2018a; Kao et al., 2020). In some regions, organizations are already addressing this issue, for example
30 The Office of Water (OW) in the USA is aimed at ensuring that drinking water is safe while ecosystem is
31 conserved to provide healthy habitat for fish, plants and wildlife; however, success strongly depends on the
32 possibility of integrating the jurisdictional framework of different agencies (Poesch et al., 2016), the
33 implementation of effective monitoring programs (Paukert et al., 2016), and finding ways to incentivize the
34 early restoration of degraded systems (Ranjan, 2020).
35
36
37 [START CROSS-CHAPTER BOX MOVING PLATE HERE]
38
39 Cross-Chapter Box: MOVING PLATE: Sourcing food when species distributions change
40
41 Authors: H. Gurney-Smith (Canada/United Kingdom), W. Cheung (Canada), S. Lluch Cota (Mexico), E.
42 Ojea (Spain),C. Parmesan (France/United Kingdom/USA), J. Pinnegar (United Kingdom) P. Thornton
43 (Kenya/United Kingdom), M-F. Racault (United Kingdom/France), G. Pecl (Australia), E.A. Nyboer
44 (Canada), K. Holsman (USA), K. Miller (USA), J. Birkmann (Germany), G. Nelson (USA) and C.
45 Möllmann (Germany)
46
47 This Cross-Chapter Box the `moving plate' addresses climate-induced shifts and domesticated production
48 suitability of food species consumed by people. Marine, freshwater, and terrestrial systems are already
49 experiencing species shifts in response to climate change (very high confidence) (see also Sections
50 2.4.2.1.and 3.4.3., Figure Cross-Chapter Box MOVING PLATE.1), with subsequent impacts on food
51 provisioning services, pests, and diseases (high confidence) (see Box 5.8 and Cross-Chapter Box ILLNESS
52 in Chapter 2). This Box highlights food insecurity and malnutrition of vulnerable peoples under climate
53 change for both wild and domesticated aquatic and terrestrial species, discusses challenges for adaptation,
54 and the roles that management (transboundary and ecosystem-based) can play to enable food security, reduce
55 conflicts, and prevent resource over-extraction.
56
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1 Range contractions, shifts or extirpations are projected for terrestrial and aquatic species under warming with
2 greater warming leading to larger shifts and losses, where mitigation would therefore benefit climate refugia
3 and reduce projected biodiversity declines (Smith et al., 2018; Warren et al., 2018). Marine species are
4 moving poleward faster than terrestrial and freshwater species, despite faster warming on land (Pecl et al.,
5 2017; Lenoir et al., 2019; Woolway and Maberly, 2020), leading to new or exacerbated socio-economic
6 conflicts within and between countries (see Figure Cross-Chapter Box MOVING PLATE.1, see Sections
7 13.5.2.2., 15.3.4.4., FAQ 15.3., Mendenhall et al., 2020). There is large variation in the magnitude and
8 pattern of species shifts, even among similar species within a region, leading to changes in communities in a
9 given region (Brown et al., 2016; Pecl et al., 2017). The number of extreme heat stress days are projected to
10 increase for domesticated species like cattle (see Figure Cross-Chapter Box MOVING PLATE.1), leading to
11 shifts in suitable habitat for raising livestock in the open with associated impacts in animal productivity and
12 the costs of adapting in Africa, Asia, Central and South America (Thornton et al., 2021).
13
14 Nutritional dependency, cultural importance, livelihood, or economic reliance on shifting species will
15 increase impacts of climate change, especially for small scale fishers (marine and freshwater), farmers,
16 women, and communities highly dependent on local sources of food and nutrition (high confidence) (see
17 Figures Cross-Chapter Box MOVING PLATE.1 and 3, Sections 3.5.3., 8.2.1.2. and 15.3.4.4, McIntyre et al.,
18 2016; Blasiak et al., 2017; Kifani et al., 2018; Bindoff et al., 2019; Atindana et al., 2020; Hasselberg et al.,
19 2020; Farmery et al., 2021). Micronutrient concentrations from marine fisheries vary with species, providing
20 higher concentrations of calcium, iron and zinc in tropical regions and higher concentrations of omega-3
21 fatty acids in polar regions (Hicks et al., 2019). While consumption of smaller species rich in micronutrients
22 may provide significant benefits against deficiencies in Asia and Africa, local dietary changes in fish
23 consumption may be linked to food preferences, fish availability due to international trade or illegal fishing
24 and competing usage of fish (see Figure Cross-Chapter Box MOVING PLATE.3, Hicks et al., 2019; Sumaila
25 et al., 2020; Vianna et al., 2020). Industrial fleets are likely to switch target species (Belhabib et al., 2016)
26 and inhibit small-scale fishers via illegal, unreported, or unregulated fishing in Exclusive Economic Zones
27 (Belhabib et al., 2019; Belhabib et al., 2020). Extreme events can exacerbate issues, as fisheries are
28 frequently increasingly exploited as a coping mechanism under times of crisis, increasing illegal fishing
29 activities and conflict amongst maritime users (Pomeroy et al., 2016; Mazaris and Germond, 2018). Spatial
30 conflicts between artisanal and commercial foreign fishing fleets are already occurring in Ghana (Penney et
31 al., 2017), and from climate-induced tropical tuna shifts in the Western and Central Pacific Ocean Islands
32 (see Section 15.3.4.4., (Bell et al., 2018a)). Properly managed small-scale fisheries can reduce poverty and
33 improve localized food security and nutrition in low-incom countries but will likely require restriction in the
34 number of fishers, boat size or fishing days (Purcell and Pomeroy, 2015; Hicks et al., 2019).
35
36 Shifting species have negative implications for the equitable distribution of food provisioning services,
37 increasing the complexity of resolving sovereignty claims and climate justice (high confidence) (Allison and
38 Bassett, 2015; Ayers et al., 2018; Baudron et al.; Ojea et al., 2020; Palacios-Abrantes et al., 2020). Higher
39 latitude countries generally have higher GHG emissions and will benefit from poleward migrating resources
40 from tropical poorer and lower-emitting GHG countries (Free et al., 2020). In this context, climate justice
41 supporting fishing arrangements could offset socio-economic impacts from exiting species (Mills, 2018; Lam
42 et al., 2020) and have negative implications particularly for small-scale operators (Farmery et al., 2021),
43 However, considerations of climate justice have not been used by Regional Fisheries Management
44 Organizations (RFMOs) allocation shares to date (Engler, 2020). Species shifting from one historical
45 jurisdiction to another may result in an incentivized depletion of the resource by the country the stock is
46 shifting away from; reforming management to allocate resource sharing of quotas and permits, or stock-
47 unrelated side payments in bilateral or multilateral cooperative agreements may compensate or prevent loss
48 (Diekert and Nieminen, 2017; Free et al., 2020; Ojea et al., 2020; Østhagen et al., 2020; Cross-Chapter Paper
49 Polar 6.2.).
50
51 Strong governance, ecosystem-based and transboundary management are considered fundamental to
52 ameliorate the impacts of climate change (high confidence) but may be limited in effectiveness by the
53 magnitude of change projected under low or no mitigation scenarios (see Sections 2.6.2., 14.4.2.2. and
54 15.3.4.4., Harrod et al., 2018c; Pinsky et al., 2018; Holsman et al., 2020; Ojea et al., 2020). Flexible and
55 rapid policy reform and management adaptation will help to meet sustainability targets (Nguyen et al., 2016;
56 Pentz and Klenk, 2020), and may only be available for countries with the scientific, technical, and
57 institutional capacity to implement these (high confidence) (Peck and Pinnegar, 2018; Figures Cross-Chapter
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1 Box MOVING PLATE.2 and 3). Other adaptation options include `follow the food' thereby migrating
2 further (Belhabib et al., 2016), provision of alternative livelihoods (Thiault et al., 2019; Cross-Chapter Box
3 MIGRATE in Chapter 7, Free et al., 2020), increasing ecosystem resilience by rebuilding coastal mangroves
4 (Tanner et al., 2014; and Box 1.3) and riparian areas of freshwater ecosystems (Mantyka-Pringle et al., 2016)
5 and autonomous adaptations, such as harvesting gear modifications to access new target species (Harrod et
6 al., 2018c; Kifani et al., 2018), practice change, and early-warning systems (see Section 11.3.2.3; Pecl et al.,
7 2019; Melbourne-Thomas et al., 2021). Adaptive capacity will change with country, region, scale
8 (commercial, recreational, Indigenous) of fishery, jurisdiction and resource dependence (see Figure Cross-
9 Chapter Box MOVING PLATE.2 for adaptation options for marine, freshwater, and terrestrial systems).
10 Whilst shifting fishing fleets or herding may be an adaptation option to follow resources, limits to feasibility
11 include institutional, legal, financial, and logistical barriers such as costs of sourcing food and operational
12 economic viability (Belhabib et al., 2016); this could potentially lead to maladaptation through increased
13 greenhouse gas emissions from fuel usage and cultural displacement from traditional fishing and herding
14 lands. Overall, decreases in greenhouse gas emissions under future scenarios would reduce increases in
15 global temperatures and limit species shifts, thereby lowering the likelihood of conflicts and food insecurity
16 (high confidence).
17
18 Coastal regions of the Gulf of Guinea: Ghanian fisheries
19
20 Marine fisheries in Ghana are dominated by artisanal fishers with overfished stocks, high nutritional fish
21 dependency, high illegal fishing, low governance capacity (-0.21 2018, (World Bank, 2019)) and low climate
22 awareness in regional fisheries management (Figure Cross-Chapter Box MOVING PLATE.3, see Chapter 9;
23 Nunoo et al., 2014; Belhabib et al., 2015; Belhabib et al., 2016; Kifani et al., 2018; Belhabib et al., 2019).
24 Artisanal fishing plays a pivotal role in reducing poverty and food insecurity, and the impacts of climate
25 change will risk developing poverty traps (see Section 8.4.5.6., (Kifani et al., 2018)). Climate change
26 induced species redistribution is a large risk to Ghanian fisheries, with projections of over 20 commercial
27 fish species exiting the region with no new species entering under RCP4.5 by 2100 (Oremus et al., 2020),
28 and has already seen increases in warmer-water species with declining stocks. Adaptation options being
29 applied are extending fishing ranges increasing fishing effort (and cost) to access declining fish (with
30 government fuel incentives) (Kifani et al., 2018; Muringai et al., 2021), developing aquaculture for
31 alternative livelihoods, implementation of fleet monitoring to reduce illegal fishing and developing a robust
32 Fisheries Information and Management System that accounts for environmental and climate drivers (Johnson
33 et al., 2014; FAO, 2016; Kassi et al., 2018). However, fisheries remain insufficiently regulated, there is a
34 lack of a skilled workforce, and there is low access to credit; collectively these factors limit options for
35 artisanal fishers to find alternative sustainable employment (FAO, 2016).
36
37 Shifting distributions of freshwater fishery resources: knowledge gaps
38
39 Freshwater fisheries provide the primary source of animal protein and essential micronutrients for an
40 estimated 200 million people globally and are especially important in tropical developing nations (see
41 Section 9.8, Lynch et al., 2017; Funge-Smith and Bennett, 2019.). There is evidence that freshwater fishes
42 have undergone climate-induced distribution shifts (Comte and Grenouillet, 2015; see Section 9.8.5.1.), and
43 further shifts are projected as water temperatures rise and hydrological regimes change, with the largest
44 effects predicted for equatorial, subtropical, and semi-arid regions (Barbarossa et al., 2021). Currently, the
45 effects of distribution shifts on local fishery catch potential, food security, and/or nutrition have not been
46 quantified for any major inland fishery, representing a key knowledge gap for anticipating future adaptation
47 needs for freshwater fishing societies. However, studies on fishers' perceptions of climate-induced changes
48 in fishery catch rates have revealed that using local knowledge to adjust management practices (see Chapter
49 12 Central and South America this volume; Oviedo et al., 2016) and shifting gears, fishing grounds and
50 target species (see Section 9.8.5.3.; Musinguzi et al., 2016) can be effective adaptation options.
51
52
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1
2 Figure Cross-Chapter Box MOVING PLATE.1: Global vulnerabilities to current and projected climate change for
3 living marine resources and cattle. a - Ocean areas are delineated into FAO (Food and Agricultural Organization of the
4 United Nations) regions. Ocean sensitivity is calculated from aggregated sensitivities from Blasiak et al. (2017) S1
5 country data based on number of fishers, fisheries exports, proportions of economically active population working as
6 fishers, total fisheries landings and nutritional dependence, which was subsequently reanalyzed for each FAO region
7 depicted here. Arrows denote projected average commercial (light blue) and artisanal (orange arrows) fishing resource
8 shifts in location under RCP2.6 and under RCP8.5 (dark blue and red arrows respectively) scenarios by 2100. Text
9 boxes highlight examples of vulnerabilities (Bell et al., 2018a), conflicts (Miller et al., 2013; Blasiak et al., 2017;
10 Østhagen et al., 2020), or opportunities for marine resource usage (Robinson et al., 2015; Stuart-Smith et al., 2018;
11 Meredith et al., 2019). b Projected changes in the number of extreme heat stress days per year for cattle (Bos taurus,
12 temperate sub-regions, grey background; Bos indicus, tropical sub-regions, orange background) from 2000 to the 2090s,
13 shown as arrows rooted in the most affected area in each IPCC sub-region pointing to the nearest area of reduced or no
14 extreme heat stress.. Arrows are shown only for sub-regions where > 1 million additional animals affected. Areas in
15 green are those with >5000 animals per 0.5 degree grid cell (Thornton et al., 2021).
16
17
18 Terrestrial species shifts
19
20 There is robust evidence of shifts that terrestrial species have shifted poleward in high latitudes, with general
21 declines of sea-ice dependent as well as some extreme-polar-adapted species (high confidence) (Arctic and
22 Siberian Tundra, see Section 2.4.2.2., Cross-Chapter Paper 6), with often deleterious effects on the food
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1 security and traditional knowledge systems of Indigenous societies (Horstkotte et al., 2017; Pecl et al., 2017;
2 Mallory and Boyce, 2018; Forbes et al., 2020). Recent decades have seen declines in Arctic reindeer and
3 caribou (see Section 2.5.1., Cross-Chapter Paper 6) and adaptation responses include utilization of
4 Indigenous knowledge with scientific sampling to maintain traditional management practices (Pecl et al.,
5 2017; Barber et al.; Forbes et al., 2020). Preserving herder livelihoods will necessitate novel solutions
6 (supplementary feeding, seasonal movements), where governance, ecological and socio-economic trade-offs
7 will be balanced at the local level (Horstkotte et al., 2017; Pecl et al., 2017; Mallory and Boyce, 2018;
8 Forbes et al., 2020). Wild meat consumption plays a critical, though not well understood, role in the diets and
9 food security of several hundred million people (medium evidence), for example in lower latitudes such as
10 central Africa and the Amazon basin (Bharucha and Pretty, 2010; Godfray et al., 2010; Nasi et al., 2011;
11 Friant et al., 2020). Although illegal in many countries, wild meat hunting occurs either in places where there
12 is no or limited domesticated livestock production, or in places where shock events such as droughts and
13 floods that threaten food supply, forcing increased reliance on wild foods including bush meat (Mosberg and
14 Eriksen, 2015; Bodmer et al., 2018). Appropriate management of wild meat for reliant peoples under
15 projected climate change will necessitate incorporating social justice elements into conservation and public
16 health strategies (see Cross-Chapter Box ILLNESS in Chapter 2, Cross-Chapter Box COVID in Chapter 7,
17 Friant et al., 2020; Ingram, 2020; Pelling et al., 2021).
18
19
20
21 Figure Cross-Chapter Box MOVING PLATE.2: Common adaptation options, limitations, and potential for
22 adaptation and maladaptation in aquatic and terrestrial species with climate-induced movement of food species and
23 reliant peoples.
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1
2
3 In terrestrial, marine, and freshwater systems human populations already impacted by poverty and hunger
4 experience greater risk under climate change. Future food security will depend on access to other sustainable
5 sources either via transnational agreements or resource / livelihood diversification. Sudden shocks across
6 food production systems (Cottrell et al., 2019) can lead to increases in fisheries harvest and wild meat
7 consumptions and following food species may result in community relocations or disruption and loss of
8 access to historical places of attachment (high confidence) (Pecl et al., 2017; Lenoir et al., 2019; Meredith et
9 al., 2019; Melbourne-Thomas et al., 2021; see Cross-Chapter Box MIGRATE in Chapter 7). Ecosystem
10 based management approaches exist for terrestrial, marine and freshwater systems, but have proved
11 successful only with early engagement of local small-scale, subsistence fishers / harvesters, utilizing
12 Indigenous knowledge and local knowledge and needs, in addition to those of larger-scale operators (high
13 confidence) (Huntington et al., 2015; McGrath and Costello, 2015; Huq and Stubbings, 2016; Huq et al.,
14 2017; Raymond-Yakoubian et al., 2017; Nalau et al., 2018; Raymond-Yakoubian and Daniel, 2018; Pecl et
15 al., 2019; Planque et al., 2019). Currently there is large regional differences in climate literacy in RFMOs
16 (Sumby et al., 2021) which, when combined with low governance and GDP per capita, will limit adaptation
17 capacity and increase vulnerabilities, particularly for tropical and sub-tropical regions already at increased
18 risk due to poleward species migrations (see Figure Cross-Chapter Box MOVING PLATE.3). Trade will be
19 an alternative to compensate for the moving plate but has specific risks that can amplify inequities and
20 maladaptation (Asche et al., 2015; Vianna et al., 2020).
21
22
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1
2 Figure Cross-Chapter Box MOVING PLATE.3: Global documented fisheries adaptive capacity to climate change
3 and regional seafood micronutrient deficiency risk. Ocean areas are delineated into FAO (Food and Agricultural
4 Organization of the United Nations) regions. Fisheries management adaptive capacity is a function of: averaged GDP
5 World Development Indicators for 2018 (World Bank, 2020); climate awareness assessments of 30 of the FAO
6 recognized most recent Regional Fisheries Management Organizations with direct fisheries linkages (see
7 Supplementary Material SM5.5); governance effectiveness index based on six aggregate indicators (voice and
8 accountability, political stability and absence of violence / terrorism, government effectiveness, regulatory quality, rule
9 of law, control of corruption) from 2018 World Governance Indicator (World Bank, 2019) data, and; heterogeneity of
10 countries within each FAO zone (highly heterogeneous regions are less likely to establish sustainable and efficient
11 fisheries management for the entire FAO zone). Land area represents the percentage regional averaged seafood
12 micronutrient deficiency risk of calcium, iron, zinc, and vitamin A from 2011 data (Beal et al., 2017).
13
14
15 [END CROSS-CHAPTER BOX MOVING PLATE HERE]
16
17
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1 5.9 Ocean-based and Inland Aquaculture Systems
2
3 Global aquaculture provides more fish for human consumption than wild capture fisheries, with projected
4 provisioning of 60% by 2030 (FAO, 2018c). Aquaculture can contribute to SDGs by reducing poverty and
5 food insecurity, filling increasing aquatic food demand shortages from declining capture fisheries
6 production, (medium confidence) ( Figure 5.13a and c, World Bank, 2013; Béné et al., 2016; Hambrey, 2017;
7 Beveridge et al., 2018b; Kalikoski et al., 2018; Belton et al., 2020), improving social inequities for poor rural
8 communities (Béné et al., 2016; FAO, 2018c; Vannuccini et al., 2018; Pongthanapanic et al., 2019). Global
9 aquaculture production reached 82 million tonnes (Mt) of food fish, crustaceans, molluscs, and other aquatic
10 animals from inland (51 Mt) and marine (31 Mt) systems, and 32 Mt of aquatic plants in 2018 (FAO, 2020d).
11 China, India, Indonesia, Vietnam, Bangladesh, Egypt, Norway and Chile are major production regions
12 (FAO, 2020d). The range of species, farming methods and environments makes aquaculture the most
13 diverse, long-standing farming practice in the world with an estimated global sectoral value of USD 250
14 billion in 2018 ( Figure 5.13b and 5.14d, Bell et al., 2019; Harland, 2019; FAO, 2020d; Houston et al., 2020;
15 Metian et al., 2020), but is dominated by 20 finfish, 9 mollusc and 6 crustacean species (FAO, 2020). Inland
16 aquaculture in freshwater and coastal ponds accounts for 85-90% of farmed production (Beveridge et al.,
17 2018b; Naylor et al., 2021). Globally 20.5 million people are engaged in aquaculture (FAO, 2020d), where
18 marine finfish farming is primarily conducted by high-income countries and inland production is dominated
19 by small-scale producers in lower-middle-income countries (Vannuccini et al., 2018).
20
21
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2 Figure 5.13: Global and regional aquaculture production a) world wild capture fisheries and aquaculture inland
3 (freshwater and brackish) and marine production from 1950-2018, b) diversity of aquaculture groups cultured in 2016,
4 and c) regional aquaculture share of total fisheries production, and d) global aquaculture species production in 2018 by
5 region and type (freshwater, brackish, or marine) on a logged scale (FAO, 2018c; FAO, 2020c; FAO, 2020d).
6
7
8 5.9.1 Observed Impacts
9
10 Marine aquaculture food production is being impacted directly and indirectly by climate change (high
11 confidence) (Bindoff et al., 2019). Ocean pH and oxygen levels are declining, whereas global warming, sea
12 level rise and extreme events are increasing ( Cross-Chapter Box SLR in Chapter 3, Canadell et al., 2021;
13 Eyring et al., 2021; Fox-Kemper et al., 2021; Lee et al., 2021;). Marine heatwaves have been increasing in
14 both incidence and longevity over the past century (Frolicher and Laufkotter, 2018; Oliver et al., 2018;
15 Bricknell et al., 2021) with productivity consequences for marine aquaculture (mariculture), carbon
16 sequestration and local species extinctions (high confidence) (Weatherdon et al., 2016; Smale et al., 2019).
17 Temperature increases related to El Niño climatic oscillations have caused mass fish mortalities either
18 through warming waters (e.g. Pacific threadfin in Hawaii (McCoy et al., 2017)), or associated harmful algal
19 blooms (e.g. 12% loss of Atlantic salmon as well as other fish and shellfish in Chile in 2016 with estimated
20 $800 million in losses (high confidence) (Clement et al., 2016; Apablaza et al., 2017; Leon-Munoz et al.,
21 2018; Trainer et al., 2020)). Increases in sea lice parasite infestations on salmon are related to higher salinity
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1 and warmer waters (medium confidence) (Groner et al., 2016; Soto et al., 2019). Ocean acidification is
2 having negative impacts on the sustainability of mariculture production (high confidence) (Bindoff et al.,
3 2019) with observed impacts on shellfish causing significant production and economic losses for regions,
4 estimated at losses of nearly USD $110 million by 2015 in the Pacific Northwest (Barton et al., 2015;
5 Ekstrom et al., 2015; Waldbusser et al., 2015; Zhang et al., 2017b; Doney et al., 2020). Ocean oxygen levels
6 are declining due to climate change (Hoegh-Guldberg et al., 2018; IPCC, 2021) and decreased oxygen
7 (hypoxia) has negative impacts on fish physiology (Cadiz et al., 2018; Hvas and Oppedal, 2019; Martos-
8 Sitcha et al., 2019; Perera et al., 2021), fish growth, behaviour and sensitivity to concurrent stressors (high
9 confidence) (Stehfest et al., 2017; Abdel-Tawwab et al., 2019).
10
11 Observed impacts on inland systems have generally been site and region specific (high confidence) (Hoegh-
12 Guldberg et al., 2018; Sainz et al., 2019; Lebel et al., 2020). Salinity intrusions into freshwater aquaculture
13 systems have changed oxygen and water quality of inland ponds, resulting in mortalities in areas such as
14 India and Bangladesh (medium confidence) (Dubey et al., 2017; Dabbadie et al., 2018). Rapid changes in
15 temperature, precipitation, droughts, floods and erosion have created significant production losses for aquatic
16 farmers in Cambodia, Laos, Myanmar, Thailand, Viet Nam and Ghana (medium confidence) (Asiedu et al.,
17 2017; Pongthanapanic et al., 2019; Lebel et al., 2020). Algal blooming and inland lake browning related to
18 warming was found to negatively affect fish biomass (van Dorst et al., 2018). Observed indirect effects of
19 climate change on aquaculture include extreme weather events that damage coastal aquaculture infrastructure
20 or enable flooding, both leading to animal escapees (e.g. fish, shrimp), damaged livelihoods and interactions
21 with wild species (high agreement, medium evidence) (Beveridge et al., 2018b; Dabbadie et al., 2018; Kais
22 and Islam, 2018; Pongthanapanic et al., 2019; Ju et al., 2020).
23
24 5.9.2 Assessing Vulnerabilities
25
26 Aquaculture vulnerability assessments have shown that countries from both high and low latitudes are highly
27 vulnerable to climate change, where vulnerability is driven by particular exposures, economic reliance, type
28 of production sector (freshwater, brackish, marine) and adaptive capacity (high confidence) (Handisyde et
29 al., 2017; Soto et al., 2018). Regional aquaculture vulnerabilities and risk mitigation potentials for the major
30 FAO reporting regions are shown in Figure 5.14. Best practice guidelines for assessments exist (Brugère et
31 al., 2019; FAO, 2020d), but in practice most only cover some climatic drivers (medium agreement, limited
32 evidence) (Soto et al., 2018). Holistic vulnerability assessments include ecosystem services (Custódio et al.,
33 2020; Gentry et al., 2020) and farming practices which can exacerbate production pressures (stocking
34 densities, eutrophication, fish stress) (Soto et al., 2018; Sainz et al., 2019). Common vulnerabilities to inland
35 and marine aquaculture include increasing incidence and toxicity of harmful algal blooms related to warming
36 waters, causing fish kills and product consumption risks, negatively impacting the productivity and stability
37 of production sectors and reliant communities (high confidence) (Soto et al., 2018; Aoki et al., 2019)
38 (Bannister et al., 2019).
39
40 There is high confidence that inland aquaculture in Southeast Asia is highly vulnerable to climate change,
41 due to fluctuations in water resources either through climatic variability in precipitation, flooding or salinity
42 inundation or through competition (Handisyde et al., 2017; Nguyen et al., 2018; Soto et al., 2018; Islam et
43 al., 2019; Nguyen et al., 2019b; Prakoso et al., 2020). Studies in Bangladesh and Indonesia highlighted
44 regional and species-specific vulnerabilities (Prakoso et al., 2020) and roles of governance in vulnerability
45 reduction (Islam et al., 2019).
46
47
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1
2 Figure 5.14: Assessment of a) inland freshwater and brackish aquaculture (salinities of <10ppm and / or no connection
3 to the marine environment) b) marine aquaculture vulnerabilities and mitigation potential per major FAO production
4 zones. See SM5.6 (Tables SM5.4, 5.5, 5.8,5.9) for assessment methodologies.
5
6
7 In the marine sector, vulnerability models (Brugère and De Young, 2015; Handisyde et al., 2017) have been
8 adapted and applied to semi-quantitative spatial risk assessments for Chilean Atlantic salmon, where analysis
9 of exposure threat coupled with mortality and temperature farm data could enhance salmon production (Soto
10 et al., 2019). Vulnerability assessments in Korea (RCP8.5 temperature increase of 4-5°C by 2100) (Kim et
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1 al., 2019a) and the U.S. (ocean acidification, Barton et al., 2015; Ekstrom et al., 2015) found major
2 exposure-related vulnerabilities for seaweeds and shellfish, with reduced vulnerabilities under higher
3 production control and adaptive capacity. Global bivalve vulnerability assessments (RCP8.5 by 2100) show
4 high vulnerabilities for major producing countries related to cyclones (China, Japan, South Korea, Thailand,
5 Viet Nam, and North Korea), regional risk of high sensitivity and low adaptive capacity (Chile, Peru, Spain,
6 Italy), with few major producers (France, the Netherland and U.S.) anticipated to remain moderately
7 vulnerable by 2100 (Stewart-Sinclair et al., 2020).
8
9 Climate uncertainty and data limitations hinder vulnerability assessments (high confidence), so broader
10 vulnerabilities and qualitative assessments can be used (Brugère and De Young, 2015; Soto et al., 2018;
11 Brugère et al., 2019; Cochrane et al., 2019). Filling data gaps with monitoring (high confidence), increasing
12 governmental support to assist particularly vulnerable small- and medium-scale farmers with increased costs
13 associated with risk management and uncertainty (medium confidence) and the early inclusion of community
14 stakeholders (high agreement, medium evidence) can reduce vulnerabilities (Handisyde et al., 2017;
15 Dabbadie et al., 2018; Soto et al., 2018; Bindoff et al., 2019; Cochrane et al., 2019).
16
17 5.9.2.1 Gender and other social vulnerability and roles in aquaculture
18
19 There are regional differences in women's roles, responsibilities and involvement in adaptation strategies in
20 the aquaculture sector. Women comprise 14% of the 2018 global aquaculture workforce of 20.5 million
21 (FAO, 2020c), representing up to 42% of the salmon workforce in Chile (Chávez et al., 2019),
22 predominantly in processing roles (Gopal et al., 2020). In the majority of lower-middle-income countries
23 seaweed culture is dominated by women in family-owned businesses as in Zanzibar and the Philippines
24 (Brugere et al., 2020; Ramirez et al., 2020), where women are not always paid directly but contribute to
25 family incomes (high confidence) (Msuya and Hurtado, 2017; Brugere et al., 2020; Ramirez et al., 2020). In
26 India women collect stocking juveniles and assist in pond construction, in Bangladesh women do the same
27 tasks as men and in Ghana women undertake post-harvest fishing activities (Lauria et al., 2018). Women
28 employed in aquaculture cooperatives gained adaptive capacity, which reduced gender inequities (medium
29 confidence) (Farquhar et al., 2018; Gonzal et al., 2019), but lack of financial access for women can create
30 gender inequality at larger commercial scales (Gurung et al., 2016; Call and Sellers, 2019).Women in
31 aquaculture experience competing roles between employment, childcare and home duties (high confidence)
32 (Morgan et al., 2015; Lauria et al., 2018; Chávez et al., 2019; see Cross-Chapter Box GENDER in Chapter
33 18), and differ from men in terms of perceptions of environmental risk, climate change, adaptation
34 behaviour, with limited contributions to decision-making (medium confidence) (Barange and Cochrane,
35 2018). Therefore, effective climate aquaculture adaptation options need to address gender inequality e.g.
36 suitable technology designs that fit with social norms and access to credit to facilitate independent uptake
37 (medium evidence, high agreement) (Morgan et al., 2015; Oppenheimer et al., 2019). Generalized best
38 practices for gender-sensitive approaches to adaptation are relevant for aquaculture (UNFCCC, 2013).
39
40 5.9.3 Projected Impacts
41
42 Projected impacts on regional inland and marine aquaculture production are summarized in Figure 5.15.
43
44 5.9.3.1 Inland freshwater and brackish aquaculture
45
46 Predicted sea level and temperature rise will result in coastal inundation into brackish and inland aquaculture
47 systems (high confidence) (Mehvar et al., 2019; Nhung et al., 2019; Oppenheimer et al., 2019; IPCC AR6),
48 with negative impacts on aquaculture production in Viet Nam, East Africa and Jamaica (medium confidence)
49 (Lebel et al., 2018; Nguyen et al., 2018; Bornemann et al., 2019). Precipitation and temperature changes will
50 cause drought and flooding, negatively affecting near-shore fishpond productivity (limited evidence)
51 (Canevari-Luzardo et al., 2019), but provide competitive advantages to non-native shrimp in Australia
52 (limited evidence) (Cerato et al., 2019). Warming and acidification will increase harmful algal bloom toxicity
53 in freshwater systems, but responses may be strain-specific (Griffith and Gobler, 2020; Hennon and
54 Dyhrman, 2020). As for molluscs in marine systems, projected climate change in freshwater and brackish
55 systems may limit the availability of wild-sourced juveniles from fisheries (Beveridge et al., 2018). Projected
56 impact studies for the inland and small-scale aquatic sectors are very limited (Halpern et al., 2019;
57 Galappaththi et al., 2020b), therefore this is a noted knowledge gap.
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1
2
3
4 Figure 5.15: Assessment of projected impacts of climate change on a) inland freshwater and brackish aquaculture
5 (salinities of <10ppm and / or no connection to the marine environment) b) marine aquaculture per major FAO
6 production zones. See SM5.6 (Tables SM5.6, 5.10) for assessment methodologies.
7
8
9 5.9.3.2 Marine aquaculture
10
11 5.9.3.2.1 Finfish culture
12 Global projections of ocean warming, primary productivity and ocean acidification predict suitable habitat
13 expansions and short-term growth benefits for finfish aquaculture for some regions (medium confidence) (see
14 Figure 5.15) until thermal tolerances or productivity constraints are exceeded by 2090 (Beveridge et al.,
15 2018b; Dabbadie et al., 2018; Froehlich et al., 2018a; Catalán et al., 2019; Thiault et al., 2019; Falconer et
16 al., 2020a). Sensitivities for marine finfish may be high even under +1.5-2.0°C (medium confidence)
17 (Gattuso et al., 2018), resulting in finfish farms moving northward to maintain productivity (e.g., Arctic
18 (Troell et al., 2017). Downscaled projections of regionally specific tolerances (Klinger et al., 2017) may be
19 particularly useful for management and planning; a 0.5°C rise is predicted for Chilean salmon aquaculture
20 (Soto et al., 2019) and potential projected negative impacts on productivity in Norway by 2029 (limited
21 evidence) (Falconer et al., 2020a). Marine heatwaves are predicted to increase in occurrence, intensity, and
22 persistence under RCP4.5 or RCP8.5 by 2100 (Oliver et al., 2019; Bricknell et al., 2021) with risk partly
23 mitigated by husbandry (medium confidence) (McCoy et al., 2017). Generally, negative impacts are
24 predicted for marine species with residual risk increasing with level of exposure (Sara et al., 2018; Smale et
25 al., 2019), where warming will affect oxygen solubility and reduce salmon culture capacity (limited
26 evidence) (Aksnes et al., 2019, Chapter 3) and combine with increasing incidence of harmful algal blooms
27 (high confidence) resulting in negative impacts for food security and nutrition and health (Oppenheimer et
28 al., 2019; Colombo et al., 2020; Glibert, 2020; Raven et al., 2020). Climate change is predicted to affect the
29 incidence, magnitude and virulence of finfish disease, e.g., Vibriosis (Barber et al., 2016; Mohamad et al.,
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1 2019a; Mohamad et al., 2019b), but specific host-pathogen-climate relationships are not yet established (high
2 confidence) (Slenning, 2010; Marcogliese, 2016; Montanchez et al., 2019; Bandin and Souto, 2020;
3 Behringer et al., 2020; Filipe et al., 2020; Montanchez and Kaberdin, 2020). Projected climate change will
4 also increase competition for feed ingredients between aquatic and terrestrial animal production systems (see
5 Section 5.13.2.).
6
7 5.9.3.2.2 Shellfish culture
8 Globally, there is overall high confidence that suitable shellfish aquaculture habitat will decline by 2100
9 under projected warming, ocean acidification and primary productivity changes, with significant negative
10 impacts for some regions and species before 2100 (Table 5.9, Froehlich et al., 2018a; Ghezzo et al., 2018).
11 Shellfish growth will increase with warming waters until tolerances are reached, e.g., through extreme El
12 Niño events (high confidence) (Beveridge et al., 2018b; Dabbadie et al., 2018; Liu et al., 2018b; Liu et al.,
13 2020). Rising temperatures and ocean acidification will result in losses of primary productivity and farmed
14 species from tropical and subtropical regions, and gains in higher latitudes (high confidence) (Froehlich et
15 al., 2018a; Aveytua-Alcazar et al., 2020; Chapman et al., 2020; Des et al., 2020; Oyinlola et al., 2020), but
16 net marine production gains could be achieved under strong mitigation (Thiault et al., 2019). Shellfish Vibrio
17 infections will increase with warming waters and extreme events, increasing shellfish mortalities (medium
18 confidence) (Green et al., 2019; Montanchez et al., 2019) with ocean acidification impairing immune
19 responses (limited evidence) (Cao et al., 2018b). Bivalve larvae are known to be highly vulnerable to ocean
20 acidification (high confidence) (see Section 3.3, Bindoff et al., 2019), with projected regional and species-
21 specific levels of impact (high confidence) (Ekstrom et al., 2015; Zhang et al., 2017b; Mangi et al., 2018)
22 (Greenhill et al., 2020). Ocean acidification is also projected to weaken shells, affecting productivity and
23 processing (high confidence) (Martinez et al., 2018; Cummings et al., 2019) and dependent livelihoods
24 (Doney et al., 2020).
25
26 5.9.3.2.3 Aquatic plant culture
27 There is medium confidence that cultivated seaweeds are predicted to suffer habitat loss resulting in
28 population declines and northward shifts (Table 5.11).
29
30
31 Table 5.11: Projected impacts of climate on specific inland, brackish, and marine culture systems and species.
Exposure Scenario Region Production Species Impact Reference
system
Temperature RCP4.5 and Northern Inland Nile tilapia Reduced productivity Lebel et al.
increase RCP8.5 by Thailand (2018)
2050
Precipitation - Jamaica Inland Tilapia Reduced productivity, Canevari-
change
(drought, infrastructure damage Luzardo et al.
hurricane,
heavy (2019)
rainfall)
Temperature 4°C increase, Australia Inland Freshwater Increased production in Cerato et al.
increase B2, A1B by
2100 shrimp non-native zones (2019)
Temperature CMIP5 RCP Global Marine Finfish Increased suitable Froehlich et
increase, 8.5 in 20- species habitat expansion for al. (2018a),
ocean year regions (Russia, Thiault et al.
acidification, increments to Norway, U.S. Alaska, (2019)
primary 2090 Denmark, Canada). By
productivity 2100 reduction in
declines productivity for major
producers (Norway,
China)
Temperature 2-5°C Europe Marine Atlantic Increased growth Catalán et al.
increase increase salmon (2019)
under
RCP8.5
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Temperature RCP4.5 to Norway Marine Atlantic Growth threshold Falconer et al.
increase 2029 Global Marine salmon reached by 2029 (2020a)
Temperature Downscaled Atlantic Increased or decreased Klinger et al.
increase CM2.6 by Marine salmon, growth rates depending (2017)
2050 cobia and on region
sea bream
Temperature CMIP5 RCP Global Shellfish Overall declines in Froehlich et
increase, 8.5 in 20- suitable habitat al. (2018a)
ocean year globally, up to 50-100%
acidification, increments to reductions regions in
primary 2090 China, Thailand, and
productivity Canada
declines
Temperature CMIP5 Italy Marine Clams Negative impacts for Ghezzo et al.
increase RCP8.5 by France Marine Oysters juvenile timing, spatial (2018)
2050, 2100 distribution, and quality Thomas et al.
Temperature CMIP5 Marine Shellfish Increase incidence of (2018)
increase RCP2.6 and oyster mortality;
RCP8.5 by increase by 2035 to Oyinlola et al.
2035, 2070 annual occurrence by (2020)
2070
Temperature RCP2.6 and Global Species reduction (10-
increase RCP8.5 by 40%) in tropical and
2050 subtropical regions with
increase (40%) in
higher latitudes
Temperature Ecopath with U.S. Marine Shellfish Reduction primary Chapman et
increase, RCP 8.5 by Spain productivity and al. (2020)
ocean 2100 (2.8°C subsequent bivalve
acidification warming and carrying capacity
pH 7.89)
Temperature RCP8.5 by Marine Mussels Decline in mussel Des et al.
increase, 2088-2099 optimal culture (2020)
stratification conditions of 60% in
change upper and 30% in
deeper waters by 2099
Temperature RCP2.6 and Global Marine Shellfish Under RCP8.5 a decline Thiault et al.
increase, 8.5 by 2070- in shellfish production (2019)
ocean 2090 due to primary
acidification productivity reduction
in tropical regions and
gains in high latitudes.
Under RCP2.6 marine
production will have net
gain
Temperature 4°C increase Global Marine Vibrio spp. Increased virulence Montanchez
increase Marine (mortality et al. (2019)
causative Increased oyster
Temperature 5°C increase Global agent) mortality Green et al.
increase Oysters (2019)
(marine heat
wave) ~2000ppm Global Marine Oysters Impaired immune Cao et al.
Ocean CO2 U.S. Marine Shellfish function (2018b)
acidification
RCP8.5 in Regional projected Ekstrom et al.
Ocean 20-year vulnerabilities (2015)
acidification Southern Alaska and
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increments to Pacific Northwest at
after 2099 more immediate risk
Ocean A1B and U.K. Marine Shellfish Regional projected Mangi et al.
vulnerabilities - Wales (2018)
acidification RCP8.5 by and England at more
immediate risk
2100
Ocean RCP2.6 and East Marine Shellfish Carbonate saturation RCP2.6 and
acidification RCP8.5 by China projected to decrease by RCP8.5 by
2300 13% and 72% under 2300 (Zhang
RCP2.6 and RCP8.5 et al., 2017b)
respectively, projecting
decreased shellfish
productivity
Increased RCP2.6 and North Sea Marine Seaweed Northward population Westmeijer et
temperature RCP8.5 by shift by 110-163km and al. (2019),
2100 450-635km under
RCP2.6 and RCP8.5
respectively
Increased RCP4.5 and Japan Marine Kelp Habitat decline to 30- Sudo et al.
51% and 0-25% under (2020).
temperature RCP8.5 by RCP4.5 and RCP8.5
respectively
2090
1
2
3 5.9.3.2.4 Societal impacts within the production system
4 Marine aquaculture provides distinct ecosystem services through provisioning (augmenting wild fishery
5 catches), regulating (coastal protection, carbon sequestration, nutrient removal, improved water clarity),
6 habitat and supporting (artificial habitat) and cultural (livelihoods and tourism) services (Gentry et al., 2020),
7 which vary with species, location, and husbandry (Alleway et al., 2019). Projected thermal increases of
8 1.5°C will reduce ecosystem services, further reduced under 2°C warming, with associated increases in
9 acidification, hypoxia, dead zones, flooding, and water restrictions (medium confidence) (Hoegh-Guldberg et
10 al., 2018). Sudden production loses from extreme climate events can exacerbate food security challenges
11 across production sectors, including aquaculture, increasing global hunger (high confidence) (Cottrell et al.,
12 2019; Food Security Information Network, 2020). While aquaculture provides positive influences such as
13 food security and livelihoods, there are negative concerns over environmental impacts (including high
14 nutrient loads from sites) and socio-economic conflicts (Alleway et al., 2019; Soto et al., 2019) and adoption
15 of ecosystem approaches are dependent on particular user groups and regions (Gentry et al., 2017; Brugère et
16 al., 2019; Gentry et al., 2020). In coastal Bangladesh projected saline inundation to wetland ecosystem
17 services will result in ecosystem services losses of raw materials and food provisioning, ranging from USD
18 0-20.0 million under RCP2.6 to RCP8.5 scenarios (Mehvar et al., 2019). Mangrove deforestation for shrimp
19 farming in Asia negatively impacts ecosystem services and reduces climate resilience (medium confidence)
20 (Mehvar et al., 2019; Nguyen and Parnell, 2019; Reid et al., 2019; Custódio et al., 2020), while mangrove
21 reforestation efforts may have some effectiveness in recreating important nursery grounds for aquatic species
22 (low confidence) (Gentry et al., 2017; Chiayarak et al., 2019; Hai et al., 2020). Families are highly vulnerable
23 to climate change where nutritional needs are being met by self-production, e.g., Mozambique, Namibia
24 (Villasante et al., 2015), Zambia (Kaminski et al., 2018) and Bangladesh (high confidence) (Pant et al.,
25 2014). Climate change will therefore affect multiple ecosystem services where ultimately decisions on
26 balance or trade-offs will vary with regional perceptions of service value (high confidence).
27
28 5.9.4 Aquaculture Adaptation
29
30 5.9.4.1 Adaptation planning
31 Aquaculture is often viewed as an adaptation option for fisheries declines, thereby alleviating food security
32 from losses of other climate change impacts (Sowman and Raemaekers, 2018; Johnson et al., 2020) e.g.,
33 Pacific Islands freshwater aquaculture, Bangladesh crop-aquaculture systems, or Viet Nam rice-fish
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1 cultivations (Soto et al., 2018). Many adaptations are specific to regions, countries, or sector, implemented
2 on a regional to national scale (FAO, 2018c; Galappaththi et al., 2020b). Adaptation likelihood (potential),
3 effectiveness and risk of maladaptation was assessed per major FAO production region for inland, brackish,
4 and marine aquaculture (Figure 5.16) production systems. Potential adaptation measures to reduce
5 production loss can be built upon existing adaptation planning and guidelines, to reduce the risk of
6 maladaptation including feedback loops (e. g. FAO, 2015; Bueno and Soto, 2017; Dabbadie et al., 2018;
7 FAO, 2018c; Poulain et al., 2018; Brugère et al., 2019; Pham et al., 2021; Soto et al., 2021). Large climate
8 change adaptation strategies for the aquaculture sector exist e.g. U.S. (Link et al., 2015), Australia (Hobday
9 et al., 2017) and South Africa (Department of Environmental Affairs, 2016). Lower income countries often
10 lack financial, technical, or institutional capacity for adaptation planning (Galappaththi et al., 2020b), but
11 examples include Bangladesh and Myanmar (FAO, 2018c), with programs offering adaptation funding
12 (Dabbadie et al., 2018). Early participation of stakeholders in adaptive planning has promoted action and
13 ownership of results (high confidence) e.g. India and U.S. (Link et al., 2015; FAO, 2018c; Soto et al., 2018)
14 Early outreach, education, and knowledge gap assessments raises awareness, where utilization of local
15 knowledge and Indigenous knowledge and scientific involvement support informed adaptive planning and
16 uptake for all stakeholders (high confidence) (Cooley et al., 2016; FAO, 2018c; Rybråten et al., 2018; Soto et
17 al., 2018; McDonald et al., 2019; Galappaththi et al., 2020b), as perceptions of climate risk and capacity will
18 vary (Tiller and Richards, 2018). Supporting the active involvement of women helps address gender inequity
19 and perceived risk, particularly for smallholder farmers (high confidence) (Morgan et al., 2015; Barange and
20 Cochrane, 2018; FAO, 2018c; Avila-Forcada et al., 2020). However, regional, and national political
21 influences, financial and technical capacity, governance planning and policy development will ultimately
22 support or hinder adaptation for aquaculture (high confidence) (Cooley et al., 2016; FAO, 2018c;
23 Galappaththi et al., 2020b; Greenhill et al., 2020).
24
25
26
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1 Figure 5.16: Assessment of the likelihood and effectiveness of a range of adaptation options for potential
2 implementation in the near-term (next decade) for a) inland freshwater and brackish aquaculture (salinities of <10ppm
3 and / or no connection to the marine environment) and b) marine aquaculture systems per major FAO production zone.
4 See SM5.6 (Tables SM5.7, 5.11) for assessment methodologies.
5
6
7 5.9.4.2 Species selections and selective breeding
8 Adaptation options at the operational level include species selections, e.g., cultivation of brackish species
9 (shrimp, crabs) during dry seasons, and rice-finfish in wetter seasons in Thailand (Chiayarak et al., 2019),
10 use of salt-tolerant plants in Viet Nam (Nhung et al., 2019; Paik et al., 2020), converting inundated rice
11 paddies into aquaculture, rotating shrimp, and rice culture (high confidence) (Chiayarak et al., 2019). Species
12 diversification through co-culture, integrated aquaculture-agriculture (e.g. rice-fish) or integrated multi-
13 trophic culture (e.g. shrimp-tilapia-seaweed or finfish-bivalve-seaweed) may maintain farm long-term
14 performance and viability by: creating new aquaculture opportunities; promoting societal and environmental
15 stability; reducing GHG emissions through reduced feed usage and waste, and; carbon sequestration
16 (medium confidence) ( see Section 5.10, Li et al., 2019; Galappaththi et al., 2020b; Prakoso et al., 2020; Tran
17 et al., 2020) (Ahmed et al., 2017; Bunting et al., 2017; Gasco et al., 2018; Soto et al., 2018; Ahmed et al.,
18 2019; Dubois et al., 2019; FAO, 2019c; Freed et al., 2020). In practice, most aquaculture operations
19 concentrate on single-species systems (Metian et al., 2020) and barriers such as land availability, freshwater
20 resources and lack of credit access may limit the uptake and success of integrated adaptation approaches to
21 climate change (Ahmed et al., 2019; Tran et al., 2020; Kais and Islam, 2021).
22
23 Selective breeding can promote climate resilience (medium confidence) (Klinger et al., 2017; Fitzer et al.,
24 2019) and operations have already intentionally, or unintentionally, selected for production traits for
25 changing conditions (de Melo et al., 2016; Tan and Zheng, 2020). Exposure of broodstock to future climate
26 conditions may or may not confer advantages to offspring (moderate evidence, low agreement) (Parker et al.,
27 2015; Griffith and Gobler, 2017; Thomsen et al., 2017; Durland et al., 2019). Traditional pedigree
28 developments require extensive phenotypic data, but genomic selections can rapidly select for robust
29 climate-associated traits (Sae-Lim et al., 2017; Gutierrez et al., 2018; Zenger et al., 2018; Houston et al.,
30 2020; Tan and Zheng, 2020). Genomic resources are available for salmon, rainbow trout, coho, carp, tilapia,
31 seabass, bream, turbot, flounder, catfish, yellow drum, scallops, oysters and shrimp, but have been developed
32 for disease and growth selections rather than climate resistance (Guo et al., 2018; Houston et al., 2020)
33 (Dégremont et al., 2015a; Dégremont et al., 2015b; Abdelrahman et al., 2017; Gjedrem and Rye, 2018;
34 Gutierrez et al., 2018; Liu et al., 2018a; FAO, 2019d), although bivalve selections for ocean acidification and
35 warming resiliency are underway (Tan and Zheng, 2020). Targeted genome editing could modify phenotypes
36 of major aquaculture species (Li et al., 2014a; Elaswad et al., 2018; Yu et al., 2019; Houston et al., 2020),
37 but uptake is dependent upon national regulatory and public approvals. Local adaptations within species with
38 higher climate resiliencies may assist in selections (Thomsen et al., 2017; Falkenberg et al., 2019; Scanes et
39 al., 2020; Toomey et al., 2020), but highlights the need to consider specific farming environments for
40 selective processes (Houston et al., 2020). Projections of climate on aquaculture production traits are not
41 well understood (Lhorente et al., 2019), therefore genetic diversity needs to be maintained to ensure
42 population fitness (high confidence) (Bitter et al., 2019; Lhorente et al., 2019; Visch et al., 2019; Houston et
43 al., 2020; Mantri et al., 2020).
44
45 5.9.4.3 Farm site selection, infrastructure, and husbandry
46
47 Land-based aquaculture systems including hatcheries may reduce exposure to climatic extremes (due to
48 better control of the culture environment), limit water usage, reduce juvenile reliance and buffer climate
49 effects using optimal diets (high confidence) (Barton et al., 2015; Reid et al., 2019; Cominassi et al., 2020).
50 However, land-based aquaculture requires large capital and operational costs, use of land increasing conflicts
51 between land and water use, increased energy demands increasing GHG if fossil fuels are primary energy
52 source, require necessary expertise and will not reduce outgrowing exposures (high confidence) (see Section
53 5.13, Beveridge et al., 2018b; Soto et al., 2018; Tillotson et al., 2019; Costello et al., 2020; Prakoso et al.,
54 2020).
55
56 Geographical selection of marine farm sites may prevent climate productivity declines (medium confidence)
57 (Froehlich et al., 2018a; Sainz et al., 2019; Oyinlola et al., 2020), particularly for temperaturerelated
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1 mortality hotspots (Garrabou et al., 2019), harmful algal bloom occurrences (Dabbadie et al., 2018) or
2 extreme events (Liu et al., 2020; Wu et al., 2020). However, while downscaled climate forecasts facilitate
3 localized adaptation planning (Falconer et al., 2020a), such projections are rare (Whitney et al., 2020). GIS
4 can be used for climate adaptive planning along with routine site assessments (Falconer et al., 2020b;
5 Galappaththi et al., 2020b; Jayanthi et al., 2020). Building coastal protection, stronger cages and mooring
6 systems, deeper ponds and using sheltered bays can reduce escapees and mortalities related to flooding,
7 increased storms and extreme events (medium confidence) (Dabbadie et al., 2018; Bricknell et al., 2021; Kais
8 and Islam, 2021). Inshore aquaculture in low-lying areas prone to sea-level salinity intrusion (e.g. Mekong
9 delta and Viet Nam) have already implemented adaptation measures, such as conversion of land to mixed
10 plant-animal systems (Nguyen et al., 2019a), converting freshwater ponds to brackish or saline aquaculture
11 (Galappaththi et al., 2020b), building of dams and dykes (Renaud et al., 2015) and intensification of shrimp
12 or fish pond culture to reduce water and land usage (Nguyen et al., 2019b; Johnson et al., 2020). Other
13 adaptation options for limited water supply are government equitable water allocations and water storage
14 (high confidence) (Bunting et al., 2017; Galappaththi et al., 2020b).
15
16 Feed formulations and improved feed conversion can reduce climate-associated stress for freshwater species,
17 significantly reducing waste and increase sustainability (medium confidence) (Chen and Villoria, 2019)
18 (FAO, 2018c; Gasco et al., 2018). Projected decreases in fish meal and global targets of limiting warming to
19 under 2°C may increase the ratio of plant-based diets, but reduce fish nutritional content (see Sections 5.10
20 and 5.13, Hasan and Soto, 2017; Johnson et al., 2020) (). Companies provide insurance in major production
21 areas, but aquaculture is considered high risk with large levels of small claims (Secretan et al., 2007).
22 Insurance covers natural disasters and disease, helping to reduce and cope with climate-induced risk,
23 enabling faster livelihood recoveries and preventing poverty (high agreement, limited evidence) (Xinhua et
24 al., 2017; Kalikoski et al., 2018; Soto et al., 2018). For example, small-scale shrimp farmers were willing to
25 pay higher premiums to manage risk, after participation in government pilot insurance schemes, ensuring
26 greater pay-outs if a mortality event occurred (Nyguyen and Pongthanapanic, 2016; Pongthanapanic et al.,
27 2019). Technological innovations are more widely implemented in larger operations, with internet access
28 promoting adoption at the farm site (Joffre et al., 2017; Salazar et al., 2018). Improved farm management is a
29 key opportunity (high confidence) to reduce climate risks on aquaculture, where Best Management Practices
30 can increase resiliency (Soto et al., 2018), lower additional risk from non-climatic stressors (Gattuso et al.,
31 2018; Smith and Bernard, 2020), and decision-tree frameworks can provide adaptation choices when events
32 occur (Nguyen et al., 2016).
33
34 5.9.4.4 Early warning and monitoring systems
35
36 Globally monitoring is increasing to fill scientific uncertainties (Goldsmith et al., 2019), but is not often at
37 spatial scales which facilitate farm or regional adaptation management (Whitney et al., 2020) or data
38 complexities prevent direct uptake by operators, resource managers and policymakers (medium confidence)
39 (Soto et al., 2018; Gallo et al., 2019). Specialized industry portals (Pacific shellfish) and government-
40 established monitoring programs (Chilean salmon) and other observational networks (e.g., GOA-ON) can
41 provide real-time monitoring, early-warning event alerts and facilitate aquaculture decision-making (medium
42 confidence) (Cross et al., 2019; Farcy et al., 2019; Soto et al., 2019; Bresnahan et al., 2020; Peck et al., 2020)
43 (Tilbrook et al., 2019). Seasonal forecasting, downscaled models and early-warning systems provide
44 valuable regional or farm site risk information (Hobday et al., 2018; Galappaththi et al., 2020b; Whitney et
45 al., 2020), but monitoring will need to be useful for farmers, involve farmers, accurate, timely, cost-effective,
46 reviewed and maintained in order to ensure uptake (high confidence) (Soto et al., 2018). Early warning
47 systems for harmful algal blooms enable rapid decision-making and risk mitigation (medium confidence),
48 e.g., ocean colour monitoring in South Africa (Smith and Bernard, 2020), where early harvesting and
49 additional husbandry were used to minimize production and economic losses (Pitcher et al., 2019). New
50 tools, strategies and observations are needed to predict harmful algal bloom occurrences and range shifts
51 with changing climate (high confidence) (Schaefer et al., 2019; Tester et al., 2020), as there is uncertainty on
52 drivers of incidence and toxicity (Wells et al., 2020).
53
54 5.9.5 Contributions of Indigenous, Traditional, and Local Knowledge
55
56 Indigenous mariculture practices, e.g., intertidal clam gardens, have been occurring for thousands of years,
57 providing knowledge of traditional practices still applicable to mariculture (Deur et al., 2015; Jackley et al.,
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1 2016; Poulain et al., 2018; Bell et al., 2019; Toniello et al., 2019). Indigenous groups differ in opinions on
2 aquaculture acceptability, implications for coastal management and territorial rights (high confidence)
3 (Young et al., 2019). Such perceptions may determine culturally appropriate types and benefits of
4 aquaculture (employment, food diversification, income, building autonomy and skillsets), e.g., Australia
5 (Petheram et al., 2013) and Canada (Young and Liston, 2010). Marginalized people, like small-scale
6 aquaculture farmers in lower-income and lower-middle-income countries, are often overlooked and are not
7 represented at a governance level (Barange et al., 2014; Kalikoski et al., 2018). Therefore policy, economic,
8 knowledge and other support needs to ensure representation with traditional and other stakeholder ecological
9 knowledge at national, regional, and local levels to facilitate climate change adaptation and safeguard human
10 rights for poor and vulnerable groups (high confidence) (Kalikoski et al., 2018; Poulain et al., 2018).
11
12
13 5.10 Mixed Systems
14
15 The food and livelihoods of many rural people depend on combinations of crops, livestock, forestry, and
16 fisheries, and still information on these mixed systems is scarce. Rural households in low and middle-income
17 countries earn almost 70% of their income through mixed production systems (Angelsen et al., 2014). These
18 systems produce about half of the world's cereals, most of the fruits, vegetables, pulses, roots, and tubers,
19 and most of the staple crops and livestock products consumed by poor people in lower-income countries
20 (Herrero et al., 2017). They can help in adapting to climatic risks and reducing GHG emissions by improving
21 nutrient flows and improving the recycling of nutrients within the production system and by increasing food
22 production and diet quality per unit of land and diversifying income sources (Smith et al., 2019c). Indigenous
23 groups often practice mixed production, integrating crops, animals, fisheries, forestry, and agroforestry
24 through traditional ecological knowledge.
25
26 Some evidence exists of the buffering capacity that integrated systems can provide in the face of climate
27 change (Gil et al., 2017). This buffering, often affecting the farming system as a whole rather than the
28 individual agricultural enterprises involved, applies to some aquaculture-agriculture systems as well as to
29 crop-livestock systems (Bunting et al., 2017; Stewart-Koster et al., 2017). In some situations, there may be
30 tradeoffs and constraints at the household level that affect this resilience-conferring ability: for instance,
31 mixed systems often need relatively high levels of management skill, and extra labour may be required (van
32 Keulen and Schiere, 2004; Thornton and Herrero, 2015). The diversification of food production systems
33 offers promise for enhanced resilience at the global level (Kremen and Merenlender, 2018; Dainese et al.,
34 2019; section 5.4.4.4), though policies need to provide adequate incentives for resource efficiency, equity,
35 and environmental protection (Havet et al., 2014; Thornton and Herrero, 2014; Troell et al., 2014).
36
37 5.10.1 Observed Impacts
38
39 5.10.1.1 Mixed crop-livestock systems
40
41 Overall, there is high confidence that farm strategies that integrate mixed crop-livestock systems can improve
42 farm productivity and have positive sustainability outcomes (Havet et al., 2014; Thornton and Herrero, 2014;
43 Herrero et al., 2015; Thornton and Herrero, 2015; HLPE, 2019). The scale of the improvement varies
44 between regions and systems and is moderated by overall demand in specific food products and the policy
45 context. Integrated crop-livestock systems present opportunities for the control of weeds, pests, and diseases.
46 They can also provide a range of environmental benefits, such as increased soil carbon and soil water
47 retention, increased biodiversity, and reduced need for inorganic fertilizers (Havet et al., 2014; Thornton and
48 Herrero, 2014; Herrero et al., 2015; Thornton and Herrero, 2015; HLPE, 2019).
49
50 Research indicates that mixed crop-livestock systems are often more resilient to climate change (medium
51 confidence). In the southern Afar region of Ethiopia, crop-livestock households were more resilient than
52 livestock-only households to climate-induced shock (Mekuyie et al., 2018). However, the benefits of
53 managing crop-livestock interactions in response to climate change depend on local context. For example, in
54 higher-rainfall zones in Australia, Nie et al. (2016) found some yield reductions and difficulty in maintaining
55 groundcover. The systematic review of Gil et al. (2017) concluded that the integration of crop and livestock
56 enterprises as an adaptation measure can enhance resilience (FAQ 5.1).
57
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1 Reconfiguring mixed farming systems is occurring. In semiarid eastern Senegal, Brottem and Brooks (2018)
2 found increasing reliance on livestock production mostly because of changing climate conditions. Many
3 poorer households are having to rely on migration to compensate for shortfalls in crop production arising
4 from a changing climate. Some farmers have successfully shifted to crop-livestock systems in Australia,
5 where they have allocated land and forage resources in response to climate and price trends (Bell et al.,
6 2014).
7
8 Mixed livestock-crop systems may increase burdens on women, require managing competing uses of crop
9 residues, and have higher requirements of capital and management skills. These factors can be challenging in
10 many lower-income countries (Rufino et al., 2013; Thornton and Herrero, 2015; Jost et al., 2016; Thornton,
11 2018). The policy actions needed for the successful operation of mixed crop-livestock systems may be
12 similar across widely different situations: good access to credit inputs and capacity-building needed to
13 facilitate uptake (Hassen et al., 2017; Marcos-Martinez et al., 2017), and good levels of market infrastructure
14 (Ouédraogo et al., 2017; Iiyama et al., 2018).
15
16 5.10.1.2 Mixed crop-aquatic systems
17
18 Households may have a mix of aquatic and land-based food production, contributing to food security and
19 nutrition and income generation (Freed et al., 2020; see also discussion of aquaponics and hydroponics in
20 Section 5.10.4.3. and combined rice-aquatic species production in Section 5.9.4). Failures in agricultural
21 outputs due to climate-associated factors may result in diversification to fisheries as a way of alleviating food
22 production shortfalls; for example, fisheries landings may dramatically increase after agricultural failures
23 following hurricanes, which can subsequently create overfishing collapses (Cottrell et al., 2019). Where
24 climatic impact drivers affect multiple sectors, adaptation may become more difficult because of the
25 interacting challenges (Cottrell et al., 2019). One study of 12 countries with high food insecurity levels found
26 that fish-reliant households utilized as much land as those not reliant on fish (Fisher et al., 2017). To meet
27 food security requirements, most of these households needed to both farm and fish, illustrating the
28 interdependence of aquatic-terrestrial food systems.
29
30 5.10.1.3 Agroforestry systems
31
32 Agroforestry is frequently mentioned as a strategy to adapt to and mitigate climate change and address food
33 security ((de Coninck et al., 2018; Smith et al., 2019c). There is strong evidence of net positive biophysical
34 and socioeconomic effects of agroforestry systems under both smallholder and large-scale mechanized
35 production systems (Quandt et al., 2017; Hoegh-Guldberg et al., 2018; Sida et al., 2018; Wood and Baudron,
36 2018; Table 5.10; Cross-Chapter Box NATURAL in Chapter 2; Quandt et al., 2019). Many of these effects
37 also reduce climate risk. At the same time, agroforestry systems are subject to impacts from climate change,
38 potentially reducing the benefits they provide. Still, there is limited evidence of observed climate impacts on
39 agroforestry systems, and modeling climate impacts is more complex for agroforestry than for single
40 cropping systems (Luedeling et al., 2014).
41
42 5.10.2 Assessing Vulnerabilities
43
44 5.10.2.1 Assessing vulnerability in mixed systems
45
46 Important information gaps exist concerning the costs and benefits of many adaptation options in mixed
47 systems, where the interactions between farming enterprises may be complex. Among communal crop-
48 livestock farmers in Eastern Cape province of South Africa, Bahta (2016) reported high levels of
49 vulnerability to drought and highlighted the need for more coordination between monitoring agencies in
50 terms of reliable early warning information that can be communicated appropriately, between farmers'
51 organizations and the private sector to facilitate adaptation options that can overcome feed shortages such as
52 fodder purchases in times of drought, and between government departments at the national and provincial
53 level that address the concerns and needs of affected communities. Nyamushamba (2017) reviewed the use
54 of indigenous beef cattle breeds in smallholder mixed production systems in southern Africa. Some of these
55 breeds exhibit adaptive traits such as drought and heat tolerance and resistance to tick-borne diseases.
56 However, their adaptation potential in crossbreeding programs is essentially unknown, as most African cattle
57 populations are still largely uncharacterized.
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1
2 5.10.2.2 Social vulnerabilities
3
4 As in other production systems, Indigenous groups, gender, race, and other social categories can result in
5 heightened vulnerability to climate change in mixed production systems due to historical and current
6 marginalization and discrimination (high confidence) (Parraguez-Vergara et al., 2016; Baptiste and
7 Devonish, 2019; Moulton and Machado, 2019; Popke and Rhiney, 2019; Fagundes et al., 2020). A study of
8 the Mapuche Indigenous group in Chile found that marginalization and discrimination worsened their
9 vulnerability and observed impacts of climate change because they had less access to services, lower
10 incomes and were not as high a priority as other groups (Parraguez-Vergara et al., 2016). Among fisherfolk
11 on Lake Wamala, Uganda, Musinguzi (2018) found evidence of considerable diversification to crop and
12 livestock production as a means of increasing households' food security and income, but women had greater
13 workloads and had less control over new income sources than men. Ngigi (2017) evaluated adaptation
14 actions within households in rural Kenya and found that women tended to adopt adaptation strategies related
15 to crops, men to livestock and agroforestry activities. Chingala (2017) found substantial gender- and age-
16 related differences in control of access to animal feed, animal health, and water resources in beef producers
17 in mixed crop-livestock systems in Malawi. In a review of agriculture-aquaculture systems in coastal
18 Bangladesh, Hossain et al. (2018) showed that existing policies and adaptation mechanisms are not
19 adequately addressing gender power imbalances, and women continue to be marginalized, leading to
20 increasing feminization of food insecurity. Such studies highlight the need to consider gender and other
21 social inequities when examining adaptation in mixed production systems, particularly in situations in which
22 men and women have different levels of control over productive assets (Cross-Chapter Box GENDER in
23 Chapter 18).
24
25 5.10.3 Projected Impacts
26
27 The impacts of climate change on risk in mixed farming systems are projected to be dependent on market,
28 ecosystem, and policy context (medium evidence, low agreement). In mixed crop-livestock farms in a
29 semiarid region of Zimbabwe, Descheemaeker (2018) found that feeding forages and grain could alleviate
30 dry-season feed gaps to the 2050s, but their effectiveness depended on the household's livestock stocking
31 density. In comparing different commercial production systems, Tibesigwa (2017) found that under South
32 African conditions, climate change to the 2050s will reduce productivity across the agricultural sector, with
33 the largest impacts occurring in specialized commercial crop farms owing to their relative lack of diversity.
34 Mixed farming systems were the least vulnerable in terms of relative effects on farm output; this applied to
35 commercial and subsistence sectors (Tibesigwa et al., 2017). Other studies suggest increased risk in mixed
36 systems in semiarid conditions. In northern Burkina Faso, Rigolot (2017) examined different crop
37 fertilization and animal supplementation levels under RCP8.5 to the 2050s. They found that although
38 aggregate profits could be increased via moderate levels of inputs, the use of external inputs may increase
39 risk because of marginal costs exceeding marginal benefits in lower rainfall years. In the Western Australian
40 wheat belt, Thamo (2017) assessed climate-change-induced shifts in farm profitability to the 2050s. For most
41 options, the adverse effects on profitability were greater than the advantageous effects, profit margins being
42 much more sensitive to climate change than production levels. However, in the same system Ghahramani
43 (2018) evaluated adaptation options to 2030 and found that a shift to a greater reliance on livestock could be
44 profitable, even in years with low rainfall.
45
46 Risk management in integrated production systems may constitute a barrier to uptake of adaptation options
47 (Rigolot et al., 2017). Watson (2018) highlighted the current lack of financial risk management tools that
48 could be used in smallholder coastal communities. Alongside other risk management tools such as weather-
49 based index insurance, risk pooling may find wide application in different farming systems as an effective
50 adaptation measure (medium agreement, limited evidence) (Hansen et al., 2019a).
51
52 Climate change impacts on productivity of agroforestry systems are similar to individual perennial crops,
53 although there is limited research on tree crops (see section 5.4.1.2). Impacts include increased temperature
54 or water stress, an increase in pathogens affecting crops, changes to pollinator abundance, and changes in the
55 nutrient content of one or more of the agroforestry components. Many tree products such as fruits and nuts
56 are grown in agroforestry settings. The quality and nutrition of these products and other specialty crops are
57 often negatively affected by rising temperatures, ambient CO2 concentrations, and tropospheric ozone
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1 (Ahmed and Stepp, 2016). There is also evidence that the fungus coffee rust will be positively affected by
2 climate change (Avelino et al., 2015; Bebber et al., 2016), with adverse effects on coffee agroforestry
3 systems.
4
5 While shade trees can ameliorate increasing stand temperatures that will significantly impact arabica coffee
6 (Ovalle-Rivera et al., 2015; Schroth et al., 2015), the opposite can also be true. Comparing shade and full-sun
7 coffee systems in Ghana, Abdulai (2018) concluded that the leguminous tree species providing shade and
8 additional nitrogen led to soil water competition with the coffee trees during severe drought, resulting in
9 enhanced coffee mortality. On the other hand, experimentally induced drought in a soybean-intercropping
10 agroforestry system in eastern Canada led to crop losses in the monocropping system only, whereas N-
11 fixation declined in both systems (Nasielski et al., 2015). Thus, balancing the synergies and tradeoffs of
12 multiple component systems is necessary based on local context. While species diversification can enhance
13 resilience to climate shocks, lack of water can constrain the implementation of agroforestry practices in arid
14 locations (Apuri et al., 2018).
15
16 For people reliant on both agriculture and fisheries for food production, regional differences in productivity
17 effects of climate change are expected; populations in LMICs that are already vulnerable will be most
18 affected by simultaneous reductions in fisheries and agricultural productivity (Blanchard et al., 2017).
19 Twelve out of 17 high-income countries in Europe showed projected increases in agricultural production
20 where adaptive capacity is higher, and agricultural and food fisheries' dependence were lower. Some LMIC
21 countries (Nigeria, Cameroon, Ghana, and Gabon) showed relative reductions in both fisheries and
22 agricultural production, where food insecurity, human population growth, and fisheries overexploitation rates
23 are high (Blanchard et al., 2017). Model projections under the RCP6.0 scenario show decrease in marine and
24 terrestrial production to 2050 in 87 out of the 119 coastal countries studied, even though there is a wide
25 variance in adaptive capacity and relative and combined dependencies on fisheries and agriculture
26 (Blanchard et al., 2017). A projected 2050 move towards greater consumption of cultured seafood and less
27 meat showed that aquaculture requires less feed crops and land, but was regionally dependent upon differing
28 patterns of production, trade, and feed composition (Froehlich et al., 2018b).
29
30
31 [START BOX 5.7 HERE]
32
33 Box 5.7: Perspectives of crop and livestock farmers on observed changes in climate in the Sahel
34
35 The Sahel region of West Africa has experienced some of the most severe multi-decadal rainfall variations in
36 the world: excessive rainfall in the 1950s1960s followed by two decades of deficient rainfall, leading to a
37 large negative trend until the mid-to-late 1980s with a decrease in annual rainfall of between 20 and 30%.
38 Recently, there has been a partial recovery of annual rainfall amounts, more significant over the central than
39 the western Sahel. This recovery is characterized by new rainfall features including false starts and early
40 cessation of rainy seasons, increased frequency of rainy days, increased precipitation intensity, and more
41 frequent and longer dry spells (Salack et al., 2015; Sanogo et al., 2015; Salack et al., 2016; Biasutti, 2019).
42 The Sahel is experiencing a new era of rainfall extremes (Bichet and Diedhiou, 2018; Panthou et al., 2018),
43 suggesting an intensification of the hydrological cycle (Doblas-Reyes et al., 2021).
44
45 The ways in which crop and livestock farmers in the Sahel have responded to climatic variability have been
46 studied widely (Sissoko, 2011; Gonzalez et al., 2012; Jalloh et al., 2013; Gautier et al., 2016; Sultan and
47 Gaetani, 2016; Zougmoré et al., 2016; Segnon, 2019). Local communities have developed an extensive
48 Indigenous ecological knowledge system, enabling them to make use of ecosystem services to support their
49 livelihoods and to survive environmental change (Nyong et al., 2007; Mertz et al., 2009; Lahmar et al., 2012;
50 Segnon et al., 2015). These knowledge systems have been crucial in people's resilience to and recovery from
51 major environmental change, such as the severe drought period experienced in the region in the 1970s and
52 1980s (Nyong et al., 2007; Lahmar et al., 2012; Segnon et al., 2015; Gautier et al., 2016; Zouré et al., 2019).
53 As climate change became evident and a primary concern on the global agenda, interest in local people's
54 knowledge and understanding of climate change has also increased (Mertz et al., 2009; Tambo and
55 Abdoulaye, 2013; Traore et al., 2015; Kosmowski et al., 2016; Sanogo et al., 2017; Segnon, 2019).
56
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1 There is no simple understanding of crop and livestock farmers' response in the Sahel to rainfall variability.
2 Nielsen and Reenberg (2010) developed human-environment timelines for the period 1950-2008 for a small
3 village in northern Burkina Faso, relating livelihood diversification and crop-livestock management changes
4 that map closely to local rainfall variability, such as fields abandoned in dry years and intense animal manure
5 use in wet years. Although they found a significant correlation between crop-livestock management practice
6 changes and major climatic events, the climate is only one of many interacting factors that influence local
7 adaptation strategies (Mortimore, 2010; Nielsen and Reenberg, 2010; Sendzimir et al., 2011). Robust
8 attribution of observed changes to specific change drivers remains a challenge.
9
10 Crop and livestock farmers' knowledge and perceptions of increases in temperature and temperature-related
11 stressors (heat waves, number of extreme hot or cold days) are consistent with the observed meteorological
12 data (Mertz et al., 2009; Mertz, 2012; Tambo and Abdoulaye, 2013; Traore et al., 2015; Sanogo et al., 2017;
13 Segnon, 2019). Their perceptions of changes in rainfall amounts have not always been consistent with the
14 observational record (Mertz, 2012; Segnon, 2019). Nevertheless, their perception of increases in dry spell
15 occurrence during the rainy season and changes in rainfall pattern (onset, cessation, rainfall intensity, and
16 distribution) were consistent with the recent observations (Barbier et al., 2009; Ouédraogo et al., 2010;
17 Tambo and Abdoulaye, 2013; Salack et al., 2015; Traore et al., 2015; Kosmowski et al., 2016; Salack et al.,
18 2016; Segnon, 2019). Rainfall patterns within the season, rather than the total amounts of rainfall, matter
19 more for crop and livestock farmers in the Sahel (Segnon, 2019).
20
21 Crop and livestock farmers in the Sahel have a sophisticated understanding of the local climate. There is
22 considerable potential to harness this knowledge, coupled with an enabling institutional environment, in
23 developing policies and adaptation plans (Rasmussen et al., 2018); the Sahel is a region where
24 meteorological stations and observed data are scarce (Buytaert et al., 2012; Nkiaka et al., 2017). A deeper
25 understanding of the resilience of local ecological knowledge systems, in light of the hydro-climatic
26 intensification currently experienced in the region and future changes, may well provide further insights into
27 their long-term effectiveness.
28
29 [END BOX 5.7 HERE]
30
31
32 5.10.4 Adaptation Strategies
33
34 5.10.4.1 Increasing integration and diversity within mixed systems
35
36 There is medium confidence in the effectiveness of changing the nature of the integration between crops and
37 livestock as an adaptation: moving from crops to livestock, moving from livestock to crops, and moving
38 from one species of livestock to others, for example (Roy et al., 2018). Such transitions that increase
39 integration between farm enterprises may contribute to risk reduction and increased food security. In areas
40 with adequate rainfall and relatively limited rainfall variability under climate change, where agricultural
41 diversity is the greatest, transitions towards more diverse and integrated systems may bring substantial
42 adaptation benefits (Waha et al., 2018).
43
44 Barriers to increasing integration and diversification include policies which support cereals and crop
45 specialization, lack of markets, limited post-harvest processing, limited technical or biophysical research on
46 implementation and poor market infrastructure (Keatinge et al., 2015; Bodin et al., 2016; Garibaldi et al.,
47 2016; Bassett and Koné, 2017; Kongsager, 2017; Rhiney et al., 2018; Roesch-McNally et al., 2018; Clay and
48 King, 2019; Ickowitz et al., 2019). Proactive policy and market development are needed to reduce these
49 barriers (Clay and King, 2019; Ickowitz et al., 2019; See 5.14.3.8 for Insurance).
50
51 5.10.4.2 Agroforestry as an adaptationmitigation strategy for mixed systems
52
53 Agroforestry, the purposeful integration of trees or shrubs with crop or livestock systems, increases
54 resilience against climate risks through a range of biophysical and economic effects (high confidence).
55 Traditional agroforestry has been practiced for millennia and provides prime examples of sustainable
56 agroecological production systems meeting the production, income, and socio-cultural needs of farming
57 communities within their ecological niches, but market forces have often led to their demise (McNeely and
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1 Schroth, 2006; Plieninger and Schaar, 2008; García-Martínez et al., 2016; Krcmáová and Jelecek, 2016;
2 Coq-Huelva et al., 2017; Paudel et al., 2017; Doddabasawa et al., 2018; Maezumi et al., 2018; Lincoln,
3 2020). The wide range of options to associate different trees with crops, livestock and aquaculture allow
4 agroforestry to be practiced in most regions, including those with precipitation regimes ranging from
5 semiarid to humid. While most agroforestry systems occur in smallholder settings, there are examples of
6 successful industrial-scale mechanized agroforestry systems (Feliciano et al., 2018; Lovell et al., 2018).
7 Agroforestry delivers medium to large benefits to all five land challenges described in the SRCCL - climate
8 change mitigation, adaptation, desertification, land degradation, and food security - and is considered to have
9 broad adaptation and moderate mitigation potential compared with other land challenges (Smith et al.,
10 2019c). Agroforestry is also able to deliver multiple biophysical and socioeconomic benefits (Table 5.12).
11
12
13 Table 5.12: Some of the biophysical and socioeconomic benefits of agroforestry.
Contribution Pathway References
Increased food security Diversification of production, avoiding Nath et al. (2016), Coulibaly et
and household income tradeoffs between crop and tree products al. (2017), Montagnini and
Metzel (2017), Waldron et al.
(2017), Blaser et al. (2018),
Sida et al. (2018), Quandt et al.
(2019), Amadou et al. (2020)
Increased productivity Introduction of multiple species leading to van Noordwijk et al. (2018),
per unit of land higher land equivalency ratios Reppin et al. (2019)
Improved biophysical Via limiting soil erosion, facilitating water Nguyen et al. (2013); Carsan et
site properties infiltration, increasing nutrient use efficiency, al. (2014), Rosenstock et al.
improving soil physical properties, improving (2014), Quandt et al. (2017),
crop nutritional quality, modifying the site Hoegh-Guldberg et al. (2018),
micro-climate, and helping to buffer against Sida et al. (2018), Wood and
extreme events Baudron (2018), de Leeuw et
al. (2020), Muchane et al.
(2020), Nyberg et al. (2020)
Enhanced biodiversity Via integrating different perennial and annual McNeely and Schroth (2006),
and supporting species in different spatial or temporal Imbach et al. (2017), Isbell et
ecosystem services associations, thereby providing greater habitat al. (2017), Sonwa et al.
diversity for other species, including (2017b),
pollinators and predators Tran and Brown (2019)
Enhanced cultural Enhanced recreational, cultural and spiritual Nyberg et al. (2020)
ecosystem services uses
Carbon dioxide removal Via enhanced above-ground carbon Ramachandran Nair et al.
sequestration compared with most cropping or (2009), Zomer et al. (2016),
livestock systems, ranging from 2.6 -10 Mg C Rochedo et al. (2018), Wolz et
ha-1 yr-1 depending on regional and climatic al. (2018), Crous-Duran et al.
conditions (> 0.7 Gt CO2e yr-1 globally (2019), Platis et al. (2019)
between 2000 and 2010)
Enhanced gender balance Via providing women with more diversified Kiptot et al. (2014), Ngigi et al.
income sources (2017), Benjamin et al. (2018)
Strengthened urban & Via provision of regulating and provisioning Borelli et al. (2017)
peri-urban agricultural ecosystem services such as shade, water See Section 5.12
systems infiltration, new food and livelihood
opportunities
14
15
16 The adoption and maintenance of agroforestry practices require appropriate incentives or the removal of
17 barriers (high confidence). Agroforestry adoption has been limited to date in both higher-income and lower-
18 income countries. Several constraints need to be carefully addressed for successful scaling up of agroforestry
19 systems, including costs of establishment, limited short-term benefits, lack of reliable financial support to
20 incentivize longer-term returns on investments, land tenure, knowledge of and experience with trees and the
21 management of multiple component systems, and inadequate market access, (Coulibaly et al., 2017; Iiyama
22 et al., 2017; Jacobi et al., 2017; Kongsager, 2017; Hernández-Morcillo et al., 2018; Iiyama et al., 2018;
23 Lincoln, 2019). Kongsager (2017) Roupsard et al. (2020) also highlight the need for vertical integration of
24 measures from local to national scales to successfully address local barriers to adoption. Although there are
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1 few studies evaluating the long-term performance of agroforestry systems (Coe et al., 2014; Meijer et al.,
2 2015; Brockington et al., 2016; Kongsager, 2017; Toth et al., 2017), the available results suggest that
3 successful adoption of agroforestry practices depends strongly on the local enabling environment, including
4 appropriate markets, technologies, and delivery systems (medium evidence, high agreement).
5
6 5.10.4.3 Links between crops and aquaponics-hydroponics as adaptation
7
8 Hydroponic systems produce plants in a soilless environment requiring mineral fertilizers to meet plant
9 nutritional needs, whereas aquaponics combines an aquaculture production system with hydroponics, where
10 fish waste provides nitrogen, phosphorous, and potassium for plant growth and nitrifying and mineralizing
11 bacteria act as filters (Goddek et al., 2015; Pérez-Urrestarazu et al., 2019; Ghamkhar et al., 2020). The
12 relative environmental impact of hydroponic systems is lower compared with conventional systems owing to
13 the significant reductions in land use and fertilizer usage (high confidence) (Goddek et al., 2015; Datta et al.,
14 2018; Pantanella, 2018; Suhl et al., 2018; El-Essawy et al., 2019; Jaeger et al., 2019; Monsees et al., 2019;
15 Mupambwa et al., 2019; Pérez-Urrestarazu et al., 2019; Ghamkhar et al., 2020). While studies indicate that
16 aquaponics and hydroponics have higher yields and a lower environmental footprint than conventional
17 agriculture (medium confidence), aquaculture and heated greenhouse production (Pantanella, 2018; Romeo et
18 al., 2018), aquaponic production may need to be coupled, decoupled, or have double-recirculation systems to
19 meet the different requirements of farmed fish and crop species (Pantanella, 2018; Suhl et al., 2018;
20 Mupambwa et al., 2019). Aquaponics and hydroponics are a promising adaptation option for urban
21 agriculture, benefits including a protected growing environment from climate extremes, reduced GHG
22 emissions related to food transportation, reduced food waste, rainwater harvesting and use of food waste
23 (medium agreement, limited evidence) (Goddek et al., 2015; Al-Kodmany, 2018; Clinton et al., 2018;
24 Weidner and Yang, 2020). Such systems show promise for reducing food production environmental
25 footprints and increasing food security, particularly in arid or water-stressed environments (Doyle et al.,
26 2018; Mupambwa et al., 2019). Barriers to aquaponics and hydroponics adoption include market acceptance
27 of cultured fish species and desirability of plant crops, lack of expertise, legal constraints or high investment
28 costs and financial feasibility (Bosma et al., 2017; Al-Kodmany, 2018; Datta et al., 2018; Pantanella, 2018;
29 El-Essawy et al., 2019; Martin and Molin, 2019; Pérez-Urrestarazu et al., 2019; Specht et al., 2019). There is
30 high confidence (high agreement, medium evidence) that a major barrier to hydroponic and aquaponics
31 adoption is the requirement for skilled operators (Goddek et al., 2015; Bosma et al., 2017; Datta et al., 2018;
32 McHunu et al., 2018; Pantanella, 2018), which could be mitigated by decoupling systems and disciplines
33 (Pantanella, 2018). As yet, these systems are not widely implemented and information on their climate
34 change impacts is limited.
35
36 5.10.4.4 Transitions in and between mixed systems as adaptation strategy
37
38 Transitions in and between the different elements of integrated agricultural systems can be an effective
39 adaptation option (medium confidence). Havlik et al. (2014) projected that by 2030 market-driven
40 autonomous transitions toward more efficient production systems would increase ruminant meat and milk
41 productivity by up to 20% and decrease emissions by 736 MtCO2e·y-1, most of this arising through avoided
42 emissions from the conversion of 162 Mha of natural land. Weindl et al. (2015) assessed the implications of
43 several climate projections on land use change to 2045 and found that shifts in livestock production towards
44 mixed crop-livestock systems would represent a resource- and cost-efficient adaptation option, reducing
45 global agricultural adaptation costs and abating deforestation by about 76 million ha globally. Both studies
46 suggest that public policy support for transitioning livestock production systems to increase their efficiency
47 could be an important lever for reducing adaptation costs and contributing to emissions reductions. This
48 policy support could include modified regulatory and certification frameworks that incentivise livestock
49 producers to adapt and mitigate (Weindl et al., 2015).
50
51 Recent reviews have summarised literature on production system transitions, driven at least partly by a
52 changing climate or changing climate variability, that sometimes involves substantial shifts in enterprises
53 and land configurations. These reviews found several cases of transitions affecting pastoral and mixed
54 systems, with a range of responses including intensification, diversification, sedentarisation, as well as the
55 abandonment of agriculture ( see section 5.14.3.1, Vermeulen et al., 2018; Thornton et al., 2019). The
56 consequences of these system transitions have been mixed; in some cases, the household level outcomes
57 have been beneficial, while in others not. Policy environments, defined in terms of multi-level governance
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1 structures and institutions, are critical enablers of change. The vulnerability of many crop-livestock keepers
2 to climate change is particularly affected by property and grazing rights (high confidence). Identifying the
3 winners and losers from changes in land ownership and the use of communal lands in the coming decades is
4 a key challenge for the research agenda, particularly as climate change impacts in the marginal lands
5 intensify (Reid et al., 2014).
6
7
8 [START BOX 5.8 HERE]
9
10 Box 5.8: Climate Adaptation and Maladaptation in Cocoa and Coffee Production
11
12 Coffee and cocoa are important crops in low latitude regions where agriculture is projected to be heavily
13 impacted by climate change. Both crops are at risk from climate change impacts by 2050 (Baca et al., 2014;
14 Ovalle-Rivera et al., 2015; Chemura et al., 2016; Schroth et al., 2016; Bacon et al., 2017; Schreyer et al.,
15 2018; de Sousa et al., 2019; Lahive et al., 2019; Pham et al., 2019; Cilas and Bastide, 2020). Chocolate and
16 coffee are notable among foods in that their carbon footprint ranges from negative to high, as these industries
17 include both low-input agroforestry systems that have many co-benefits, and high-input monoculture systems
18 where crops are grown without shade, in some cases on sites that have been deforested (Poore and Nemecek,
19 2019). While the coffee industry in many countries has already transitioned from agroforestry to a full-sun
20 production (Jha et al., 2014), the cocoa industry is at a turning point with many growers deciding whether to
21 move to the potentially more productive `full-sun system', despite a general view that the agroforestry
22 system is more resilient to climate change impacts (Rajab et al., 2016; Schroth et al., 2016; Farrell et al.,
23 2018; Niether et al., 2020).
24
25 Shade-grown cocoa and coffee agroforestry systems provide an array of ecosystem services, including
26 regulating pests and diseases, maintaining soil fertility, maintaining biodiversity and carbon sequestration
27 (high confidence) (Jha et al., 2014; Rajab et al., 2016; Cerda et al., 2017; Pham et al., 2019). For example, a
28 comparison of Indonesian cocoa stands found that total carbon stocks above and below ground were five
29 times higher in multi-shade agroforestry stands compared to monoculture stands (57 compared to 11 Mg C
30 ha-1) and total net primary production was twice as high (18 compared to 9 Mg C ha-1 yr-1). The extra carbon
31 sequestration was achieved without any notable difference in cocoa yield (Rajab et al., 2016). At higher
32 levels of shade there can be negative impacts on the yield of the understory crop, but careful management of
33 shade trees allows for both crops to thrive (Andreotti et al., 2018; Blaser et al., 2018; Niether et al., 2020).
34
35 Cocoa grown under shade in some situations may be more resilient to climate change (Schwendenmann et
36 al., 2010; Schroth et al., 2016). Schwendenmann et al. (2010) implemented drought experimentally in the
37 field and found shade trees increased drought resilience. Shade trees insulate the understory crop from the
38 warming and drying sun (Schroth et al., 2016). On the other hand, full-sun cocoa systems may be more
39 climate resilient in some cases (Abdulai et al., 2018), as interactions between understory trees and shade
40 trees are complex; in addition to shade effects, evapotranspiration and root interactions must be considered
41 (Niether et al., 2017; Wartenberg et al., 2020). Moving to a full-sun system may also involve additional
42 inputs in irrigation, fertiliser, and labour. Neither (2020) reviewed the literature comparing the two cocoa
43 production systems and concluded that the agroforestry system was superior in terms of climate adaptation.
44
45 The choice of cropping-system will have wide-reaching consequences for climate vulnerability and climate
46 justice. Coffee and cocoa are often a main source of income for small-scale producers who are among the
47 most vulnerable to climate hazards (Bacon et al., 2014; Schroth et al., 2016). Most of their produce is
48 exported by large corporations and sold to relatively better-off consumers. In the context of climate justice,
49 underlying structural inequalities (socioeconomic, ethnicity, gender, caste), marginality, and poverty help to
50 shape the vulnerabilities of small-scale farmers to climate hazards (Beckford and Rhiney, 2016; Schreyer et
51 al., 2018). Climate change may compound their vulnerability, if for example the loss of pollination services
52 leads to a reduction in productivity (Avelino et al., 2015). Adaptation needs to consider the inequalities
53 associated with the commodity chain, and the adaptative capacity of producers as they seek to move into the
54 more advanced processing stages of the commodity chain to realize higher returns from their exports
55 (Ovalle-Rivera et al., 2015). Blue Mountain Coffee is a 'specialty' coffee associated with a Protected Area
56 forest ecosystem that attracts a high price premium owing to its distinct flavour and aroma. The livelihoods
57 of coffee farmers in this region are characterized by multiple socioeconomic, environmental, and institutional
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1 stressors related to climate change, pests, plant diseases and production costs. Some coping strategies
2 employed by these coffee farmers have increased their susceptibility to future climate impacts (Guido et al.,
3 2019). Davis (2017) showed that these coffee farmers' food security challenges could be alleviated by
4 improved marketing of fruit tree products under shade coffee farming systems. Adaptation measures in such
5 systems need to consider co-benefits and negative trade-offs, especially in vulnerable communities, to avoid
6 widening further the inequalities, rural livelihood loss, migration, and marginalisation, and ensure progress
7 towards the SDGs (high confidence).
8
9 [END BOX 5.8 HERE]
10
11
12 5.11 The Supply Chain from Postharvest to Food
13
14 The food system is more than just the production of food. It includes domestic and international
15 transportation, storage, processing, market infrastructure and institutions that make up value chains, as well
16 as the food environment in which consumers make food purchasing decisions (HLPE, 2017a). Climate
17 change impacts along the value chain alter availability, access, and stability of food security. Nutrition-dense
18 foods tend to be more perishable and are thus more vulnerable to limitations of food storage and
19 transportation infrastructure (Ickowitz et al., 2019). Climate-change-related damage to food in storage (e.g.,
20 electricity failures and loss of cold storage) and transportation infrastructure (e.g., extreme weather events
21 damaging roads and other infrastructure) could significantly decrease availability and increase the cost of
22 highly perishable, nutritious foods such as fruits, vegetables, fish, meat, and dairy.
23
24 This discussion of the postharvest food system (i.e., after production or catch) focuses on three key
25 elements food safety, storage, and domestic and international transactions that could see significant
26 climate change impacts, either directly or indirectly. Higher temperatures and humidity can increase post
27 harvest loss from pests and diseases, increase occurrence of food borne diseases and contamination, and raise
28 the cost of refrigeration and other forms of preservation. Extreme weather events can cause disruptions to
29 food transport networks and storage infrastructure. Changes in regional weather can cause production centres
30 to shift locations, potentially requiring changes in storage and processing locations. Prices to producers and
31 consumers will change although directions and magnitudes are determined by local conditions and policies.
32
33 Food loss is the harvest not used by industry or for food. Food waste is the subset of food loss that is
34 potentially recoverable for food use. As a product moves in the postharvest chain to end users, post-harvest
35 food loss from climate change can occur from improper handling to damage from microorganisms, insects,
36 rodents, or birds. Post-harvest losses in quality can be the result of stresses and damage to a plant or animal
37 before harvest, including from climate change (Hodges et al., 2011; Medina et al., 2015a). Food waste
38 caused by climate change may occur at both retail units and homes because fresh ingredients and freshly
39 prepared foods are vulnerable to quality reduction and spoilage from exposure to higher temperatures and
40 humidity. Food waste also contributes to climate change by utilizing resources that emit GHGs (Galford et
41 al., 2020).
42
43 5.11.1 Current and Future Climate Change Impacts on Food Safety
44
45 Emerging food safety risks from climate change include those posed by toxigenic fungi, plant and marine
46 based bacterial pathogens, harmful algal blooms (HABs), increased use of chemicals (plant protection
47 products, veterinary drugs) potentially leaving residues in food (European Food Safety Authority Panel on
48 Plant Protection Products and their Residues et al., 2017; Deeb et al., 2018; Mbow et al., 2019; FAO et al.,
49 2020).
50
51 Mycotoxins, produced by toxigenic fungi found on many crops, contaminate food and feed and cause a wide
52 range of adverse impacts to human and animal health. Climate change can affect the growth and
53 geographical expansion of these fungi (high confidence) (Wild et al., 2015; Battilani, 2016; FAO and WHO,
54 2016; Watson et al., 2016b; Alshannaq and Yu, 2017; Chen et al., 2018a; Avery et al., 2019; Milicevic et al.,
55 2019; Van der Fels-Klerx et al., 2019; FAO, 2020a; FAO et al., 2020).
56
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1 Aspergillus flavus is a fungus that infects a range of crops and can reduce grain quality. Several strains also
2 produce aflatoxin, a particularly problematic mycotoxin. Increasing CO2 and drought stress has little effect
3 on growth of Aspergillus but significantly increases the production of aflatoxin (Medina et al., 2015b).
4 In Europe one estimate is that the risk of aflatoxin contamination will increase in maize in a + 2°C
5 temperature scenario in Europe with nearly 40% of Europe exceeding the current legal limits (Battilani and
6 Toscano, 2016). In Malawi, maize aflatoxin levels above EU legal thresholds are possible for most of the
7 country by mid-21st century (Warnatzsch and Reay, 2020). The occurrence of toxin-producing fungi will
8 increase and expand from tropical and subtropical areas into new regions and where appropriate capacity for
9 surveillance and risk management is lacking (medium confidence) (Miller, 2016). The increase in toxigenic
10 fungi in crops, and consequent contamination of staple foods with mycotoxins, will increase the risks of
11 human and animal exposure (high confidence) (Botana and Sainz, 2015; Rose and Wu, 2015; Battilani, 2016;
12 Avery et al., 2019; Bosch et al., 2019; Milicevic et al., 2019; Moretti et al., 2019; Van der Fels-Klerx et al.,
13 2019; FAO, 2020a).
14
15 In aquatic systems, mycotoxins produced by Vibrio during HABs also cause food safety problems (high
16 confidence) (Botana, 2016; Estevez et al., 2019; section 5.8). Increased poleward expansion of Vibrios in
17 coastal mid- to high-latitude areas has been observed (Baker-Austin et al., 2017). Vibrio-related mortalities
18 from finfish consumption are expected to rise with climate change (water temperature, salinity, oxygen and
19 pH) (medium confidence) (Mohamad et al., 2019a; Mohamad et al., 2019b). For shellfish species oxygen
20 deficits (Mohamad et al., 2019b), sea-level rise (Deeb et al., 2018) and temperature (Green et al., 2019) will
21 be most important for food safety.
22
23 Food safety is also anticipated to worsen from increased contaminant bioaccumulation under climate-
24 induced warming (high confidence) (Sections 3.5.8, 3.5.9, 5.8, 5.9, Bindoff et al., 2019;), with changes in
25 pathogen, parasite, fungi and virus abundance and virulence (Bondad-Reantaso et al., 2018). Coastal
26 communities who depend on fisheries for livelihoods and nutrition are especially vulnerable (Hilmi et al.,
27 2014; Golden et al., 2016; Bindoff et al., 2019).
28
29 Occurrence of bacterial pathogens such as Salmonella and Campylobacter will increase with rising
30 temperatures (high confidence). Foodborne pathogen risks will increase through multiple mechanisms,
31 though in general the impacts of climate change on different pathogens are uncertain (Akil et al., 2014;
32 Hellberg and Chu, 2016; Lake and Barker, 2018). Even species within a genus can be affected differently.
33 For example, higher CO2 levels depress the growth rate of F. graminearum, an economically important
34 pathogen on barley but have little effect on F. verticillioides, which is the most reported fungal species
35 infecting maize.
36
37 Increases in rainfall intensity will have some effect on the transport of heavy metals by enhancing run-off
38 from soil and increasing the leaching of heavy metals into water systems with magnitudes dependent on local
39 conditions (high confidence) (Joris et al., 2014; Wijngaard et al., 2017). Methyl mercury (MeHg) is highly
40 neurotoxic and nephrotoxic and bioaccumulates and biomagnifies through the food web via dietary uptake
41 (fish, seafood, mammals) (Fort et al., 2016). Ocean warming facilitates methylation of mercury, and the
42 subsequent uptake of methyl mercury in fish and mammals has been found to increase by 35% for each 1°C
43 rise in water temperature (Booth and Zeller, 2005; FAO, 2020a). A changing climate will release mercury
44 from snow and ice, raising the amount of mercury in aquatic ecosystems although its importance relative to
45 industrial sources is unknown (Morrissey et al., 2005).
46
47 Increased frequency of inland floods has been associated with contamination of food with toxic and fat-
48 soluble persistent organic pollutants (POPS), polychlorinated biphenyls (PCBs) and dioxins (Lake et al.,
49 2014; Tirado, 2015; Alava et al., 2017). Exposure to POPs can lead to serious health effects including certain
50 cancers, birth defects, and impairments to the immune, reproductive, and neurological systems.
51
52 Climate changecontaminant interactions may alter the bioaccumulation and biomagnification of POPs and
53 PCBs as well as (MeHg) (Alava et al., 2017). Of particular concern is the pollution risk influenced by
54 climate change in Arctic ecosystems and because of the bioamplification of POPs and MeHg in seafoods
55 resulting in long-term contamination of traditional foods in Indigenous communities (Tirado, 2015; Alava et
56 al., 2017).
57
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1 The high risk associated with emerging zoonoses (animal diseases that can infect humans) and alterations in
2 the distribution, survival and transmission of vectors and associated pathogens and parasites, could lead to an
3 increased use of veterinary drugs and more rapid development of microbial resistance (European Food
4 Safety Authority et al., 2020; FAO, 2020a) and higher veterinary drug residues in food of animal origin,
5 potentially posing health issues for humans (Beyene et al., 2015; FAO et al., 2018; European Food Safety
6 Authority et al., 2020). These outcomes will depend, at least in part, on the extent of changes in current
7 regulatory systems for veterinary drugs. Preharvest stress on animals can increase the contamination of meat
8 products with zoonoses. Climate change may also increase rodent populations and rodent-born zoonoses
9 (Naicker, 2011). Extreme weather events that cause flooding, such as hurricanes or extreme rain events,
10 increase the chance of inundating areas that contain waste from animal farms where antibiotics are used for
11 production, increasing the spread of antibiotic-resistant bacteria into the surrounding environment (FAO,
12 2020a).
13
14 5.11.2 Current and Future Climate Change Impacts on Food Loss in Storage, Distribution and
15 Processing
16
17 The potential for climate-change-based food losses exists in all parts of the food system post-harvest
18 storage, distribution, and processing with the potential for impacts in one part of the system to be passed on
19 to other elements (Davis et al., 2021). Storing a product destined for food use makes it available in times
20 other than immediately after harvest, especially important for products with a pronounced seasonal
21 availability or are not available from other regions with different seasons. Storage of fresh products (meat,
22 fish, fruits, and vegetables) even with the best cold storage technology results in some quality loss relatively
23 quickly. Higher temperatures increase the cost of maintaining quality. One estimate is that an increase in
24 outdoor temperature from 17°C to 25°C increases cold storage power consumption by about 11% (James and
25 James, 2010). Postharvest storage of roots and cereals is subject to physical and quality losses from damage
26 by mice, rats, and birds and by microorganisms such as the toxigenic fungi discussed above, all of which are
27 expected to increase in warmer and more humid conditions.
28
29 The higher temperatures and humidity will generally raise storage costs and lower the quantity and quality of
30 stored product, reducing producer incomes and raising consumer prices (high agreement, medium evidence)
31 (Mbow et al., 2019). For example, in the US state of Michigan, climate change will shorten the period of
32 reliably cold local storage of potato by 11-17 days and 1420 days further south by mid-century and by 15
33 29 days and 3135 days, respectively by late century. These changes would increase future demand for
34 ventilation and/or refrigeration immediately after harvest and again in spring and early summer (Winkler et
35 al., 2018).
36
37 Insects are a main source of food loss. Climate change can alter insect damage in at least two ways
38 increases in reproductive rate from temperature increases and changes in pheromone effectiveness (high
39 confidence). Increasing temperature up to about 40°C raises the rates of insect food digestion and
40 reproduction (Deutsch et al., 2018), but temperatures above that level are fatal for many insects (Neven,
41 2000). Most insects rely on pheromones to facilitate reproduction. Higher temperatures, but also increases in
42 atmospheric CO2 and O3 levels, can affect this process. Insect species that rely on long-range chemical signals
43 (such as ladybirds, aphids, bark beetles and fruit flies) will be most impacted, because these signals suffer
44 from longer exposure to processes that reduce pheromone effectiveness (Medina et al., 2015b; Moses et al.,
45 2015; Boullis et al., 2016; Verheecke-Vaessen et al., 2019).
46
47 There are several potential pathways for climate change impacts on processing that would negatively affect
48 quality and appearance, but with limited research to date. For example, some studies have indicated that
49 recent increases in temperature have decreased the appearance and milling quality of rice in the US and East
50 Asia, owing to increased occurrence of chalky grains (Lyman et al., 2013; Morita et al., 2016; Masutomi et
51 al., 2019; Ishigooka et al., 2021). Impacts on quality of perennial crops and annual fruits and vegetables are
52 discussed above (Section 5.4.3 and Box 5.2).
53
54 5.11.3 Current and Projected Impacts on Transportation and Distribution: Domestic and International
55 Trade
56
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1 Regional differences in resource availability are a key underlying driver of domestic and international trade.
2 Climate change can change resource availability, both in quantity and quality terms, altering trade flows,
3 prices, and incomes of producers. Climate change can also affect food access and its stability can be affected
4 through climate change driven disruption of infrastructure (FAO et al., 2018; Mbow et al., 2019). Extreme
5 events are expected to become more common as climate change progresses. Recent examples illustrate the
6 potential for trade disruptions. In March 2019, Cyclone Idai affected 1.7 million people in Mozambique and
7 920,000 in neighbouring Malawi, according to UN officials. The World Food Program reported that satellite
8 imagery of flooding in central Mozambique showed an `inland ocean' the size of Luxembourg with
9 potentially large impacts on distribution of existing supplies, and uncertain effects on future food production
10 and availability. The extreme rainfall events in the US state of Iowa in spring 2019 destroyed large numbers
11 of well-built grain silos. In addition, major road and bridge damage required rebuilding.
12
13 Trade plays a sizeable role in global food supplies. More than 1 billion people relied on international food
14 trade in the early 21st century (Fader et al., 2013; Pradhan, 2014). Domestic and international trade flows can
15 be dramatically affected by climate change impacts (medium evidence, high confidence) (Nelson et al., 2014;
16 Pradhan, 2014; Wiebe et al., 2015). Since the impacts of climate change will not be uniform, profitable
17 locations for exports production will change. In addition, the effects of increasing local weather variability
18 caused by climate change means increasing variability of food availability for domestic use and international
19 trade. Finally, extreme events driven by climate change can disrupt transportation along the food value chain.
20 Countries more at risk of natural hazards that disrupt transportation and distribution, and with less extensive
21 routes, are more vulnerable to climate change impacts. A global multi-hazard risk assessment (Koks et al.,
22 2019) suggests surface and river flooding, which are projected to increase in a warmer climate, are the main
23 hazards for road and railway infrastructure, increasingly disrupting international and domestic transportation
24 of agricultural commodities.
25
26 Climate change impacts will increase most global prices relative to early 21st levels with varying effects on
27 the cost of food imports (high confidence) (Nelson et al., 2014; Wiebe et al., 2015; Fujimori et al., 2018; Lee
28 et al., 2018). For example, analysis using results from one study (using CMIP5 data for RCP8.5 and SSP2)
29 found that net food importing countries in the early 21st century would see expenditures on food imports
30 decrease by USD 36 billion in mid-century in real terms with climate change over a no climate change
31 scenario. (Table 5.13).
32
33
34 Table 5.13: Net exports of agricultural products, by net exporting and net importing countries, 2010 and 2050 (billion
35 constant parity US dollars), based on analysis in Beach et al. (2019)
2010 2050
Net importers in 2010 -301 -838
No climate change
Climate change -301 -802
36
37
38 Global economic models with a focus on agriculture provide a perspective on the range of potential changes
39 in market outcomes because of climate change. In one study comparing several SSPs to a future with no
40 climate change to one with impacts from RCP8.5, 2050 yields with climate changes impacts are 17% smaller
41 on average than those without climate change. Adaptation by farmers reduce that to an 11% decline. The
42 change in 2050 prices of all crops and regions after climate change impacts and farm level adaptation is a
43 mean 20% increase (Nelson et al., 2014). Substantial differences arise from both the heterogeneous impacts
44 of climate change over crops and geography and the diversity of modelling approaches in the GCM and crop
45 models. A later study with more socio-economic scenarios and fewer models got roughly similar results
46 (Wiebe et al., 2015) as did a modelling study focused on food security in South Asian countries (Cai et al.,
47 2016).
48
49 Most climate scenario modelling to date does not incorporate increasing variability nor the use of storage, a
50 critical tool to manage variability. Two recent studies are exceptions. In one, climate change generally
51 reduces mean yields and increases their variability in the Midwestern U.S. and causes modest increases in
52 price volatility (Thompson et al., 2018). A second study (Chen and Villoria, 2019) focuses on maize net
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1 importers across Africa, Asia, and Latin America during 20002015. A 1% increase in the ratio of imports to
2 total consumption reduces domestic price variability by 0.29%. A 1% increase in stocks at the beginning of
3 the season is correlated with a 0.22% reduction in the coefficient of variation.
4
5 5.11.4 Adaptation in the Post-harvest Supply Chain
6
7 The SRCCL (Mbow et al., 2019) findings on adaptation support targeting food value chains and intervention
8 types to the needs of specific locations. Furthermore, adaptation choices will need to be dynamic as climate
9 change impacts are expected to worsen over time.
10
11 As discussed above and in section 6.2.5, climate change is expected to cause increasingly severe effects on
12 infrastructure needed for food security: roads and harbours for transport, water storage facilities for irrigation
13 and storage facilities able to withstand climate-related damage. Three categories of adaptation could be
14 considered adoption of technologies already in use elsewhere, including indigenous and local knowledge,
15 or available or near ready that become profitable as impacts become more severe, development of new
16 technologies, and taking advantage of changing comparative advantage across regions. Specific examples of
17 post-harvest technical adaptation options that are already available but could be more widely adopted include
18 solar driers, cold storage facilities and transport and use of ultrasonic humidification of selected fruits and
19 vegetables, a technology that has been shown in Europe to reduce losses in each postharvest stage by 20%
20 or more (Fabbri et al., 2018). Hermetic storage containers using community-based farmer research networks
21 to scale out (Singano et al., 2020; Wenndt et al., 2021) also show promise. Another innovation is to introduce
22 Aspergillus fungi that do not produce aflatoxins in biocontrol formulations, such as being undertaken in the
23 Aflasafe project in Kenya (Bandyopadhyay et al., 2016).
24
25 International trade changes are a potentially important adaptation mechanism for both the short-term effects
26 of climate variability and long-term changes in comparative advantage with globally substantial benefits but
27 that are distributed unevenly (Mosnier et al., 2014; Baldos and Hertel, 2015; Fuss et al., 2015; Costinot et al.,
28 2016; Hertel and Baldos, 2016; Gouel and Laborde, 2021). One estimate is that with a reduction in tariffs as
29 well as institutional and infra-structural barriers, the negative impacts of climate change globally would be
30 reduced by 64%, with hunger-affected import-dependent regions seeing the greatest benefit. However, in
31 hunger-affected export-oriented regions, partial trade integration might lead to increased exports at the
32 expense of domestic food availability (Janssens et al., 2020). It is possible for policy changes that result in
33 increased trade flows to also increase the potential for maladaptation, for example by encouraging
34 conversion of environmentally sensitive areas to agriculture (Fuchs et al., 2020; 5.13.3).
35
36 As discussed in section 5.4, climate change is expected to increase variability in yields. As long as the
37 variability is not correlated across regions, trade flows within a year can partially compensate, with in-period
38 exports from countries less affected to those that are. Alterations in trade flow patterns to accommodate these
39 impacts will reduce the negative effects so long as this variability is not correlated across regions (UK, 2015;
40 Janetos et al., 2017).
41
42 In terms of food safety impacts, (Lake and Barker, 2018) highlight a range of approaches to enhance
43 preparedness for more serious foodborne disease effects from climate change: adoption of novel surveillance
44 methods to speed up detection and improve intervention in foodborne outbreaks; genotypebased approaches
45 to surveillance of food pathogens to enhance spatiotemporal resolution in tracing and tracking of illness;
46 improving integration of plant, animal and human surveillance systems under the rubric of One Health,
47 increased commitment to crossborder and global information initiatives; improved clarity regarding the
48 governance of complex societal issues such as the conflict between food safety and food waste and strong
49 usercentric (social) communications strategies to engage diverse stakeholder groups.
50
51 The range of potential adaptation approaches from production to transportation to reduce food loss and waste
52 is captured in Figure 5.17 (Galford et al., 2020).
53
54
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1
2 Figure 5.17: Examples of food loss and waste (FLW) interventions at five stages in the food value change (Galford et
3 al., 2020).
4
5
6 The importance of reducing food loss and waste due to climate change is widely recognized, but literature on
7 cost-effective reductions is sparse, particularly in low-income countries (Parfitt et al., 2010). A list of farm
8 and post-harvest methods to reduce food loss (Sheahan and Barrett, 2017) includes potential farm
9 interventions such as varietal choice, education in harvest and post-harvest handling, hermetic storage
10 technologies (see above), chemical sprays and integrated pest management techniques in storage. The
11 evidence on their effectiveness, especially in the face of increased climate change impacts, is limited.
12
13
14 5.12 Food Security, Consumption and Nutrition
15
16 5.12.1 Introduction
17
18 Food security and nutrition are key desired outcomes of food systems. Climate change is already
19 contributing to reduced food security and nutrition and will continue to do so (high confidence) (Sections
20 5.4, 5.5, 5.8, 5.9, 5.10). Climate change impacts affect all four dimensions of food security: availability,
21 access, utilization, and stability (Table 5.14) through both direct and indirect pathways.
22
23 Global food security improved dramatically in the 20th century even as global population increased from 2
24 to 6 billion. While some may assume that global food security is primarily provided by large-scale
25 producers, research since AR5 has shown the sizeable role of small and mid-sized food producers in Asia,
26 Africa and Latin America contributing to global food security and nutrition, while being highly vulnerable to
27 climate change impacts on food security (Samberg et al., 2016; Herrero et al., 2017; FAO et al., 2018;
28 Ricciardi et al., 2018).
29
30 In 2019 more than 750 million people in the world, almost 1 in 10 people, suffered from severe food
31 insecurity, a figure which has risen since 2014 in every region except North America and Europe
32 (FAO et al., 2020). Overnutrition, a result of high-calorie unbalanced diets, is also rising, with over 2 billion
33 adults overweight or obese (FAO et al., 2018; Swinburn et al., 2019; FAO et al., 2020; Venkatesh Mannar et
34 al., 2020; WHO, 2021). Many low and middle-income countries now have both high under- and
35 overnutrition rates (FAO et al., 2018).
36
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1 There are multiple drivers of food security including changing dietary patterns, urbanization and population
2 growth (HLPE, 2017b; FAO et al., 2018; Swinburn et al., 2019). Vulnerability to climate change impacts on
3 food insecurity and malnutrition is worsened by other underlying causes, including poverty, multiple forms
4 of inequality (e.g., gender, racial, income), low access to water and sanitation, macroeconomic shocks, and
5 conflict (Smith and Haddad, 2015; Clay et al., 2018; FAO et al., 2018; Cook et al., 2019). Climate change
6 frequently acts to compound these drivers of food insecurity (Table 5.14).
7
8 The covid-19 pandemic has increased vulnerability to food insecurity and malnutrition of particular groups
9 and sectors in the food system, including low-income households, farmworkers, food service workers,
10 informal food market sellers, and low-income countries dependent on food imports (Cross-Chapter Box
11 COVID in Chapter 7). Climate change will compound pandemic vulnerabilities in the food system (high
12 agreement, low evidence) (HLPE, 2020; UNDRR (United Nations Office for Disaster Risk Reduction -
13 Regional Office for Asia and Pacific), 2020; WFP-FSIN, 2020). The pandemic may also increase
14 coordination among sectors and a willingness to address food system weaknesses made visible by the
15 impacts of COVID-19 (Blay-Palmer et al., 2020; Cohen, 2020; Ramos et al., 2020).
16
17 Ecosystem services, the provisioning, supporting, and regulating mechanisms we all depend on for food
18 security and nutrition, are also undermined by climate change impacts (Section 5.4.3). Even in the absence of
19 climate change, our current food system threatens to exceed planetary, regional, or local boundaries of long-
20 term sustainable development (Campbell et al., 2017). Climate change will make efforts to reduce this threat
21 more difficult to achieve (medium confidence) though many solutions to enhancing food security are also
22 potential climate change adaptation responses (Sections 5.4, 5.6, 5.8, 5.10, 5.14).
23
24 5.12.2 Mechanisms for Climate Change Impacts on Food Security
25
26 Climate change is increasing the number of people experiencing food insecurity through greater incidence
27 and severity of climatic impact drivers (CIDs), (Seneviratne et al., 2021) such as extreme heat, drought, and
28 floods. Increasing CO2 concentrations have positive effects on food and forage crops by enhancing
29 photosynthesis and alleviating drought stresses (5.4.3.1, 5.5.3.1), but have negative effects on nutrient
30 concentrations in food crops. Ocean acidification is also caused by increasing CO2, causing negative impacts
31 on aquatic systems. Tropospheric ozone concentrations already hinder crop production (Section 5.4.1.4).
32 Several CIDs increase the number of people experiencing food insecurity (high confidence) (SROCC 2019,
33 FAO et al., 2018; Mbow et al., 2019; Baker and Anttila-Hughes, 2020; Table 5.12).
34
35 Vulnerability to climate impacts on food security and nutrition vary by region and group. Countries that
36 experience CIDs such as extreme heat, severe drought or floods and have a large proportion of the
37 population dependent on rainfed agriculture or livestock for their livelihoods and food supply have
38 experienced rising food insecurity due to climate change impacts (FAO et al., 2018; Cooper et al., 2019;
39 Mbow et al., 2019). Children in Sub-Saharan Africa are particularly at risk of undernutrition and mortality
40 from increasing temperatures (Belesova et al., 2019; Baker and Anttila-Hughes, 2020). An additional
41 estimated 5.9 million children became underweight due to rising temperatures in 51 countries affected by El
42 Niño Southern Oscillation intensity in 2015-2016 (Anttila-Hughes et al., 2021). Low-income urban
43 households and marginalized groups such as landless and ethnic minorities are at risk of increased food
44 insecurity due in part to climate change extreme events such as extended drought, floods or cyclones that
45 interrupt supply chains and impact livelihoods (Rodriguez-Llanes et al., 2016; FAO et al., 2018; Algur et al.,
46 2021). A systematic review in India found that women often experience greater workloads and stress during
47 drought events (Algur et al., 2021).
48
49 In the subsequent sections, the four dimensions of food security will be discussed in relation to observed and
50 projected impacts and vulnerabilities (Table 5.14).
51
52
53 Table 5.14: Impacts from climate change drivers on the four dimensions of food security. Adapted from Table 5.1 in
54 SRCCL
Climatic impact drivers and mechanism Examples of regions and groups most References
for food security impacts affected
Food security dimension: Availability
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Increased heat and drought reduce crop Countries in which a large proportion relies on FAO et al. (2018), Dury
and animal productivity and soil fertility agriculture for livelihoods. et al. (2019), Mbow et al.
and increase land degradation for some Food production systems that rely on rainfed (2019), Section 5.4 and
regions and crops. agriculture and pastoral rangeland. Urban 5.5).
populations and the poor.
Extreme heat affects crop productivity. Countries and sectors that rely extensively on Zander et al. (2015),
Combined with high humidity reduces outdoor manual agricultural labor and Kjellstrom et al. (2016),
agricultural labour capacity and animal experience high temperatures and humidity Ioannou et al. (2017),
productivity. Mitchell et al. (2017),
FAO et al. (2018), Flouris
Increasing temperatures and East African pastoral groups who experienced et al. (2018), Kjellstrom
precipitation changes increase and shift increased livestock morbidity and mortality et al. (2018), Levi et al.
crop and livestock pests and diseases from Rift Valley Fever in El Niño years. (2018).
Bebber (2015), FAO et
Increasing temperatures and drought Tropical and sub-tropic regions with limited al. (2018), Mbow et al.
stress has led to higher post-harvest losses food safety surveillance (2019), Sections 5.4.1.3
due to mycotoxins. and 5.5.1.3
Rising ocean temperatures, marine Coastal people and coastal areas of tropical Miller (2016), FAO et al.
heatwaves and ocean acidity has reduced countries with high dependence on fisheries (2018), Section 5.11
availability of fish in coastal communities. e.g., West African coastal communities
Hilmi et al. (2014),
Increased number and intensity of Delta regions where there are high populations Golden et al. (2016),
Bindoff et al. (2019),
extreme events such as cyclones lead to and are often important food production Section 5.8 and 5.9
Omori et al. (2020)
reduced food production and distribution regions. E.g., Cyclone Nargis in Myanmar
Iizumi et al. (2018);
from crop damage, increased pest estimated to reduce crop production by 19%, Canadell et al. (2021),
Ranasinghe et al. (2021),
incidence and transportation disruption. production declined for subsequent 3 years. Cross-Chapter Box
MOVING PLATE this
Increased atmospheric CO2 All regions are anticipated to have increased Chapter)
concentrations increase total plant atmospheric CO2 concentrations, but due to
Saronga et al. (2016),
biomass and plant sugar content, which can impacts of other CIDs (e.g., drought, heat Giannini et al. (2017),
FAO et al. (2018) Mbow
increase crops as well as pests and weeds. stress, pests), the impacts on crop growth, et al. (2019) Omori et al.
(2020)
High CO2 also reduces transpiration during forage, and subsequent food availability are
FAO et al. (2018), Mbow
drought which can increase plant drought mixed. et al. (2019), Ilboudo
Nébié et al. (2021)
resistance.
Toufique and Belton
Food security dimension: Access (2014), FAO et al.
(2018), Hickey and
Increased drought and flood events and Low-income smallholder farmers and Unwin (2020), Algur et
al. (2021)
increased pests and disease from rising pastoralists in Ethiopia, Mali, Niger, Malawi,
FAO et al. (2018), Mbow
temperatures lead to loss of agricultural Zambia, and Tanzania. et al. (2019), Section 5.11
income due to reduced yields, and higher
costs of production inputs such as water.
Reduced ability to purchase food leads to
lower dietary diversity and consumption
levels.
Increase in number and intensity of Low-income consumers.
extreme weather events (e.g droughts, Women and girls.
floods) lead to increased food prices,
which often leads to lower dietary diversity
as well as lower consumption levels.
Extreme events (e.g. floods) disrupt food Countries dependent on food imports e.g
storage and transport networks, reducing Small Island Developing States. Poor
access and availability of food supplies. households living in flash flood and saline
zones in Bangladesh who rely on
monocropped rice. Women and children may
experience greater impacts from extreme
events.
Food security dimension: Utilization (food quality and safety)
Increased temperatures reduce food Countries with limited food safety
safety caused by microorganisms, surveillance systems.
including increased mycotoxins in food
and feed.
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Climate change extreme events make Urban low-income households and rural An et al. (2018), Algur et
fruits and vegetables relatively households who purchase the majority of their al. (2021), Baker and
unaffordable compared to less nutrient food. Children in regions such as West Africa, Anttila-Hughes (2020),
dense foods. with lower access to diverse food types as a Niles et al. (2021)
result of climate impact drivers e.g. drought.
Rising air temperatures, ocean warming, Low-income tropical countries where current Golden et al. (2016),
and high CO2 conditions increase risk of ability to reduce and monitor mycotoxin Bindoff et al. (2019),
food poisoning and pollutant contamination is limited. Coastal Indigenous Sections 5.7, 5.8, 5.9,
contamination of food through increased Peoples and other poor populations in coastal 5.11
prevalence of pathogens (e.g., areas of tropical countries with high
mycotoxins), harmful algal bloom, and dependence on fisheries e.g., west African Mbow et al. (2019),
increased contaminant bioaccumulation coastal communities Section 5.4
and threaten human health.
Increased atmospheric CO2 Low-income households who have limited Golden et al. (2016);
concentrations reduce nutritional quality access to range of diverse foods. Bindoff et al., 2019;
of grains, some fruits, and vegetables. Section 5.7, 5.8, 5.9
Rising ocean temperatures, marine Coastal areas of tropical countries; coastal
heatwaves and ocean acidity reduce fish Indigenous Peoples and other groups who rely Toufique and Belton
populations, which reduce consumption of on fisheries. (2014), FAO et al.
fish high in iron, zinc, omega-3 fatty acids (2018), Algur et al.
and vitamins in areas where fish Landlocked countries; low-income countries (2021), Section 5.11
populations decline. reliant on imports; lo- income households in
Food security dimension: Stability areas prone to floods. Ruiz Meza, (2015), FAO
Increased frequency and severity of et al. (2018), Sections
extreme events (e.g., droughts and Small-scale producers (crops and livestock) 5.8, 5.9
heatwaves) lead to greater instability of and fishers
supply through production losses and Bene et al. (2015), Peri
disruption to food transport. Low-income countries reliant on imports; (2017), Mbow et al.
Increased drought and flood events and Urban low-income households and rural (2019), Section 5.11
increased pests and disease from rising households who purchase the majority of their
temperatures lead to unstable incomes food. Golden et al. (2016),
from agriculture and fisheries. Coastal communities in West Africa, SE Asia, Bindoff et al. (2019)
Climate change extreme events increase and other tropical countries highly dependent Mbow et al. (2019)
food prices due to climate shocks. on fisheries.
Jones and Barbetti
Increased drought and flood events and Australia, most Asian regions, Europe, Central (2012), IPPC Secretariat
increased pests and disease from rising and South America, North America (2021), Ranasinghe et al.
temperatures cause widespread crop The benefits of yield gains at high latitudes (2021)
failure. Rising ocean temperatures, may be tempered by greater risks of pests and
marine heatwaves, and ocean acidity pathogen damages.
lead to dramatic decline in fisheries
contributing to migration and conflict.
Reduced frost days and snow days will
increase stability of food security in some
temperate regions since there will be less
loss of food crops to frost damage and a
longer growing season. However, they also
raise pest and disease risks due to
increased range and overwintering.
1
2
3 5.12.3 Observed Impacts
4
5 5.12.3.1 Impacts on food availability
6
7 All food production systems (crops, livestock, marine, fish, mixed, aquaculture) have been undermined by
8 climate change and are expected to experience larger impacts in the future as described in earlier sections
9 (see Sections 5.4.1, 5.5, 5.8, 5.9, 5.10). In addition, sudden production losses from extreme climate events
10 can reduce food security (FAO et al., 2018; Cottrell et al., 2019; FAO et al., 2020; Anttila-Hughes et al.,
11 2021). For example, a 2007 drought-induced crop failure in southern Africa led to severe food insecurity in
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1 Lesotho because of the land-locked country's dependence on imports from South Africa that aggravated food
2 availability and access under conditions of declining food production and land degradation (Verschuur et al.,
3 2021). Pest and disease outbreaks in both crops and livestock due to climate change (Sections 5.4.1, 5.5.1)
4 have also impacted food availability and access (see Box 5.8 Desert Locust case study). Loss in labour
5 productivity from climate change-related heat stress is a growing problem.
6
7
8 [START BOX 5.9 HERE]
9
10 Box 5.9: Desert Locust Case Study: Climate as Compounding Effect on Food Security
11
12 At the end of 2019, desert locust swarms infested Eastern Africa and caused widespread damage to crops and
13 pastures, threatening food security and livelihoods (Kimathi et al., 2020; Salih et al., 2020). The FAO
14 estimates that over 200,000 ha of crop and pastureland were damaged, rendering 2 million people in the
15 region acutely food insecure (IGAD, 2020). The desert locust infestation was facilitated by two tropical
16 cyclones that created desert lakes in a usually dry region of Saudi Arabia. Moist soils, warm temperatures
17 and ample vegetation provided a suitable environment for desert locust breeding and migration to Yemen
18 and Somalia, where the pest remained uncontrolled due to conflict and spread to neighbouring countries. A
19 series of political and socioeconomic weaknesses such as armed conflict, limited financial resources, and
20 lack of early actions compounded the impact of the current invasion and made it the most damaging in 70
21 years (Meynard et al., 2020; Salih et al., 2020).
22
23 Although desert locusts have been here for centuries, this recent outbreak can be linked to a unique feature of
24 the positive Indian Ocean Dipole event (IOD), in part caused by long-term trends in sea surface temperatures
25 (Wang et al., 2020a). The warming of the western Indian Ocean has increased frequency and intensity of
26 severe weather, including tropical cyclones (Roxy et al., 2014; Murakami H, 2017; Roxy et al., 2017). Under
27 a 1.5° C warmer climate, extreme positive IODs are anticipated to occur twice as often, which could also
28 increase the occurrence of pest outbreaks (Cai et al., 2018).
29
30 Climate change increases the need for robust adaptation measures, such as transnational early warning
31 systems, biological control mechanisms, crop diversification, and further technological innovations in areas
32 of sound and light stimulants, remote sensing, and modeling for tracking and forecasting of movement
33 (Maeno and Ould Babah Ebbe, 2018; Peng et al., 2020). The desert locust outbreak and the role of the Indian
34 Ocean warming show that the impacts of climate change extend can increase unpredictable events. Extreme
35 weather events act as a compounding effect, exacerbated further by weak governance systems, political
36 instability, limited financial resources, and poor early warning systems (Meynard et al., 2020).
37
38 [END BOX 5.9 HERE]
39
40
41 Climate change affects agricultural labour productivity through increased intensity and frequency of heat
42 stress events, with those performing physical labour in high humidity and ambient temperatures most
43 vulnerable to heat stress (high confidence) (Hsiang et al.; FAO et al., 2018; Kjellström et al., 2019; Antonelli
44 et al., 2020; Shayegh et al., 2020). Labour capacity, supply, and productivity loss in moderate outdoor work
45 due to heat stress is estimated between 2% and 14% depending on the location and indicator (Ioannou et al.,
46 2017; Kjellstrom et al., 2018), with an overall estimate of 5.3% loss in productivity for outdoor work
47 between 2000 and 2015 (medium confidence) (Watts et al., 2018) but as high as 14% in low-income tropical
48 countries (Antonelli et al., 2020; Shayegh et al., 2020). Highly vulnerable occupation groups affected by heat
49 stress include farmers, farmworkers and livestock keepers working outdoors in low-income tropical countries
50 (high confidence) (Zander et al., 2015; Kjellstrom et al., 2016; Flouris et al., 2018; Kjellstrom et al., 2018;
51 Levi et al., 2018). Farmworkers and small-scale food producers in high- and middle-income countries
52 involved in outdoor labour are also affected by heat stress (Zander et al., 2015; Gosling et al., 2018;
53 Szewczyk et al., 2018; Watts et al., 2021). There is also evidence that heat stress is affecting labour supply
54 through variation in nutrition intake (Antonelli et al., 2020).
55
56 5.12.3.2 Impacts on food access (physical, economic, and socio-cultural) and vulnerabilities
57
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1 Increased extreme events (e.g., droughts, floods, and tropical storms, (Seneviratne et al., 2021) due to climate
2 change are key drivers of recent rises in food insecurity rates and severe food crises in some regions (high
3 confidence) (Section 5.4.1, Yeni and Alpas, 2017; FAO et al., 2018; Cooper et al., 2019; Baker and Anttila-
4 Hughes, 2020; Bogdanova et al., 2021; Ilboudo Nébié et al., 2021). Extreme weather events reduce physical
5 and economic access to food, increase food prices, and compound underlying conditions of food insecurity
6 and malnutrition such as low access to diverse healthy foods, and safe water (FAO et al., 2018; Niles et al.,
7 2021). Increased incidence of severe drought conditions since 2005 are contributing to food insecurity in
8 affected regions, including Africa, Asia, and the Pacific ( Chapter 7, Phalkey et al., 2015; FAO et al., 2018;
9 Cooper et al., 2019; Ilboudo Nébié et al., 2021; Verschuur et al., 2021;). In Arctic western Siberia, high
10 temperatures, melting ice and forest and tundra fires have degraded reindeer pastures; Indigenous Peoples
11 have reduced traditional diets and increased purchased food with increases in hypertension and related health
12 impacts (Bogdanova et al., 2021).
13
14 There is growing evidence that anthropogenic climate warming has already intensified climate extreme
15 events induced by large-scale sea surface temperature oscillations such as ENSO (Herring et al., 2018;
16 Seneviratne et al., 2021). For example, the 2015-2016 El Niño, the strongest for the past 145 years, induced
17 severe droughts in southeast Asia, eastern and southern Africa, some intensified by anthropogenic warming
18 (Funk et al., 2018). As a result, 20.5 million people faced acute food insecurity in 2016 (FSIN, 2017) and an
19 estimated additional 5.9 million children became underweight (Anttila-Hughes et al., 2021).
20
21 Weather extreme events increased food prices and food price volatility (Peri, 2017), thereby worsening food
22 insecurity (Shiferaw et al., 2014; Bene et al., 2015; Miyan, 2015; FAO et al., 2018; Ilboudo Nébié et al.,
23 2021). Rising food prices can affect conflict, political instability, and migration (Bush and Martiniello, 2017)
24 but the relationship between climate change, political instability and conflict is often mediated by other
25 underlying factors such as poor governance (Chapter 7.2.7, Mach et al., 2019; Selby, 2019).
26
27 Low-income urban and rural households who are net food buyers are particularly affected by food price
28 increases, with reduction of consumption of diverse food groups (high confidence) (Green et al., 2013;
29 Villasante et al., 2015; FAO et al., 2018). Depending on the context, particular groups, including women,
30 ethnic and religious minorities will be more vulnerable to worsening food insecurity from climate change
31 impacts (Clay et al., 2018; Jantarasami et al., 2018; Nature climate change Editorials, 2019; Algur et al.,
32 2021 and see Cross-Chapter Box GENDER in Chapter 18). Indigenous Peoples are often more vulnerable to
33 climate change, due to conditions of poverty, limited resources, discrimination, and marginalization (high
34 confidence) (Smith and Rhiney, 2016; Vinyeta et al., 2016; Jantarasami et al., 2018). Indigenous Peoples
35 may experience loss of culturally significant foods and declining traditional ecological knowledge (Dounias
36 and Ichikawa, 2017; Ross and Mason, 2020; 5.7 ).
37
38 5.12.3.3 Impacts on food utilization and vulnerabilities
39
40 Food utilization refers to the way the body most effectively uses food, and includes food preparation, food
41 quality, and intra-household distribution. Food utilization is affected by climate change in several ways: food
42 safety, dietary diversity, and food quality (Aberman and Tirado, 2014).
43
44 Climate change hazards have increased food safety risks (high confidence) including animal diseases (5.5),
45 harmful algal blooms and marine toxins (Section 5.8, 5.9) and mycotoxins (Section 5.11). Other foodborne
46 and waterborne infectious diseases such as cholera are further covered in Chapter 7.
47
48 Weather variability and extreme events (Seneviratne et al., 2021) have reduced availability and access to
49 diverse foods to sell and to purchase in rural markets, thereby reducing access to affordable, diverse foods
50 for both rural small-scale producers and net consumers, particularly for landlocked and low-income countries
51 (high confidence) (Pant et al., 2014; Villasante et al., 2015; Alston and Akhter, 2016; FAO et al., 2018; Park
52 et al., 2019; Niles et al., 2021) and otherwise marginalised communities (Algur et al., 2021). One study of 87
53 countries and 150 extreme events estimated that low-income food deficit and landlocked countries had
54 reduced nutrient supply ranging from -1.6 to -7.6% of average supply, a significant portion of a healthy
55 child's average dietary intake (Park et al., 2019).
56
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1 Rural children in low-income countries are at particular risk of undernutrition from climate change impacts,
2 due to a combination of factors: potential reduction in food quantity and quality from heat impacts; greater
3 exposure from outdoor play and agricultural activities, and increased likelihood of heat exhaustion, vector
4 borne and diarrheal diseases (Oppenheimer and Anttila-Hughes, 2016). A study of child growth data in 30
5 countries in Africa between 1993-2012 found that increased temperature was significantly related to
6 children's wasting (Baker and Anttila-Hughes, 2020). Another study examined 30 years of climate data and
7 child dietary diversity outcomes in 19 countries, and found that higher-than-average annual temperatures
8 correlated with declines in child diet diversity at levels equal to or greater than other factors which often are
9 the focus of policy, such as market access or education (Niles et al., 2021).
10
11 5.12.3.4 Impacts on food stability
12
13 Climate change has already changed the start and duration of the growing season and increased variability of
14 rainfall in some places with impacts on food intake and nutritional status and income for low-income and
15 small-scale producers (medium evidence, high agreement, (FAO et al., 2018; Cooper et al., 2019). Evidence
16 to date suggests that climate change has negative impacts on the stability of food supply over the medium to
17 long term, thereby affecting food stability (Myers et al., 2017b). Increasing number and intensity of adverse
18 weather events, driven by climate change (Seneviratne et al., 2021), are important factors decreasing food
19 stability, through reduced availability, increased local price volatility, reduced livelihoods for food producers
20 and disruption to food transport (Toufique and Belton, 2014; Verma et al., 2014; Ruiz Meza, 2015; Clay et
21 al., 2018; FAO et al., 2018; Mbow et al., 2019).
22
23 5.12.4 Projected Impacts on Food Security
24
25 5.12.4.1 Food availability and access
26
27 Climate change will have negative effects on food security and nutrition in 2050 (high agreement, medium
28 evidence) (Amjath-Babu et al., 2016; Springmann et al., 2016; Lloyd et al., 2018; Richardson et al., 2018;
29 see Chapter 7; Hasegawa et al., 2021a). How many people are affected will depend considerably on non-
30 climatic drivers of food security (van Dijk et al., 2021), but modelling studies agreed that climate change
31 would increase the risk of food insecurity. For example, one study comparing an RCP8.5 scenario with one
32 that has zero climate impacts estimates 65 million additional people (10% increase) will experience food
33 insecurity due to climate change impacts in 2050 (modelling results in Nelson et al. (2018)). Another study
34 accounting for climate extreme events estimates that by 2050, the number of people at risk of hunger will
35 increase by 20% and 11 % under high and low emission scenarios, respectively, owing to a once-per-100-
36 year extreme climate event (Hasegawa et al., 2021a). Sub-Saharan Africa and South Asia in this study were
37 projected to be at the greatest risk, with triple the amount of South Asia's current food reserves needed to
38 offset such an extreme event. Models suggest that food security and malnutrition impacts will be much more
39 severe from 2050 onwards relative to pre-2050, but the scale and extent of the impacts will strongly depend
40 on the greenhouse gas emission scenario (FAO, 2018a; Richardson et al., 2018). Due to climatic impact
41 drivers and non-climate drivers of food insecurity, Sub Saharan Africa is projected to be the hardest hit,
42 followed by south Asia and Central and South America, but contingent on adaptation level (Richardson et
43 al., 2018; Hasegawa et al., 2021a).
44
45 Without adaptive measures, heat stress impacts on agricultural labour will increase with climate change (high
46 confidence) (Im et al., 2017; Levy and Roelofs, 2019; Hertel and de Lima, 2020). Climate-change-related
47 heat stress will reduce outdoor physical work capacity on a global scale. Depending on greenhouse gas
48 concentrations, some regions will experience losses of 200 to 250 outdoor workdays per year at century's
49 end. Using results from one study reporting experimental procedures to assess loss of work capacity (Foster
50 et al., 2021) regions hardest hit in an SSP5-8.5 scenario include much of South Asia, tropical Sub-Saharan
51 Africa and parts of Central and South America (Figure 5.18) de Lima et al. (2021) projected that negative
52 impacts of warming on crop yields and labour capacity would affect crop production and cost for workers
53 and labour-saving mechanisation, raising food price by 5 % at +3° from the baseline period (1986-2005)
54 globally, with significant implications for vulnerable regions (sub-Saharan Africa and Southeast Asia). Large
55 uncertainties, however, exist around population diversity and adaptive capacity (Vanos et al., 2019).
56 Agricultural labour productivity impacts of heat attributed to climate change are expected to be worse in
57 low- and middle-income countries (Kjellstrom et al., 2016). Adaptation options needed to protect agricultural
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1 worker productivity outdoors and reduce occupational heat illnesses and deaths include cooled working
2 environments, improved surveillance systems and education about the need to monitor (high confidence)
3 (Xiang et al., 2016; Quiller et al., 2017; Flouris et al., 2018; Day et al., 2019; Vanos et al., 2019). Currently
4 available options, however, are more difficult to achieve in lower-income economies (Kjellstrom et al., 2016;
5 Im et al., 2017).
6
7
8
9 Figure 5.18: The number of days per year where physical work capacity (PWC) is less than 50% based on average
10 daily air temperature and relative humidity (Foster et al., 2021). PWC is defined as the maximum physical work output
11 that can be reasonably expected from an individual performing moderate to heavy work in a `cool' reference
12 environment of 15oC. Values plotted are from the early (A) and end of century (B) for SSP 585 using ensemble means
13 from the ISIMIP CMIP6 data set. See SM5.4 for detail.
14
15
16 Under higher emission scenarios, food availability will be further reduced after 2050, due to the potential for
17 widespread crop failure, and decline in livestock and fisheries stocks (Mbow et al., 2014; Kelley et al., 2017;
18 Challinor et al., 2018; Hendrix, 2018; Bindoff et al., 2019). At +3° from the preindustrial era, all food
19 production sectors will experience greater, and pronounced, losses due to climate change compared to +1.5°
20 or +2° (see Sections 5.2, 5.4.3, 5.8.3 and 5.9.3).
21
22 Food insecurity from food price spikes due to reduced agricultural production associated with climate impact
23 drivers such as drought can lead to both domestic and international conflict, including political instability
24 (Abbott et al., 2017; Bush and Martiniello, 2017; WEF, 2017; D'Odorico et al., 2018; de Amorim et al.,
25 2018;Chapter 7.2.7 ). While climate change impacts, including drought impacts on food security are
26 important risk factors for conflict, other key drivers are often more influential, including low socioeconomic
27 development, limited state capacity, weak governance, intergroup inequities, and recent histories of conflict
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1 (medium confidence) (Mach et al., 2019; Selby, 2019; Chapter 7.2.7). The interaction between extreme
2 weather events, conflict and human migration may increase vulnerability of particular communities of low-
3 income countries (WEF, 2017; D'Odorico et al., 2018; de Amorim et al., 2018; Chapter 7 ). Further research
4 is needed to better understand how increased drought-risk under future climate change might affect food
5 prices and water availability (Abbott et al., 2017).
6
7 5.12.4.2 Projected impacts on food safety and quality
8
9 Increasing levels of CO2 directly contribute to reduced food quality by reducing levels of protein, iron, zinc
10 and some vitamins, varying by crop species and cultivars (high confidence) (Section 5.4.3, Myers et al.,
11 2014; Smith and Haddad, 2015; Bisbis et al., 2018; Scheelbeek et al., 2018; Weyant et al., 2018; Zhu et al.,
12 2018a). Higher levels of CO2 are predicted to lead to 5-10% reductions in a wide range of minerals and
13 nutrients (Loladze, 2014). Climate warming will also reduce food quality of seafood, by changing the long-
14 chain polyunsaturated fatty acid content in phytoplankton (Section 5.8; Hixson and Arts, 2016).
15
16
17 [START BOX 5.10 HERE]
18
19 Box 5.10: Food Safety Interactions with Food Security and Malnutrition
20
21 Climate change significantly increases the future food safety risks (high confidence) (Sections 5.8.2, 5.8.3,
22 5.11.1, Box 5.9). Increasing temperatures and drought stress are expected to lead to greater aflatoxin
23 contamination of food crops. Aflatoxins, a major foodborne hazard, contaminate staple crops and are
24 associated with various health risks including stunting in children and cancer (Koshiol et al., 2017). In LICs,
25 children with high exposure to aflatoxins were found to be more likely to suffer from micronutrient (zinc and
26 vitamin A) deficiencies (Watson et al., 2016b). Climate change is expected to cause decreases in micro- and
27 macronutrient content of foods, leading to an increased burden of infectious diseases, diarrhea and anaemia,
28 with an estimated 10 % increase in disability-adjusted life years (DALYs) by 2050 associated with
29 undernutrition and micronutrient deficiencies (Aberman and Tirado, 2014; Smith and Myers, 2018; Weyant
30 et al., 2018; Zhu et al., 2018a; Ebi and Loladze, 2019; FAO, 2020a; Sulser et al., 2021b).
31
32 Children in low-income countries will be at greater risk of undernutrition from these multiple climate change
33 impacts, including lower food availability, lower food quality, food safety and risk of diarrheal disease (high
34 confidence) (Aberman and Tirado, 2014). One study of 30 countries in Africa estimated that by 2100,
35 increased temperatures under RCP8.5 could increase children's wasting in western Africa by 37% and 25%
36 in southern Africa (Baker and Anttila-Hughes, 2020).
37
38 The combination of climate change and the presence of arsenic in paddy rice fields is expected to increase
39 the toxic heavy metal content of rice and reduce production by 2100, threatening food security and food
40 safety mainly in low-income countries where rice is the main staple (Neumann et al., 2017; Muehe et al.,
41 2019; Farhat et al., 2021).
42
43 [END BOX 5.10 HERE]
44
45
46 5.12.4.3 Reaching SDG2
47
48 Current projections indicate that it is highly likely that the UN SDG 2 (`Zero Hunger') by 2030 will not be
49 achieved, with climate impacts one of several drivers on food security and nutrition preventing this goal
50 including in Africa, Small Island States and South Asia (high confidence) (FAO et al., 2018; Otekunrin et al.,
51 2019; Singh et al., 2019; Atukunda et al., 2021; Kumar et al., 2021; Vogliano et al., 2021). Integrated policy
52 strategies that consider synergies and tradeoffs between different food system components would strengthen
53 the likelihood of meeting SDG2 goals (Dyngeland et al., 2020; Lipper et al., 2020; Vogliano et al., 2021)
54 (Grosso et al., 2020). Adaptation options which address climate risks for food security and nutrition are
55 discussed below.
56
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1 5.12.5 Adaptation Options for Food Security and Nutrition
2
3 Since AR5 there has been increased research on adaptation options that address climate risks for food
4 security and nutrition. In this section cultivar improvements, urban and peri-urban agriculture, changing
5 dietary patterns, integrated multisectoral approaches and rights-based approaches are assessed for their
6 potential as an adaptation option that addresses food security and nutrition. Feasibility and effectiveness
7 assessment of several options is in section 5.14.
8
9 5.12.5.1 Potential, barriers, and challenges for genetically modified crops to address food security and
10 nutrition
11
12 While biotechnology can be used as an adaptation strategy (Section 5.4.4.3), there is low confidence that
13 genetically modified (GM) crops can increase food security and nutrition in smallholder farming systems
14 relative to alternative agronomic strategies (National Academies of Sciences Engineering and Medicine,
15 2016; Qaim, 2016). Some underline their potential in building resilience to changing climatic conditions, in
16 the form of enhanced drought/heat tolerance, pest/disease protection and/or reduced land usage, thus serving
17 to bolster food security and nutrition (Sainger et al., 2015; Muzhinji and Ntuli, 2021). Others suggest that the
18 empirical evidence supporting GM crops as a climate-resilience strategy remains thin (Leonelli, 2018).
19 Technical and social barriers and potential solutions are summarized in Table 5.15.
20
21
22 Table 5.15: Barriers, challenges and potential solutions for GM crops
Barriers and challenges Examples and potential solutions to barriers
Major challenges as a food security and nutrition adaptation One case study is the Water Efficient Maize for Africa
include the introgression of GM traits into host varieties program (WEMA), a Public Private Partnership that
(Dowd-Uribe, 2014), and confusion around proper growing transplants a cold shock protein B, known as
practices that can accelerate resistance (Iversen et al., 2014; Droughtgard, into maize in order to mitigate yield
Fischer et al., 2015). The combination of the kinds of traits losses from drought. Proponents suggest that this GM
and restrictions that come from the predominant intellectual venture, which will be distributed free to smallholder
property rights instruments used in their commercialization, farmers, represents the best strategy for ensuring
and concentration of plant and animal breeding industry stable yields in the face of climatic change across
(Bonny, 2017) mean that benefits from released GM crops Africa (Kyetere et al., 2019). Critics argue that
tend to be captured disproportionately by farmers with WEMA maize is not a good fit with the smallholder
more land, wealth and education (Afidchao et al., 2014; Ali farming systems it is designed to benefit, with
and Rahut, 2018; Azadi et al., 2018) but also increase debt particular concerns around how farmers will access
levels for growers (Dowd-Uribe, 2014; Leguizamón, 2014). the extra inputs, credit, and labour that WEMA maize
requires in order to be successful (Schnurr, 2019).
Underlying gender inequities also play a critical role in
shaping food security and nutrition outcomes associated Emergent genome edited crops are considered a more
with the introduction of GM crops in part due to unequal precise, accessible and accelerated means of targeting
control over income and agricultural decision-making; in stressors that matter to poor farmers, but evidence is
some cases women reported decreased workload and limited (Kole et al., 2015; Haque et al., 2018; Zaidi et
enhanced decision-making power (Gouse et al., 2016), al., 2019). A more iterative and flexible adaptation
while in others the introduction of GM crops could increase approach beyond just genomic improvement to tackle
workload and devalue womens' role as seed savers.(Carro- the multiplicity of factors limiting smallholder
Ripalda and Astier, 2014; Addison and Schnurr, 2016). production is anticipated to increase the likelihood
that these promising technologies can enhance food
Major hurdles for genetically modified crops include security and nutrition (medium confidence) (Giller et
translating promising research results into real-world al., 2017; Stone, 2017; Montenegro de Wit, 2019).
farming systems and consumer trust in the food product.
Experimental programs have been dogged by issues To address food security and nutrition, future breeding
including complications with the introgression of needs to move from just enhancing agronomic traits of
genetically modified traits into high-performing varieties a single crop to improving multiple traits of multiple
(Dowd-Uribe and Schnurr, 2016; Stone and Glover, 2017), crops suited to local conditions that will increase
strict management regimes that clash with the realities of climate resilience of farming systems. To make
smallholder agricultural systems (Iversen et al., 2014; breeding technologies scale-neutral, the policy
Whitfield et al., 2015), and a lack of attention to farmer structure is needed to support and protect smallholders
decision-making (Schnurr, 2019). (medium confidence).
23
24
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1 5.12.5.2 Urban and peri-urban agriculture, vertical and horizontal
2
3 Urban areas have more than half of the global population and consume about 70 % of the total food supply
4 (FAO, 2019b). The urban population is projected to grow further to about 70 % of the global population by
5 2050 (UN, 2018). Direct evidence supporting climate resilience of UPA is limited and contextual, but there
6 is medium confidence of multifunctional benefits from UPA, depending on regions and types of UPA
7 (Artmann and Sartison, 2018; Kareem et al., 2020). UPA takes different forms of production, and can be
8 broadly classified into four categories, depending on operating characteristics and capital inputs (Table 5.16)
9 (Goldstein et al., 2016). Controlled environments can protect crops, livestock, and fish from extreme weather
10 events or pest and disease outbreak (Mohareb et al., 2017). Innovative indoor farming such as vertical
11 farming can be highly productive with minimal water and nutrient supply but can be capital intensive with
12 high energy demand (O'Sullivan et al., 2019) and those with aquaponics can be water demanding (Love et
13 al., 2015). Currently, commodities are often limited to crops with short growing seasons such as leafy
14 vegetables. Vertically grown crops are more expensive than field-grown produce, and thus not accessible for
15 low-income urban dwellers (Al-Kodmany, 2018). Community and institutional unconditioned (outdoor)
16 farms and gardens are better positioned to provide increased access to healthy food to those who need it
17 (Eigenbrod and Gruda, 2015; Goodman and Minner, 2019).
18
19 Many UPA farmers are migrant workers or other socially marginalized racial and ethnic groups and often
20 limited by access to land (Lawanson et al., 2014; Horst et al., 2017). There is high agreement that proactive
21 policies for urban design accounting for food-energy-nexus and social inclusion including addressing
22 questions of governance and rights to green urban spaces are necessary to enhance food provisioning and to
23 gain multiple functions of UPA (Lwasa et al., 2014; Horst et al., 2017; Mohareb et al., 2017; Siegner et al.,
24 2018; O'Sullivan et al., 2019; Titz and Chiotha, 2019; Halvey et al., 2020).
25
26
27 Table 5.16: Urban agriculture classifications based on operating characteristics and capital inputs (Goldstein et al.,
28 2016; O'Sullivan et al., 2019), and a summary of literature search on positive and negative aspects.
Summary of adaptation option and evidence for improved food security and nutrition
Urban agriculture has two components vertical (e.g., grown on or in buildings) and horizontal (grown on land within
urban boundaries, in backyards and marginal spaces). The horizontal component of urban and peri-urban agriculture
(UPA) has gained attention because of multiple functions that could improve food systems and ecosystem services under
climate change (Revi et al., 2014; Artmann and Sartison, 2018; FAO, 2019b; Mbow et al., 2019; Chapter 6).
UPA cannot fully feed urban dwellers within its boundaries but can make an important contribution to local food security
and nutrition (medium confidence) (Martellozzo et al., 2014; Badami and Ramankutty, 2015; Algert et al., 2016; Mohareb
et al., 2017; Clinton et al., 2018; Kriewald et al., 2019). UPA is also expected to play important roles in ecosystem
functions in addition to alleviating food shocks caused by natural disasters and reducing food mileage.
Categories and Synergies Tradeoffs
Description
Ground-based - Multi-species cropping can increase access to - Can increase the value of land and
Unconditioned diverse healthy foods and reduce food costs for thereby push out lower income households
Traditional, peri- low-income households (Algert et al., 2016; Horst via gentrification (Horst et al., 2017).
urban field farms, et al., 2017). -unconditioned UPA is under strong
market gardens, pressure from other lucrative land-use
community farms, -Green cover helps to attenuate heat island effects, demands and can be difficult to maintain
community gardens, reduce run-off and flood risks (Lwasa et al., 2015; without addressing urban social inequities,
home gardens. Di Leo et al., 2016; Gondhalekar and Ramsauer, (Martellozzo et al., 2014; Horst et al.,
Building-integrated 2017; Artmann and Sartison, 2018; Small et al., 2017; White and Bunn, 2017).
Unconditioned 2019).
-Yields are lower than conventional, rural
Rooftop gardens, -Green garden spaces can reduce vulnerability to production and water demand is high
balcony agriculture, heat stress and food insecurity for low-income (Goldstein et al., 2016; Bisaga et al.,
and green wall, but neighborhoods and address racial inequities in 2019).
production quantity is access to green spaces if UA governance addresses
small. equity concerns (Horst et al., 2017; Titz and - Air, soil and water quality in urban areas,
Chiotha, 2019; Halvey et al., 2020; Hoffman et al., can disturb crop production and reduce
2020) food safety (Eigenbrod and Gruda, 2015;
Titz and Chiotha, 2019), and create health
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-Multi-species cropping helps to conserve risks from contamination (Mok et al.,
biodiversity (Lovell, 2010; Goldstein et al., 2016). 2014) which causes mixed or even
negative public perceptions against the
-Skill building and job opportunities (Lovell, produce (Specht et al., 2019; Menyuka et
2010; Mok et al., 2014; Horst et al., 2017), al., 2020). Trace metal contamination in
sometimes in regions and for groups that have soils and plants is an increased risk in
been socially and economically disadvantaged outdoor UPA (Eigenbrod and Gruda, 2015;
(Horst et al., 2017). Titz and Chiotha, 2019).
- cultural ecosystem service benefits through -May provide limited job and income
cultivation of specific crops, cultural learning, opportunities in low income urban areas
sharing culinary and garden knowledge and (Daftary-Steel et al., 2015; Biewener,
strengthening social networks for socially 2016)
marginalized ethnic, racial groups (Horst et al.,
2017; Nadeau et al., 2019). - outdoor fields are exposed to rising
temperatures and urban heat islands
-UPA provides social and health co-benefits such (Chapman et al., 2017). Low water
as increased social interaction, physical and availability may be another limit for UPA
mental health benefits (Horst et al., 2017; White as a form of adaptation (Kareem et al.,
and Bunn, 2017). 2020; Tankari, 2020). In coastal cities, sea
level rise and flooding from climate
-can divert organic waste produced in cities as change impacts may make significant
compost, to reduce water contamination and input portions of cities unuseable for UPA
costs (Menyuka et al., 2020) (Algert et al., 2016; Kareem et al., 2020).
Ground-based -Controlled environments can protect crops, -Power outages and/or system failure can
Conditioned
livestock, and fish from extreme weather events or easily destroy the production system
pest and disease outbreak (Mohareb et al., 2017). (Small et al., 2019).
Horticultural farms -Some building integrated conditioned farms can -Initial costs and energy requirements,
using glasshouses or utilise wastewater and waste heat from buildings particularly are substantially higher than
polyhouses. Often or other urban source (De Zeeuw et al., 2011; unconditioned farms (Goodman and
exist on the city Thomaier et al., 2015; Mohareb et al., 2017). Minner, 2019; O'Sullivan et al., 2019).
fringes. -Greenhouse gas emissions may be higher
Aquaponics that grow - Innovative indoor farming such as vertical than conventional rural agriculture (Santo
fish in aquaculture farming (VF) is highly productive with minimal et al., 2016) and full mitigation potential
systems and reuse water and nutrient supply, but highly energy- only realized with low energy systems
nutrient-rich demanding (O'Sullivan et al., 2019). (WGIII, 12.4)
wastewater. One of - Some initiatives combine with social justice
the few options that goals and use abandoned buildings in low income -Commodities are often limited to short-
provide proteins in neighbourhoods to grow diverse food types for cycled crops such as leafy vegetables and
urban farms. addressing food security of low income groups herbs and the produce is more expensive,
Building integrated (Thomaier et al., 2015; Horst et al., 2017). which are difficult for the urban poor to
Conditioned access (O'Sullivan et al., 2019).
Rooftop glasshouses,
fully indoor,
artificially lit plant
factories. Recent
advancements include
production using
vertical stacks to
produce more food
per land area.
Indoor aquaculture is
also included.
1
2
3 5.12.6 Changing Dietary Patterns
4
5 Dietary change in regions with excess consumption of calories and animal-sourced foods to a higher share of
6 plant-based foods with greater dietary diversity and reduced consumption of animal-sourced foods and
7 unhealthy foods (as defined by scientific panels such as EAT-Lancet), has both mitigation and adaptation
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1 benefits along with reduced mortality from diet related non-communicable diseases, health, biodiversity and
2 other environmental co-benefits (high confidence) (Springmann et al., 2016; Springmann et al., 2018; Branca
3 et al., 2019; Henry et al., 2019; Searchinger et al., 2019; Swinburn et al., 2019; Willett et al., 2019;
4 Rosenzweig et al., 2020; Chapter 7.4.2.1.3 and WGIII Chapter 12). Reducing food waste, especially of
5 environment- and climate- costly foods would further extend these benefits (Rosenzweig et al., 2020 and see
6 section 5.11).
7
8 Dietary behaviour is complex: shaped by the broader food system (HLPE, 2017a), the food environment
9 (Herforth and Ahmed, 2015; Turner et al., 2018) and socio-cultural factors (Fischler, 1988). Since most
10 food-related decisions are made at a subconscious level (Marteau et al., 2012), achieving dietary change for
11 personal health reasons has proven difficult: it seems unlikely that dietary change for climate will be
12 achieved without careful attention to the factors that shape dietary choice and behaviour. Food environments,
13 defined as "the physical, economic, political and socio-cultural context in which consumers engage with the
14 food system to make their decisions about acquiring, preparing and consuming food" (HLPE, 2017a): 28),
15 include food availability, accessibility, price/ affordability, food characteristics, desirability, convenience,
16 and marketing.
17
18 There are a range of options to change dietary patterns, but more research is needed in this area, adjusted to
19 the regional, socio-economic, and cultural context. Studies of policy instruments to change diets include
20 changes in subsidies, taxes, marketing regulation and efforts to change the retail physical environment.
21 Subsidies directed at staple foods and animal sourced foods could be shifted towards diversified production
22 of plant-based foods in order to change the relative price of foods and thus dietary choice (Franck et al.,
23 2013; Harris et al., 2021). Taxes on animal-sourced foods that are climate-costly and unhealthy, as defined
24 by scientific panels such as the EAT-Lancet report, could similarly impact relative price (Mbow et al., 2019;
25 Willett et al., 2019). Regulation of marketing could change desirability of climate-unfriendly and unhealthy
26 foods (Willett et al., 2019). Many of the same strategies used to increase sales by conventional food
27 marketing efforts hold potential to change the desirability and people's preferences for plant foods which are
28 strongly shaped by social-cultural norms. Studies have shown that changes to the number, placing, or
29 prevalence vegetarian options on a menu (Bacon and Krpan, 2018; Kurz, 2018; Garnett et al., 2019; Gravert
30 and Kurz, 2019), the relative price of vegetarian options (Garnett et al., 2021)and the "access" (order and
31 distance) to vegetarian options in the retail physical environment (Garnett et al., 2020) can all increase
32 consumption of plant-based foods and decrease meat consumption (Bianchi et al., 2018). Studies on food
33 environment `nudging' methods found that making the vegetarian meal option the default during conference
34 registration or on a meal plan significantly reduced meat consumption (Campbell-Arvai et al., 2012; Hansen
35 et al., 2019b). Studies simply educating people about the negative health and environmental/ climate
36 outcomes of meat consumption have been found to have very little impact (Byerly et al., 2018). More
37 research is needed to understand the potential for motivational crowding in shaping pro-climate dietary
38 choice, as has been demonstrated in development (Agrawal et al., 2015) and conservation interventions
39 (Rode et al., 2015).
40
41 5.12.7 Integrated Multisectoral Food Security and Nutrition Adaptation Options
42
43 Integrated multisectoral strategies that incorporate social protection are effective adaptation responses (high
44 confidence) (Gros et al., 2019; Ulrichs et al., 2019; Medina Hidalgo et al., 2020; Daron et al., 2021; Ilboudo
45 Nébié et al., 2021; Verschuur et al., 2021; 7.4.2, Cross-Chapter Box-GENDER in Chapter 18). Social
46 protection programmes, such as cash transfers, weather index insurance and asset-building activities such as
47 well construction, can support short-term responses to acute food insecurity in response to extreme events,
48 but can also build adaptive capacity longer-term (Table 5.16, Costella et al., 2017; Ulrichs et al., 2019). An
49 assessment of an adaptive social protection programme in the Sahel found that tailored seasonal forecasting
50 can improve responsiveness to climate-related extreme events, but investment in capacity building and
51 dialogue between forecasters, community groups and humanitarian organizations is needed (Daron et al.,
52 2021). Forecast-based financing, which automatically disperses funds when threshold forecasts are reached
53 for an extreme event (Coughlan de Perez et al., 2016), used in Bangladesh prior to a 2017 flood event
54 allowed low-income, flood-prone communities to access better quality food in the short term without
55 accruing debt (Gros et al., 2019).
56
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FINAL DRAFT Chapter 5 IPCC WGII Sixth Assessment Report
1 Differentiated responses based on food security level and climate risk can be effective. A study of drought
2 impacts on food security in Senegal between 1997-2016 recommended different adaptation strategies based
3 on whether the region was a higher risk of acute short-term food insecurity and/or faced higher risk of
4 drought (Table 5.16; Ilboudo Nébié et al., 2021).Given identified linkages between higher temperatures and
5 extreme events with declines in child dietary diversity, safeguarding diverse diets is one important adaptation
6 priority (Niles et al., 2021). Humanitarian responses are appropriate for short-term acute hunger, while in the
7 medium term, home-grown school feeding programmes with diverse foods can support child nutrition and
8 learning, and with local procurement can also increase income and food security of smallholder farmers
9 (Ilboudo Nébié et al., 2021). Farmer associations can manage regional staple food storehouses, in which
10 farmers store their harvest and receive credit, and can sell their harvest later in the season and pay back the
11 credit with interest, strengthening local supplies and farmer income (Ilboudo Nébié et al., 2021).
12
13 A study in Lesotho examined the extent to which climate change increased the likelihood of an acute drought
14 in 2007, and a related food crisis (Verschuur et al., 2021). Given land degradation, reliance on rainfed
15 agriculture and food imports from neighbouring South Africa, the study recommended crop diversification,
16 increased use of drought tolerant crop varieties and expanded trade partners in the medium to long term, to
17 both strengthen regional food production, reduce risk of crop failure, and the likelihood of climate-induced
18 drought from trade partners reducing food imports (Verschuur et al., 2021). A longitudinal study of
19 smallholder coffee farmers in Nicaragua found that crop diversification, alongside crop management and
20 varietal improvement, would help farmers strengthen food security long term in the face of climate hazards
21 such as drought and coffee leaf rust (Bacon et al., 2021). Another medium to long-term adaptation response
22 is to address systemic gender, land tenure and other social inequalities as part of an inclusive approach
23 (Bezner Kerr et al., 2019; Khatri-Chhetri et al., 2020; Bacon et al., 2021). This long-term strategy could be
24 part of a human-rights-based approach (HRBA, 5.12.8)
25
26
27 Table 5.17: Examples of adaptation responses to drought and floods by food security level and time frame. Adapted
28 from Ilboudo Nébié et al. (2021) Table 4, with information from (Bahadur et al., 2015; Costella et al., 2017; Gros et al.,
29 2019; Ulrichs et al., 2019; Medina Hidalgo et al., 2020; Bacon et al., 2021; Verschuur et al., 2021).
Food insecurity level and time frame of
adaptation
Adaptation response to drought or floods Acute, short- Moderate, Chronic, Resilience type
term medium long-term
term
Forecast-based financing (provides X Anticipatory: people
unconditional cash in advance of extreme and systems are
event) better prepared for
Early warning systems / climate services and X X X climate shock by
education for disaster preparation reduced exposure or
Social protection programmes with regular X X vulnerability.
provisions which allow for asset building e.g.,
savings, build informal networks, purchase of
livestock
Humanitarian food aid and malnutrition X X Absorptive capacity:
treatment people or systems
Home grown nutrition-sensitive school X X cope with climate-
feeding programmes related shocks or
Social protection programmes with short-term X systems while and
targeted response e.g., short-term cash immediately after
transfers, food assistance for asset building they occur.
e.g., wells
Weather index insurance program X X X
Regional grain banks run by farmer X X Adaptive capacity:
associations can adjust to long-
Savings, credit and local food procurement X X term climate risks
support for smallholder farmers and disasters reduce
Agroecosystem diversification, other X X vulnerability to future
agroecological practices to strengthen shocks.
ecosystem services in long-term (see Box
5.10)
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Rainwater evacuation infrastructure combined X X
with flood management and waste collection
and urban gardening X X
Drought or flood resistant crop varieties
Expand trade partners beyond climactically X X
connected partners
Gender transformative or responsive X X
agriculture programs
1
2
3 5.12.8 Incorporating Human Rights-based Approaches into Food Systems
4
5 A human rights-based approach (HRBA), endorsed by the United Nations, is one strategy for addressing core
6 inequities that are key drivers for food insecurity and malnutrition of particular groups such as low-income
7 consumers, children, women, small-scale producers and different regions of the world (FAO, 2013; Claeys
8 and Delgado Pugley, 2017; Caron et al., 2018; Le Mouël et al., 2018; Springmann et al., 2018; Tramel, 2018;
9 HLPE, 2019; Willett et al., 2019). Climate change impacts, mitigation and adaptation approaches can also
10 worsen inequities (Eastin, 2018; Borras et al., 2020). HRBA includes core principles of participation,
11 accountability, non-discrimination, transparency, human rights, empowerment, and rule of law, which can be
12 integrated into policymaking and implementation as part of transforming the food system (FAO, 2013; Caron
13 et al., 2018; Toussaint and Martínez Blanco, 2020). The right to wellbeing can serve as the overarching
14 umbrella of HRBA to addressing climate change within food systems and includes a right to health, right to
15 food, cultural rights, the rights of the child and the right to healthy environment (Swinburn et al., 2019). A
16 HRBA has a specific focus on those groups who are vulnerable due to poverty, discrimination and historical
17 inequities and involves meaningful participation of vulnerable groups in governance, design and
18 implementation of adaptation and mitigation strategies, including gender-responsiveness and integration of
19 Indigenous Peoples' knowledge (UNHRC 2017; Caron et al., 2018; Mills, 2018). There can be conflicts and
20 trade-offs, such as between addressing land rights or traditional fishing grounds, the right to food, and
21 addressing climate justice concerns (Mills, 2018; Borras et al., 2020; section 5.13 ). Adaptation strategies
22 that incorporate HRBA include legislation, programmes that address gender inequities in agriculture,
23 agroecology, recognition of rights to land, fishing areas and other natural resources, protection of culturally
24 significant seeds, and community-based adaptation that explicitly involves marginalized groups in
25 governance (Mills, 2018; Tramel, 2018; Huyer et al., 2019; Borras et al., 2020; section 5.14 ).
26
27
28 5.13 Climate Change Triggered Competition, Trade-offs and Nexus Interactions in Land and Ocean
29
30 This section presents information about the impacts generated by competition and trade-offs in food systems
31 and discusses opportunities and challenges associated with the use of the Nexus framework.
32
33 5.13.1 Impacts of Global Land Deals on Land Use, Vulnerable Groups, and Adaptation to Climate
34 Change
35
36 Land deals, also known as large-scale land acquisitions (LSLAs), describe recent changes in access to land
37 globally (Borras et al., 2011). Since 2000, at least 160 million hectares have been under negotiation (Land
38 Matrix, 2021). Land deals surged after the 2007-2008 food price crisis and farmland investment boom
39 (Fairbairn, 2014), with a diverse range of drivers (Arezki et al., 2015; Zoomers and Otsuki, 2017; Conigliani
40 et al., 2018) including land-based climate change interventions (Dunlap and Fairhead, 2014; Davis et al.,
41 2015a; Hunsberger et al., 2017; Franco and Borras, 2019). Examples are the expansion of biofuel crops (e.g.
42 Yengoh and Armah, 2016; Aha and Ayitey, 2017), Afforestation and Reforestation (A/R) projects (Olwig et
43 al., 2016; Richards and Lyons, 2016; Scheidel and Work, 2018), REDD+ (Bayrak and Marafa, 2016; Ingalls
44 et al., 2018), conservation areas (Lunstrum, 2016; Schleicher et al., 2019), renewable energy installations
45 (e.g. Sovacool, 2021), or natural disaster management (e.g. Uson, 2017).
46
47 Land deals raise important social justice questions (Franco et al., 2017; Hunsberger et al., 2017; Borras and
48 Franco, 2018b; Borras et al., 2020; Sekine, 2021) (high confidence). Specific impacts of land deals vary
49 according to their purpose, location, actors, land use history, and procedural aspects. However, multi-case
50 analyses identify severe adverse impacts (Table 5.18). LSLAs are a significant driver of tropical forest loss
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1 (Davis et al., 2020) increasing emissions through deforestation (Liao et al., 2021) and industrialization of
2 agriculture (Rosa et al., 2021). LSLAs entail large water appropriations (Breu et al., 2016; Chiarelli et al.,
3 2016; Adams et al., 2019) affecting local populations' access to water and food security (Dell'Angelo et al.,
4 2018; Veldwisch et al., 2018). By increasing exported crops, and limiting local populations' access to land,
5 LSLAs produce food security risks (Marselis et al., 2017; Müller et al., 2021b). Negative livelihoods impacts
6 arise through enclosure of assets, elite capture (Oberlack et al., 2016), crowding out of small farmers (Nolte
7 and Ostermeier, 2017) and reducing local populations' access to commons (Dell'Angelo et al., 2016; Giger
8 et al., 2019). Indigenous People are affected facing high levels of violence in land acquisition conflicts
9 (Dell'Angelo et al., 2021). The social burdens of land deals tend to be gendered (e.g. Fonjong et al., 2016;
10 Nyantakyi-Frimpong and Bezner Kerr, 2017; Atuoye et al., 2021).
11
12 Local populations can experience declining access to livelihood resources and deteriorating food security,
13 increasing gendered vulnerabilities (Yengoh et al., 2015; Faye and Ribot, 2017; Atuoye et al., 2021).
14 Vulnerable groups displaced by land deals may face higher exposure to climate change (Dell'Angelo et al.,
15 2017). LSLAs affecting common-pool resources governed by Indigenous institutions jeopardize the
16 resilience and adaptive capacity of local socio-ecological systems (Dell'Angelo et al., 2016; D'Odorico et al.,
17 2017; Hak et al., 2018; Haller, 2019; Haller et al., 2020). Growing land tenure insecurity may force farmers
18 to engage in unsustainable farming and forestry practices (Aha and Ayitey, 2017; Gabay and Alam, 2017)
19 and hinder agroecological innovations to manage climate risks (Nyantakyi-Frimpong, 2020b). Social justice
20 concerns and vulnerability of local populations can be addressed by promoting land redistribution and
21 recognition, particularly for customary lands of Indigenous and ethnic minorities; and land restitution to
22 those who were forcibly displaced (Franco et al., 2015; Borras and Franco, 2018a).
23
24
25 Table 5.18: Adverse social and ecological risks and impacts of agricultural land deals on land use and vulnerable
26 groups.
Land use Impacts and implications References (2014- present)
dimensions
Forestry Direct and indirect land use change provoked Multi-case analyses
by LSLAs accelerate deforestation of tropical Davis et al. (2020)
forests globally.
Case study examples
Davis et al. (2015b)
Scheidel and Work (2018), Magliocca et
al. (2020)
Energy use and Expected land use changes provoked by Multi-case analyses
access agricultural LSLAs have high fossil-energy Rosa et al. (2021)
footprints. LSLAs may adversely affect local
population' access to energy resources.
Carbon LSLAs have high carbon footprints resulting Multi-case analyses
emissions from deforestation and industrialization of Liao et al. (2021)
agriculture. Rosa et al. (2021)
Case study examples
Johansson et al. (2020)
Liao et al. (2020)
Water use and LSLAs frequently involve water Multi-case analyses
access appropriations, which may affect access to Breu et al. (2016)
water, traditional agriculture, and the human Chiarelli et al. (2016)
right to food of local populations. Dell'Angelo et al. (2018)
Food security LSLAs pose food security risks by re- Case study examples
and nutrition orienting crop production to nutrient-poor Adams et al. (2019)
crops predominantly destined for export, Tejada and Rist (2018)
Multi-case analyses
Cristina Rulli and D'Odorico (2014)
Mechiche-Alami et al. (2021)
Marselis et al. (2017)
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and/or excluding local populations from Müller et al. (2021b)
agricultural land.
Conceptual studies
Häberli and Smith (2014)
Livelihoods LSLAs frequently provoke adverse livelihood Case study examples
impacts and increased livelihood Shete and Rutten (2015)
vulnerability of local populations. Mabe et al. (2019)
Bruna (2019)
Hules and Singh (2017)
Moreda (2018)
Atuoye et al. (2021)
Multi-case analyses
Davis et al. (2014)
Oberlack et al. (2016)
Nolte and Ostermeier, 2017)
Vandergeten et al. (2016)
Schoneveld (2017)
Conceptual studies
Zoomers and Otsuki (2017)
Indigenous LSLAs have adverse impacts on Indigenous Case study examples
People and peoples and lands, including land Richards and Lyons (2016)
commons encroachment, dispossession, and Shete and Rutten (2015)
displacement. Yengoh and Armah (2016)
Gender Land deals frequently target common land Mabe et al. (2019)
and may increase the vulnerability of Gyapong (2020)
Impacts on customary, traditional, and Indigenous Multi-case analyses
other climate systems common property, while reducing Dell'Angelo et al. (2016)
their adaptive capacity. Giger et al. (2019)
Dell'Angelo et al. (2021)
Impacts and implications of land deals are
frequently suffered in different ways among Conceptual studies
genders. Haller et al. (2020)
LSLAs may undermine mitigation and Case study examples
adaptation initiatives and other land uses Olwig et al. (2016)
Moreda (2017)
Montefrio (2017)
Scheidel and Work (2018)
Konforti (2018)
Pietilainen and Otero (2019)
Mingorría (2018)
Bukari and Kuusaana (2018)
Haller (2019)
Hak et al. (2018)
Gabay and Alam (2017)
Imbong (2021)
Case study examples
Tsikata and Yaro (2014)
Yengoh et al. (2015)
Fonjong et al. (2016)
Nyantakyi-Frimpong and Bezner Kerr
(2017)
Elmhirst et al. (2017)
Bottazzi et al. (2018)
Ndi (2019)
Osabuohien et al. (2019)
Porsani et al. (2019)
Atuoye et al. (2021)
Multi-case analyses
Carter et al. (2017)
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change relevant for climate change mitigation and Case study examples
mitigation and adaptation Borras et al. (2020)
adaptation Gabay and Alam (2017)
initiatives Nyantakyi-Frimpong (2020b)
Scheidel and Work (2018)
Rodríguez-de-Francisco et al. (2021)
Other LSLAs expected to provoke lasting global
environmental environmental change (Lazarus, 2014);
impacts LSLAs are a potential driver of slope
instability (Chiarelli et al., 2021); LSLAs
affect natural habitats such as tiger
landscapes (Debonne et al., 2019); LSLAs
jeopardize biodiversity (Balehegn, 2015).
1
2
3 5.13.2 Trade-offs Generated by Agricultural Intensification and Expansion
4
5 Agricultural intensification seeks to increase agricultural productivity per input unit, reducing the pressure on
6 land use, generating positive impacts in greenhouse gas emissions (Mbow et al., 2019), but valuing the final
7 effect requires common metrics in terms of carbon capture or emission reductions (Searchinger et al., 2018).
8 It has been suggested to address multiple Sustainable Development Goals (SDG2, SDG13, SDG15), but only
9 occasionally leads to simultaneous positive ecosystem service and well-being outcomes (Rasmussen et al.,
10 2018). When the process relies only on increasing input use there is a risk of generating adverse outcomes
11 that may override positive effects, such as CO2 emissions, (McGill et al., 2018); NOx emissions (Hickman et
12 al., 2017), soil salinization and groundwater depletion (Doody et al., 2015; Daliakopoulos et al., 2016;
13 Fragaszy and Closas, 2016; Foster et al., 2018; Flörke et al., 2019). Agricultural intensification could meet
14 short-term food security and livelihood goals, but reduces biological and landscape diversity, and ecosystem
15 services (high confidence) (Campbell et al., 2017; Balmford et al., 2018; Springmann et al., 2018; Ickowitz
16 et al., 2019; Mbow et al., 2019). Agricultural intensification can also affect livelihoods of small-scale
17 producers, compromising food security. It can increase low-waged casual farm work, increasing gender and
18 income inequality (Bigler et al., 2017; Clay and King, 2019; Table 5.18).
19
20
21 Table 5.19: Case studies of trade-offs and negative outcomes associated with Agricultural Intensification on
22 biodiversity and ecosystem services.
Ecosystem service Trade-offs / Negative Outcomes References
Provisioning: Water quality Negative impacts on ephemeral Dalu et al. (2017)
wetlands
Provisioning: Water availability Contribution to water scarcity Satgé et al. (2019)
Supporting: Soil Increasing erosion risk Govers et al. (2017)
Regulating: Climate Reduced soil organic carbon Olsen et al. (2019)
Regulating: Pest control sequestration Emmerson et al. (2016)
Reduced level of biological
Cultural: Recreational control of pests: Reduced number DeBano et al. (2016)
of insectivorous birds
Reduction on river wildlife
Biodiversity Reduced global biodiversity Newbold et al. (2015), Egli et al.
Biodiversity (2018), Beckmann et al. (2019)
Biodiversity Reduction of taxonomic diversity Jeliazkov et al., (2016), Kehoe et
al. (2017), Banerjee et al. (2019)
Negative impacts on mean Olivier et al. (2020)
population stability
23
24
25 Land available for provisioning ecosystem services is declining in many places because of agricultural
26 expansion, bioenergy crops and reforestation for mitigation (Kongsager, 2018), with adverse climate impacts
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1 (Froese and Schilling, 2019). Cropland expansion can deteriorate biodiversity (Delzeit et al., 2017), water
2 quality (Ayala et al., 2016) and carbon storage (Goldstein et al., 2012) and increase water demands
3 (Yokohata et al., 2020).
4
5 A systems-based perspective on land use is needed to address climate change impacts on nutrition security,
6 and ecosystem services (Springmann et al., 2018; IPCC, 2019b; Willett et al., 2019). Land sparing sets aside
7 some land for conservation purposes and intensifies production on farmland (Balmford et al., 2018; Benton
8 et al., 2018; IPCC, 2019b) with potential to offset greenhouse gas emissions (Lamb et al., 2016).
9 Alternatively `land sharing' approach, through principles such as minimizing fossil-fuel based inputs,
10 maximizing synergies, addressing both climate change mitigation and adaptation and biodiversity (Kremen
11 and Miles, 2012; Kremen, 2015; Kremen and Merenlender, 2018; HLPE, 2019; section 5.14, Box on
12 Agroecology). Community-managed initiatives can address biodiversity and ecosystem conservation,
13 livelihoods, food provisioning and other ecosystem services (Kremen and Merenlender, 2018; HLPE, 2019).
14
15 The concept of sustainable intensification has emerged, looking for enhancements in environmental
16 outcomes, while maintaining or increasing agricultural systems performance. There is a potential to find
17 synergies between agricultural production and landscape systems if systems are design to operate within
18 planetary boundaries (Rockström et al., 2017; Liao and Brown, 2018; Pretty, 2018; Pretty et al., 2018).
19
20 5.13.3 Competition Between Food Systems in Land and Ocean
21
22 Livestock and aquaculture feeds utilize crops such as soyabean and maize, with food conversion efficiencies
23 similar in chicken and Atlantic salmon, and higher in pigs and cattle (Troell et al., 2014; Fry et al., 2018b;
24 Fry et al., 2018a). Use of wild fish meal and oil has been decreasing, partly due to concerns regarding
25 vulnerable small pelagic fish stocks (Bindoff et al., 2019). The instability of wild fish stocks has increased
26 terrestrial crop feed components (Troell et al., 2014; Blanchard et al., 2017; FAO, 2017; Cottrell et al.,
27 2018). The use of wild fish in fish feeds that may have been directly consumed may put low-income
28 households at risk of food insecurity (Troell et al., 2014). An increasing demand for aquaculture products
29 intensifies competition for feed supplies (medium confidence) (Troell et al., 2014; Blanchard et al., 2017).
30 Increases in demands for animal protein and shifts to pescatarian diets will increase the existing competition
31 for land resources, particularly in low and medium income countries, with negative impacts on food security
32 (Makkar, 2018), but may be mitigated by dietary changes, novel feeds and food waste usage for aquatic
33 systems (Berners-Lee et al., 2018; Hua et al., 2019; Cottrell et al., 2020).
34
35 Competition over use of major aquaculture feed crops (Fry et al., 2016) with terrestrial livestock (Troell et
36 al., 2014), and fish use by terrestrial livestock, will also place pressure on fish and crop resources (medium
37 confidence) (Cottrell et al., 2018). Increases in feed prices will affect fish and meat prices (Troell et al.,
38 2014), and changes in agriculture will be needed to satisfy aquaculture demands (Blanchard et al., 2017).
39 Aquaculture and livestock dietary components may also compromise crops and forage fish that provide
40 essential nutrients for low-income households increasing nutritional insecurity, in regions of sub-Saharan
41 Africa, Asia and Latin America (Troell et al., 2014). Waste fish products can supplement fish meal and oil to
42 reduce competition for feed, as well as reducing use of fish that could go to human consumption (medium
43 confidence) (Little et al., 2016; Shepherd et al., 2017; Dave and Routray, 2018; Naylor et al., 2021). Use of
44 algae, bacteria, yeast and insect diets could replace fishmeal for aquaculture (Cohen et al., 2018; Hua et al.,
45 2019; Cottrell et al., 2020), not affecting nutritional profiles (Campanaro et al., 2019) and fish could be
46 reared on waste by-products of other food production systems (Bava et al., 2019). Complete fish oil
47 substitutions with microalgae may be possible without compromising omega-3 contents, but energy usage in
48 diet production should be considered Cottrell et al. (2020). Substitutions of plant-based and alternative feeds
49 may decrease food conversion efficiencies (Cottrell et al., 2020), affect omega-3 content of farmed seafood
50 (Fry et al., 2016; Shepherd et al., 2017), be problematic for the fish themselves (Little et al., 2016; Naylor et
51 al., 2021) and lead to reduced productivity (Shepherd et al., 2017).
52
53 Competition will be heightened by other climate impacts, such as changes in water availability. Water usage
54 is relatively high in animal production (Abraham et al., 2014; Sultana et al., 2014; de Miguel et al., 2015;
55 Palhares and Pezzopane, 2015; Weindl et al., 2017). In some areas, increased demand for plant-based animal
56 feeds will be affected by sea level rise and competing usage of available freshwater with other users, and
57 ecosystem needs (Karttunen et al., 2017).
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1
2 5.13.3.1 Agricultural and river run-off
3
4 Flooding on agricultural land will enhance nutrient run-off, creating eutrophication and increasing hamr
5 phytoplankton blooms, affecting fisheries and aquaculture, human health and ecosystem biodiversity.
6 Changes in precipitation, monsoons, run-off and flood potential combine with deforestation and poor sewage
7 treatment, resulting in larger volumes of nutrients and freshwater reaching coastal ecosystems (Jin et al.,
8 2018; Nasonova et al., 2018; Tamm et al., 2018). Rising surface temperatures, ocean acidification and
9 eutrophication will increase pathogenic Vibrio bacterial loads in marine organisms with potential transfer to
10 humans (Hernroth and Baden, 2018). Shallow and microtidal estuaries will be more vulnerable to changing
11 river runoffs and saltwater intrusions, eutrophication, and hypoxia (high confidence) (IPCC, 2019c).
12
13 5.13.4 Maladaptation Responses and sustainable solutions
14
15 Maladaptation can result in three types of outcomes (Juhola et al., 2016) 1) Rebounding vulnerability: short
16 term adaptations that decrease adaptive capacity and hinder future choices; 2) Shifting vulnerability: larger-
17 scale adaptation actions that produce spill-over effects in other locations; 3) Eroding sustainable
18 development: adaptation strategies which increase emissions, deteriorate environmental conditions and/or
19 social and economic values (Tables 5.20 and 5.21).
20
21 Existing climate policies do not adequately consider tradeoffs, adaptive limits, cumulative costs and potential
22 risks of maladaptation (robust evidence and medium agreement) (Dovie, 2017; Holsman et al., 2019; IPCC,
23 2019b; Work et al., 2019; Thomas, 2020: Table 5.19 ). Government policies are seldom coordinated across
24 scales and often focused on regional short-term risks (medium evidence, medium agreement) (Dovie, 2017;
25 Holsman et al., 2019; Rahman and Hickey, 2019; Butler et al., 2020). Past development trajectories and
26 dominant political economic structures may narrow adaptation pathways, be restrictive and increase the
27 vulnerability of particular groups (Paprocki, 2018; Quan et al., 2019; Rahman and Hickey, 2019; Work et al.,
28 2019).
29
30 Case Studies of Maladaptation
31
32 Large-scale irrigation project in Navarre, Spain
33
34 Many small-scale producers could not afford the irrigation investment and had to sell or rent their land to
35 those who joined the irrigation project. Many large-scale farmers using irrigation switched to corn and forage
36 and dropped crops with high labour costs. Water costs are now paid to a private company, and small-scale
37 farmers lost access to communal water rights. The project increased inequity, land concentration and lowered
38 crop diversity, with small scale producers more vulnerable to climate change. Large-scale intensive farmers
39 are more exposed to crop price volatility than to climate vulnerability but have greater access to subsidies
40 and water rights (Albizua et al., 2019).
41
42 Constraining adaptation: previous agricultural development pathways in India
43
44 Government policies in colonial and postcolonial India, invested in infrastructure, export production and
45 synthetic input use (Gupta, 1998; Davis, 2001), setting the stage for current development trajectories, closing
46 out other adaptive options. Although such policies increased national food production, they failed to address
47 high levels of malnutrition, worsening regional inequalities, degraded natural resources, and an agrarian debt
48 crisis (Singh, 2000; Gupta et al., 2016; Gajjar et al., 2019). Agricultural livelihoods are increasingly
49 considered unviable, with lower adaptive capacity of farmers, high debt levels (Gupta et al., 2016),
50 Indigenous and local knowledge loss and denigration (Kumar, 2016) alongside lower crop diversification
51 (Srivastava et al., 2016). Government institutions aimed at infrastructure often lack adaptive capacity needed
52 to address rural livelihoods (Singh et al., 2017; Gajjar et al., 2019).
53
54
55 Table 5.20: Summary of the emerging literature on potential risks of maladaptation.
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Description of Potential Negative impacts Maladaptation Regions Groups affected References
adaptation Typology (1= and
strategy Increases GHG emissions, water Rebounding countrie
pollution, possible insect vulnerability, s
Agricultural resistance and costs to farmers, 2= shifting or affected
intensification to possibly increased inequities. 3=eroding
increase May constrain adaptation policy SDGs) United Farmers, Gajjar et al.
productivity, in options for development 1,2,3 States, pastoralists / (2019),
places with pathways due to lock-ins and Africa, nearby Guodaar et al.
heavy rainfall trade-offs which entrench Asia communities who (2019),
events or rising inequities. (India, rely on water; Houser and
pest/disease China), small-scale Stuart (2019),
incidence Europe farmers who Neset et al.
cannot afford (2019b), Quan
Livelihood Increases GHG emissions and 1,3 Africa inputs; et al. (2019),
(Norther Policymakers. Young and
diversification deforestation rates n Ismail (2019)
Ghana), Small-scale food Antwi-Agyei
into charcoal South producers; et al. (2018),
America Indigenous Zavaleta et al.
production (Peru) communities (2018), Young
Northern and Ismail
Irrigation Reduces long term potential for 1,2 and 3 China; Food producers (2019)
projects or hydropower and groundwater India; who rely on
programs either availability, can increase Mediterr irrigation; Doody et al.
large-scale salinization and cost of water. anean consumers who (2015),
and/or that rely areas; rely on Herbert et al.
on groundwater Can increase cost of farming Europe; hydropower or (2015), Barik
and debt levels of farmers, United groundwater; et al. (2016),
squeezing out small-scale States Small-scale Daliakopoulos
producers. diversified et al. (2016)
South producers who Fragaszy and
Can reduce water availability America cannot afford Closas (2016)
for aquaculture. (Bolivia) irrigation; Dalin et al.
; Pacific Aquaculture. (2017), Foster
Investment in May displace local varieties, 1, 3 Islands; et al. (2018)
Asia Small scale food Hanacek and
improved reduces diversity if too much producers; Rodríguez-
Indigenous Labajos
cultivars or shift policy/extension emphasis falls communities (2018),
Albizua et al.
to different on a few varieties; may increase (2019), Flörke
et al. (2019)
crops risk of crop loss from pests, Gajjar et al.
(2019), Xu et
disease, drought if reliant on a al. (2019)
Mcleod et al.
few varieties; may increase (2018),
Meldrum et al.
(2018), Neset
et al. (2019b)
Rahman and
Hickey (2019)
fertilizer use; may lead to loss
of Indigenous or local
knowledge
Migration Can increase the workload of 1,3 Asia, Small-scale low- Bettini et al.
Africa, income food (2017),
people left behind (often Central producers or rural Paprocki
and workers; women (2018), Chen
women), worsen rural South et al. (2019),
America Jacobson et al.
livelihoods and food insecurity;
can lead to worsened living
conditions, food security and
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poverty in precarious urban (2019),
conditions, may increase Michael et al.
vulnerability to flooding in (2019), Young
urban locations. and Ismail
(2019), Singh
May affect mental health by and Basu
disrupting eisting social ties (2020), Torres
and Casey
Coastal sea Can degrade coastal mangroves, 1,2,3 Asia, Coastal (2017)
walls, deplete open freshwater South communities Dovie (2017),
embankments, fisheries, sedimentation of Pacific dependent on Owusu-Daaku
canals, riverbed rivers, reduce fish diversity and Islands, mangroves and (2018),
draining and increase flooding risk for west fisheries; low- Freduah et al.
dikes to reduce particular vulnerable groups; Africa income rural (2019), IPCC
flood risk may divert funds from other households with (2019c),
more sustainable measures. Global seasonal Rahman and
dependence on Hickey
River regulation May have negative impacts on 2,3 West inland fisheries (2019), Nunn
for hydropower inland fisheries. Africa et al. (2020)
Small-scale inland Seddon et al.
Government Government confiscation of 1,3 fisheries and low- (2020),
policies to fishing nets to prevent rapid income rural Thomas
manage coastal decline of fish population can 2 households with (2020)
fisheries which worsen livelihoods for small 1,2,3 seasonal FAO (2018c)
promote scale fishers; Subsidies of pre- 2,3 dependence on
overcapitalizatio mixed fuel to allow fishers to inland fisheries FAO (2018b),
n of fisheries, stay out longer due to shifting Coastal small- Freduah et al.
including index fish populations may increase scale fishery (2019),
insurance total number of fishers and total communities Holsman et al.
fish catch. Insurance payments (2019),
Consultative may benefit larger-scale fishing Sainsbury et
stakeholder fleets and push out small-scale al. (2019)
systems in fishers.
fisheries or May encourage inertia in the North Coastal fisheries Holsman et al.
flood system due to a few powerful America; (2019),
management stakeholders participating in the Asia Rahman and
Climate services consultative process. Hickey (2019)
Nature-based May reinforce existing North Coastal fisheries, Furman et al.
solutions inequalities if climate services America Farming (2014),
mitigation and are attuned to powerful Webber
adaptation stakeholders in industry, (2017), Nost
services are privatized, there are (2019)
limited ways to get input from
vulnerable groups and planning Africa, Indigenous Lunstrum et
budgets that use climate Asia, and communities; al. (2016),
services are constrained. South small-scale Work et al.
Can displace local communities' America producers and (2019),
access to land for food
production and other ecosystem
services, have negative impacts
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FINAL DRAFT Chapter 5 IPCC WGII Sixth Assessment Report
strategies such on Indigenous rights, reduce e.g., forest dependent Seddon et al.
Indonesi communities (2020), Cross-
as reforestation biodiversity and may not reduce a, Working
Amazon, Indigenous Group Box
or afforestation GHG as much as conserving west- communities BIOECONO
central MY this
natural forests and wetlands or Africa Chapter)
South Lemos et al.
agroecological systems such as America (2016),
(Amazon Zavaleta et al.
agroforestry or other means to ian (2018)
region of
increase soil C. Peru);
Africa
Social safety Decline in Indigenous 1,3 (South
Africa)
nets provide knowledge of and collective
funds which approaches to seasonal
increases adaptation strategies in hunting,
consumption of fishing, and food production;
processed, shift in dietary patterns to more
purchased food processed and non-local foods;
and erodes reduction in farming. Reduced
Indigenous capacity to respond to hazards
knowledge through dispersed settlement
e.g. hunting, fishing, wild food
collection. Increased population
density increases deforestation
and vulnerability.
Community- Local gender and other social 1,3 Pacific Small scale food McNamara
Islands; producers; and Buggy
based adaptation inequities can lead to `elite Africa; Indigenous (2017) Jamero
Asia communities, et al. (2018),
strategies capture' that reinforces other vulnerable Singh (2018)
groups such as Bezner Kerr et
inequality; power dynamics women and low al. (2019)
caste groups Piggott-
between the funding agency and McKellar et
al. (2020),
local participants can make Westoby et al.
(2020)
local community involvement
tokenistic. There may be
inadequate attention to socio-
cultural preferences and
structural factors which foster
maladaptation such as
inappropriate crops or animals
used.
Digital Could lead to net job losses, 2,3 North Farmworkers; (Furman et al.
America, small-scale food (2014), Rotz
agriculture for particularly for those with lower South producers who et al. (2019)
America, cannot afford
increased levels of education; increased Europe, digital
Asia, technologies; rural
precision and surveillance and employer parts of communities.
Africa.
efficient use of scrutiny of lower-skilled
fertilizers, workers in fields, greenhouses
pesticides, water and processing plants and
warehouses; separate workers
from employees and companies
who collect data. Overall
increased racial, income
inequities and unequal working
conditions.
Increased credit High interest rates, tight return 1,3 Asia Low-income Rahman et al.
(Banglad landless people or (2018)
access for policies could increase debt esh) small-scale
producers
livelihood loads for low-income
diversification households, which could
rebound vulnerability.
Household may invest in
livelihood strategies which are
vulnerable to climate change
impacts, or which increase
GHG.
Aquaculture Large-scale coastal aquaculture 2,3 Asia Small-scale mixed Paprocki
(Banglad systems including (2018),
can increase soil salinization esh) rice production Paprocki and
and other rural Huq (2018)
and reduce land available for livelihoods
other food production and can
increase migration
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1
2
3 Adaptation options that consider adverse effects for different groups reduce the risk increasing vulnerability,
4 negatively affecting socio-economic factors to deal with climate impacts, or impeding efforts to implement
5 sustainable development goals (high confidence) (Juhola et al., 2016; Antwi-Agyei et al., 2018; Paprocki and
6 Huq, 2018; Holsman et al., 2019; IPCC, 2019b; Stringer et al., 2020). Adaptation methods considering
7 historical roots of current vulnerabilities can identify viable solutions, which are difficult to undertake
8 because of path dependencies (high confidence) (Ribot, 2014; Albizua et al., 2019; Gajjar et al., 2019;
9 Paprocki, 2019; Thomas, 2020). Planning techniques that model outcomes for different groups from different
10 adaptation options could be put in place to diminish maladaptation risks (Rodríguez et al., 2019).
11
12 Inclusive planning initiatives such as community-based anticipatory adaptation combined with `two-way
13 learning' that considers future scenarios and different adaptation pathways, can prevent maladaptation (high
14 confidence) (Dovie, 2017; Bezner Kerr et al., 2019; Neset et al., 2019a; Rahman and Hickey, 2019; Work et
15 al., 2019; Butler et al., 2020; Nunn et al., 2020; Piggott-McKellar et al., 2020; Westoby et al., 2020; Table
16 5.20). Promising policy management tools combine temporal scales, mitigation-adaptation interactions,
17 consider political dynamics, socio-economic impacts and trade-offs for vulnerable groups, long-term support
18 for policy leaders, efforts to establish livelihood `niches' and ongoing participatory evaluation (Dovie, 2017;
19 Holsman et al., 2019; Rahman and Hickey, 2019; Work et al., 2019; Butler et al., 2020). A focus on the most
20 disadvantaged groups can help small-scale producers at higher risk to prevent maladaptation (FAO, 2018c).
21 Governance mechanisms have emerged that consider food security, socio-cultural factors, land and water
22 rights, using participatory, inclusive `two-way learning' methods that involve vulnerable people alongside
23 government (IPCC, 2018; Holsman et al., 2019; IPCC, 2019b; Rahman and Hickey, 2019; Butler et al.,
24 2020).
25
26
27 Table 5.21: Strategies to avoid maladaptation (adapted from (Magnan, 2014; Lim-Camacho et al., 2015; Sovacool et
28 al., 2015; FAO, 2018b; Paprocki and Huq, 2018; Sainsbury et al., 2019).
Type of Strategies
maladaptation
Environmental 1. Prevent negative effects on ecosystem services in situ (e.g., habitat degradation, pollution)
that increases exposure to climate hazards.
2. Avoid increasing pressure on other socio-ecological systems.
3. Ensure ecosystems' protective role as natural buffer zones is sustained against current and
future climate-related hazards, such as storms, floods, and sea level rise.
4. Provide some duplication and ensure flexibility of adaptation strategies to reduce risk
because of uncertainties about climate change impacts and ecosystem response (e.g.,
agrobiodiversity to reduce pest outbreaks).
Socio-cultural 1. Consider local social characteristics and cultural values that could affect risks and
environmental dynamics.
2. Support local skills and knowledge related to climate-related hazards.
3. Support capacity-building for new skills needed by local communities.
Political- 1. Consider the political dynamics and power imbalances and create inclusive processes to
Economic involve the most vulnerable and disadvantaged groups in decisions.
2. Work to reduce socio-economic inequalities, poverty, and food insecurity.
3. Support livelihood diversification.
4. Focus on the impacts of adaptation on the poorest, structurally disadvantaged, and
vulnerable groups, and take power imbalances into account.
5. Work across the full supply chain to consider linkages and possible ripple effects.
29
30
31 5.13.5 Climate Change and Climate Response Impacts on Indigenous People
32
33 Indigenous people and ethnic minorities, many of them having special cultural associations to local foods,
34 are particularly vulnerable to climate change due to changes in the availability of wild foods, crop failure and
35 food production loses or via increased food prices (Norton-Smith et al., 2016; Otto et al., 2017).
36
37 Changes in sea level rise or coastal erosion can reduce ecosystem services to a point where either subsidies
38 are used to enable human populations to remain in their place of attachment, or ultimately to displace coastal
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1 residents thereby removing connections to places of intrinsic value. For example, the United Houma Nation
2 in Louisiana is experiencing coastal land loss, sea level rise and strong Gulf hurricanes, which leads to the
3 relocation of some tribes causing loss of Houma identity (Sullivan and Rosenberg, 2018). Another example
4 is the relocation of Alaska Native communities due to climate change (Hamilton et al., 2016)
5
6 Expansion of agriculture can bring distress to Indigenous communities because of environmental
7 deterioration and the stress associated with relocation or displacement (Otto et al., 2017). Afforestation and
8 reforestation (A/R) programs can also bring inequalities to Indigenous communities (Godden and Tehan,
9 2016) and even violent displacement with tragic results (Celentano et al., 2017). A/R programs can
10 negatively affect a range of substantial and procedural Indigenous Peoples' rights entrenched in international
11 human rights law (Table 5.22) and their potential for climate change adaptation (high confidence).
12
13 A significant proportion of land targeted for A/R projects is inhabited and used by Indigenous Peoples and
14 local communities (Cagalanan, 2016). Indigenous Peoples have rights to and/ or manage at least 37.9 million
15 km2 of land and influence land management across at least 28.1% of the land area (Garnett et al., 2018). At
16 least a quarter of the global land area is traditionally owned, managed, used or occupied by Indigenous
17 Peoples overlapping 35 to 40 per cent of the area that is formally protected (Garnett et al., 2018; Brondizio et
18 al., 2019). In many cases, A/R is implemented in areas where tenure rights are insecure and Indigenous
19 Peoples' rights are in risk of being disregarded (Naughton-Treves and Wendland, 2014; Kohler and
20 Brondizio, 2017; Garnett et al., 2018) (medium evidence, high agreement). Many projects are also found in
21 areas where complex socio-political contexts challenge management (Jurjonas and Seekamp, 2019). It is
22 anticipated that A/R projects will create huge pressures on existing land uses and generate further land use
23 conflicts (Aggarwal, 2014; Robinson et al., 2014; Paul et al., 2016; Brancalion and Chazdon, 2017; Pye et
24 al., 2017; Bond et al., 2019). In addition, many afforestation projects are conducted in regions that are not
25 bio-climatically suitable, leading to the degradation of ecosystems that are key to local livelihoods (Veldman
26 et al., 2015; Robinson et al., 2016b).
27
28
29 Table 5.22: Indigenous rights recognized in international human rights law negatively affected by A/R projects.
Negative impacts of monoculture Indigenous Degree of References
plantations (and other A/R projects) Peoples' rights certainty
affected
Local community not informed, not Right to self- Medium Aggarwal (2014),
adequately consulted, not provided means determination; evidence, Maraseni et al. (2014),
for meaningful participation in project consultation and high Ravikumar et al. (2015),
design, implementation, and monitoring free, prior and agreement Bayrak and Marafa
(with specific attention to women and poor informed consent (2016), Loaiza et al.
households); disruption or non-recognition (FPIC); (2016), Vijge et al.
of local or traditional institutions; elite participation (2016), Pye et al. (2017),
capture; no access to third-party grievance Ryngaert (2017), Wolde et
mechanisms. al. (2016), Brancalion and
Chazdon (2017), Seddon
et al. (2020)
Evictions and displacement; dispossession; Right not to be Medium Mingorría (2014),
livelihood precarity; and criminalization of forcibly removed evidence, Richards and Lyons
forest-dwelling people high (2016), Witasari (2016),
agreement Corbera et al. (2017), Pye
et al. (2017), Sarmiento
Barletti et al. (2020),
Brancalion and Chazdon
(2017)
Loss, transfer or acquisition of land. A/R Rights to land and Limited Aggarwal (2014),
projects involve changes in land use for territory evidence, Robinson et al. (2014),
medium to long term and often lack high Bayrak and Marafa
consideration for local dynamics including agreement (2016), Pye et al. (2017),
land tenure and competition with Bond et al. (2019)
agriculture or conservation.
A/R projects exacerbate conflicts, Rights to land and Limited Aggarwal (2014)
accentuate uneven power relations,
territory evidence,
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increase existing inequalities within Rights to land and low Lyons et al. (2014),
communities, exclude the poor and deepen territory (with agreement Wolde et al. (2016),
structural injustices including racism and implications for Brancalion and Chazdon
stigmatization. food security) Limited (2017), Mousseau and
Forest expansion intensifies already acute evidence, Teare (2019)
land shortages for growing food and forces Right to water high Veldman et al. (2015),
villagers to take their animals for grazing agreement Aitken and Bemmels
to new areas as a result of forests being (2016), Brancalion and
fenced off. Robust Chazdon (2017), Pye et al.
Decreased stream flows and water yields; evidence, (2017), Bond et al. (2019),
exacerbated water scarcity. high Seddon et al. (2020)
agreement Richards and Lyons
(2016), Johansson and
Pollution of lakes with agrochemicals; Right to a healthy Medium Isgren (20179, Pye et al.
heavy chemical use including the spread of environment evidence, (2017)
pesticides, herbicides and fertilizers by high
aircraft and other means causing runoff Right to a healthy agreement Richards and Lyons
into rivers environment, (2016), Holmes et al.
Encroachment on other ecosystems with right to food Medium (2017), Seddon et al.
devastating impacts on biodiversity; evidence, (2020), Ennos et al.
pressures on ecologically sensitive Right to a healthy high (2019)
ecosystems such as wetlands; reduction in environment, agreement
seed-dispersing animals; planted tree right to food Veldman et al: (2015),
species becoming invasive, introducing Robust Cormier-Salem and
pests and diseases evidence, Panfili (2016), Brancalion
Loss of habitat, degradation of savannas, high and Chazdon (2017),
native grasslands (grassy biomes) or agreement Bond et al. (2019),
mangroves wrongly characterized as Seddon et al. (2020)
degraded land suitable for afforestation Dotchamou et al. (2016),
Johansson and Isgren
Direct negative health impacts; loss of Right to health Limited (2017)
traditional medicine evidence,
Right to cultural medium Lyons et al. (2014),
A/R projects affect burial sites as for many identity and to agreement Gabriel and Mangahas
communities, the forest is also the resting main and control Limited (2017), Mousseau and
place for deceased ancestors their traditional evidence, Teare (2019)
knowledge high
Loss of traditional or Indigenous Right to cultural agreement Bayrak and Marafa (2016)
ecological knowledge and forest identity and
management practices traditional Limited Boyd et al. (2007),
knowledge evidence, Aggarwal (2014),
Increased labor burden. Benefit sharing by Right to an medium Cagalanan (2016),
direct cash transfer or in-kind modalities adequate standard agreement Witasari (2016), Corbera
tends to not compensate lost income of living; right to Medium et al. (2017), Pye et al.
opportunities. Some projects bring decent work; right evidence, (2017)
employment opportunities, but these are to benefit-sharing medium
short term and limited and rarely viable if agreement
the opportunity cost of land and labour is
considered. Poor farmers may drop out in
order to regain access to their land for uses
that provide cash returns in the shorter
term.
1
2
3 Until 2010, most A/F projects had technical, carbon-related goals and did not consider issues of livelihoods,
4 community involvement or broader ecosystem impacts (Wolde et al., 2016). New strategies such as Nature-
5 based Solutions (Seddon et al., 2020) and Forest and Landscape Restoration (Brancalion and Chazdon, 2017)
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1 integrate a larger set of social and environmental objectives. Indigenous Peoples enjoy a range of co-benefits
2 of A/F initiatives such as improved habitat, fire management or protection from climatic shocks such as
3 drought (Robinson et al., 2016b; Seddon et al., 2020) provided they are able to manage carbon funds
4 collectively, meet the monitoring and reporting requirements, and protect forests from illicit uses and natural
5 disasters (Wolde et al., 2016).
6
7 Policies and safeguards attached to specific A/R initiatives determine their impact (high confidence) (Talor,
8 2015; West, 2016; Brancalion and Chazdon, 2017). In countries where there is a great level of devolution of
9 rights to Indigenous Peoples there is a risk that the A/R agenda will lead to recentralization (limited evidence,
10 medium agreement) (Bayrak and Marafa, 2016). Some A/R initiatives specify the need to respect the rights
11 of Indigenous Peoples and local communities and protect biodiversity (medium evidence, high agreement)
12 (Seddon et al., 2020).
13
14 Local communities' ability to participate in project design, implementation and monitoring is directly linked
15 to the autonomy and independence of local institutions (Pye et al., 2017), their ability to formulate by-laws
16 (Wolde et al., 2016) and handle funds in a transparent way (medium evidence, high agreement) (Witasari,
17 2016). It is further dependent on cohesion in the community (Cagalanan, 2016), the existence of clear rules
18 delineating community membership and the presence of elders and community members with relevant local
19 knowledge (Robinson et al., 2016b) as well as gender and out-migration dynamics affecting participation
20 structures (robust evidence, medium agreement) (Cormier-Salem and Panfili, 2016; Witasari, 2016; Wolde et
21 al., 2016; Jurjonas and Seekamp, 2019).
22
23 5.13.6 Increased Presence of Financial Actors in the Agrifood System
24
25 Financial actors, markets, institutions, and incentives have gained importance in agricultural commodities
26 and farmland markets in the past two decades (Clapp and Isakson, 2018; Fairbairn, 2020).New types of
27 investment vehicles such as commodity index funds that track prices of commodities and farmland have
28 emerged and the use of older vehicles such as forward and futures markets has increased (Schmidt and
29 Pearson, 2016; Clapp and Isakson, 2018). These trends are connected to climate change as financial
30 investments are influenced by the likelihood that climate change will increase commodity and farmland price
31 variability (medium confidence) (Cotula, 2012; Isakson, 2014; Tadesse et al.).
32
33 Financial investors pool their investments through intermediaries, alongside other dynamic forces in the
34 global economy, making unambiguous assessments of their effect difficult (Clapp, 2014; Clapp, 2017).
35 However, assessment of the broader trends at the interface of financial investment, food system dynamics,
36 and climate change shows potential connections.
37
38 Climate-induced variability in food production has the potential to introduce a new level of uncertainty into
39 food and farmland markets, encouraging financial investment into products to capitalize on price volatility
40 and to hedge risks. The new financial instruments enable investors to speculate more easily on the direction
41 of food and land prices, especially when they are volatile (Ouma, 2014; Baines, 2017).
42
43 5.13.7 Climate Change Interactions with other Drivers Food-Water-Health-Energy-Security Nexus
44
45 Linkages between food security and nutrition with water and energy as well as other important socio-
46 environmental issues are increasingly being described within a nexus framework (see also Chapters 3, 4, 6,
47 and 7) with food systems frequently located at the centre of nexus concepts (Caron et al., 2018).
48
49 Climate change will affect the food-energy-water (FEW) nexus, commonly in the form of risk multiplier
50 (high confidence) (e.g. Conway et al., 2015; Barik et al., 2016; Keairns et al., 2016; Abbott et al., 2017;
51 Ebhuoma and Simatele, 2017; Caron et al., 2018; D'Odorico et al., 2018; de Amorim et al., 2018; Mpandeli
52 et al., 2018; Nhamo et al., 2018; Soto Golcher and Visseren-Hamakers, 2018; Yang et al., 2018; Amjath-
53 Babu et al., 2019; Froese and Schilling, 2019; Mercure et al., 2019; Momblanch et al., 2019; Pastor et al.,
54 2019; Xu et al., 2019). Xu et al. (2019) assessed the need for an increase in irrigation water to sustain maize
55 production in Northeast China. As droughts will become more frequent, this could lead to groundwater
56 depletion and other environmental knock-on effects. Barik et al. (2016) described how the growing demand
57 for food in India has led to more irrigation with a reduction in groundwater levels in some regions.
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1
2 Increasing demands for food, energy and water can lead to domestic and international conflict, including
3 political instability and migration, often in the context of drought (high confidence) (Abbott et al., 2017;
4 Bush and Martiniello, 2017; WEF, 2017; D'Odorico et al., 2018; de Amorim et al., 2018). de Amorim et al.
5 (2018) conclude that the WEF nexus is susceptible to many global risks, including extreme weather events
6 and human migrations and predominantly endanger vulnerable communities of less developed countries.
7 There is emerging evidence that food and water insecurity enhance social conflicts, including protests and
8 violent riots, at least partially, by accelerating existing grievances (Heslin, 2021; Koren et al., 2021). Closer
9 coordination at global, regional, and national levels could be recommended to manage these risks.
10
11 Meeting growing demands for food, water, and energy under a changing climate require technical solutions
12 and behavioural change as well as greater coordination across multilateral institutions and governance.
13 Supply-side solutions focus on enhancing production, reducing food waste and loss or lowering water
14 demand through both technological approaches (e.g., breeding, improved irrigation) and agroecological
15 approaches, such as agroforestry, underutilized and more adapted crops, and transition toward a circular
16 economy (Alexander et al., 2015; Obersteiner et al., 2016; D'Odorico et al., 2018; Nhamo et al., 2018; Soto
17 Golcher and Visseren-Hamakers, 2018). Demand-side solutions focus primarily on changes in consumer
18 behaviour toward healthier diets with lower carbon footprints, particularly reduction of meat consumption
19 (Alexander et al., 2015; Obersteiner et al., 2016). Improving the coordination of multilateral organizations
20 could result in improved cross-boundary management of natural resources, particularly related to water
21 (Conway et al., 2015; Nhamo et al., 2018; Soto Golcher and Visseren-Hamakers, 2018).
22
23 As relationships between individual subsystems are systemic, integrated solutions would result in better
24 outcomes across the FEW nexus (strong agreement). Obersteiner et al. (2016) concluded that single-sector
25 policies can create strong trade-offs with other policy targets and SDGs, whereas strategies that reduce
26 pressure on food production systems diminish trade-offs between FEW nexus components. This suggests
27 that achieving multiple SDGs will require balancing societal demands in the context of finite natural
28 resources (Jägermeyr et al., 2017; Amjath-Babu et al., 2019; Momblanch et al., 2019).
29
30 Despite concluding that integrated solutions addressing the systemic connections between the FEW nexus
31 would improve development and environmental outcomes, there are limitations of integrating multiple
32 frameworks, both in terms of describing the complexities and in finding solutions (Leck et al., 2015; Weitz et
33 al., 2017; Wichelns, 2017; Shannak et al., 2018). Leck et al. (2015) and Weitz et al. (2017) indicate that
34 evidence of successful implementation and improved outcomes based on the application of nexus concepts is
35 rare.
36
37
38 5.14 Implementation Pathways to Adaptation and Co-benefits
39
40 5.14.1 State of Adaptation of Food, Feed, Fibre, and Other Ecosystem Products
41
42 Since AR5, several adaptation reviews have been done (Ford et al., 2015; Lesnikowski et al., 2016). In a
43 review of 1159 peer-reviewed sources, Berrang-Ford et al. (2021b) found that observed adaptations in food,
44 fibre and other ecosystem products has consisted mainly in changes in autonomous behaviour changes, such
45 as changing planting time, followed by technological/infrastructure and ecosystem-based adaptation
46 approaches, the majority of which have occurred in Africa and Asia (Figures 5.20-5.21, Table 5.22).
47 Several adaptation options addressed multiple SDGs (e.g. 2, 6 8, 12) (Figure 5.21).
48
49
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1
2
3 Figure 5.19: State of adaptation by region and type of response (based on 1159 peer-reviewed references that addressed
4 adaptation in food, fibre, and other ecosystem products sector; source: Global Adaptation Mapping Initiative (GAMI)
5 database (Berrang-Ford et al., 2021a). The bars indicate the number of evidence for the category x region.
6
7
8 Table 5.23: State of adaptation in food, fibre and other ecosystem products by actor and vulnerability (planned and
9 targeted) (source: Global Adaptation Mapping Initiative (GAMI) database (Berrang-Ford et al., 2021a)).
10
Actors N (%) Equity/justice Planned N (%) Targeted N
(%)
International or multinational 72 (6%) Women 134 (12%) 118 (10%)
governance institutions 264 (23%) Youth 22 (2%) 24 (2%)
National government
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- 117 (10%) Indigenous 95 (8%) 85 (7%)
international/multinational/national 257 (22%) 32 (3%) 32 (3%)
Civil Society- sub-national or local Ethnic
minorities
Individuals or households 1087 (94%)
11
12
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1
2 Figure 5.20: Observed adaptation across regions in food, fibre, and other ecosystem products. Stage of implementation;
3 Type of adaptation; Inclusion of Indigenous knowledge and local knowledge (IK and LK) based on Global Adaptation
4 Mapping Initiative (GAMI) database (Berrang-Ford et al., 2021a). The bars indicate the number of evidence for the
5 options x region.
6
7
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1
2 Figure 5.21: How different response types address the SDGs based on GAMI
3
4
5 Assessment of adaptation options was done for 15 potential options for land and ecosystem transitions
6 (SM5.7, Figure 5.22a). Several adaptation options have high to medium feasibility, with robust evidence,
7 high agreement about the adaptive capacity resilience building potential of options in relation to climate
8 change impact drivers (high confidence). Policy and planning and production shifts have limited evidence for
9 feasibility. Most options are technically and physically feasible, with generally high political and social
10 acceptability and environmental feasibility, but have limited evidence for institutional feasibility. Most
11 adaptation options have medium to high microeconomic feasibility (high confidence), but limited evidence
12 for macroeconomic viability.
13
14 Among five effectiveness indicators (SM5.7, Figure 5.22b), most options have robust evidence of reduced
15 risk vulnerability to climate change, with low scores for local governance, substitution of plant or animal
16 type, community forest management, livelihood diversification and climate services. Higher scored options
17 to reduce risk included increasing biodiversity (at landscape and field level), community seed banks,
18 conventional breeding (plant and animals), mixed systems and agroecological approaches (medium
19 confidence), suggesting multiple co-benefits of these options. Most options have high scores for enhancing
20 social well-being, economic and environmental benefits (medium confidence) but limited evidence for
21 strengthening institutions for most options. There were low scores for potential maladaptation (medium
22 confidence).
23
24
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1
2 Figure 5.22: Assessment of 11 feasibility indicators (six categories) (a) and five effectiveness indicators and
3 maladaptation (b) of adaptation options based on 287 peer-reviewed papers. See SM5.7 for methods and data. Scores
4 ranging from 1 (low) to 3 (high) were obtained by averaging five or more papers for each option and indicator.
5
6
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1 5.14.1.1 Nature-based solutions or ecosystem-based adaptation
2
3 There is growing evidence that nature-based solutions (NBS), which emphasise ecological approaches and
4 biodiversity conservation (Chapter 1), have high potential to transform land and aquatic systems into
5 climate-resilient systems (medium evidence, high agreement) (Albert et al., 2017; Brugère et al., 2019;
6 Galappaththi et al., 2020b; Snapp et al., 2021; Cross-Working Group Box BIOECO; Cross-Chapter Box -
7 NATURAL in Chapter 2).
8
9
10 [START BOX 5.11 HERE]
11
12 Box 5.11: Agroecology as a Transformative Climate Change Adaptation Approach
13
14 Agroecological approaches can increase food system resilience (robust evidence, medium agreement), while
15 some agroecological practices such as agroforestry can provide mitigation measures (medium confidence) (
16 Section 5.10.4.2, Table Box 5.11.1, Altieri et al., 2015; Martin and Willaume, 2016; HLPE, 2019; Bezner
17 Kerr et al., 2021; Snapp et al., 2021). Studies testing agroecological approaches have shown robust evidence,
18 medium agreement of increasing adaptation effectiveness through reducing risk, improving food security,
19 yield stability, reducing input costs, and other supporting and provisioning ecosystem services (Section
20 5.4.4.4 Diacono et al., 2017; Pandey et al., 2017; Schulte et al., 2017; Calderón, 2018; Bezner Kerr et al.,
21 2019; Côte et al., 2019; Rosa-Schleich et al., 2019; Bezner Kerr et al., 2021; Snapp et al., 2021). Effective
22 locally relevant agroecological approaches involves participatory processes, co-creation of knowledge with
23 farmers and attention to social inequities (Bezner Kerr et al., 2021; Santoso et al., 2021; Snapp et al., 2021).
24 To address smallholder vulnerability to climate change impacts, however, additional policy support beyond
25 agroecology will be needed that is context specific; for example, addressing farmer capacity, limited political
26 power to access land, water, seeds and other key natural resources, structural gender inequalities, policy and
27 market disincentives that support large-scale monocultures (high confidence) (Anderson et al., 2019a; HLPE,
28 2019; Holt-Giménez et al., 2021; Snapp et al., 2021).
29
30
31 Table Box 5.11.1: Dimensions of agroecological transitions as a transformative climate change adaptation strategy,
32 benefits, tradeoffs and constraints to implementation
Different dimensions of agroecological Links to climate change impacts, benefits, tradeoffs and
transitions as a transformative climate constraints to implementation with examples.
change adaptation strategy
Environmental: Agroecology can support · Biodiversity of functional species groups and responses to
long-term productivity and resilience of food climate hazards play an important role in building stability and
systems by sustaining ecosystem services productivity in agroecological systems (5.4.4.4). A 5-year
such as pollination, soil organic carbon, pest study, for example, in Asia, Africa and Latin America found
and weed control, soil microbial activity, that smallholder farmers (< 2 ha) increased yields by 25%
crop yield stability, water quality and through promoting pollination (Garibaldi et al., 2016).
biodiversity (high confidence, see Section
5.4.4.4, Cross-Working Group Box · Landscape complexity is an important feature of agroecology
BIOECONOMY this chapter and Cross- which can increase resilience to extreme events, such as pest
Chapter Box NATURAL in Chapter 2). and disease outbreaks or floods, and provide multipurpose
(Isbell et al., 2017; Kremen and benefits (Sections 5.4.4; 5.10.4.2) (Paolotti et al., 2016; Reed et
Merenlender, 2018; LaCanne and Lundgren, al., 2016; Kremen and Merenlender, 2018; LaCanne and
2018; Beillouin et al., 2019b; Dainese et al., Lundgren, 2018; Rosa-Schleich et al., 2019; Holt-Giménez et
2019; Rosa-Schleich et al., 2019; Snapp et al., 2021).
al., 2021).
Socio-cultural: Effective locally relevant · Context-specific: some agroecological systems and practices
agroecological approaches involves have lower average crop productivity than conventional
participatory processes, co-creation of systems, while others can have higher overall crop productivity
knowledge with farmers and attention to and farm profitability (LaCanne and Lundgren, 2018; Barbieri
et al., 2019; Rosa-Schleich et al., 2019).
· Agroecology can emphasize social justice concerns, including
gender inequities, considered crucial for climate change
adaptations in food production to have positive impacts on food
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social inequities, in doing so building farmer security and nutrition (Cross-Chapter Box GENDER in Chapter
capacity (HLPE, 2019; Bharucha et al., 2020; 18; (Smith and Haddad, 2015; HLPE, 2019; Sylvester and
Holt-Giménez et al., 2021; Snapp et al., Little, 2020).
2021).
· In some contexts, agroecological systems can draw on and
support Indigenous knowledge, farming systems, networks and
socio-cultural values(Catacora-Vargas et al., 2017).
Food security and nutrition: Agroecological · Combinations of practices, such as intercropping, crop rotation
practices can increase household food and crop diversification, often outperform individual practices
security and nutrition for producer for yield and food security outcomes (Beillouin et al., 2019b;
households, with more evidence in low- and Bezner Kerr et al., 2021).
medium-income countries (high confidence) · Agroecological systems more effectively support food security
(Darrouzet-Nardi, 2016; Demeke et al., and nutrition when complemented by nutrition and health
2017; Jones, 2017a; Kangmennaang et al., education, participatory research and other public policies and
2017; Pandey et al., 2017; Luna-Gonzalez programs which address access to knowledge (high confidence;
and Sorensen, 2018; Bezner Kerr et al., (HLPE, 2019; Bezner Kerr et al., 2021; 7.4).
2019; Boedecker et al., 2019; Mulwa and
Visser, 2020; Bezner Kerr et al., 2021;
Santoso et al., 2021).
Economic: Agroecology can support socio- · Multi-level policies and programs that support urban and peri-
economic resilience, through reducing urban networks with agroecological producers, including
reliance on purchased inputs, enhancing local farmers' markets, public procurement (e.g.school meals,
and regional economies (HLPE, 2019; hospitals), incentives for short food value chains, and
Bharucha et al., 2020; Holt-Giménez et al., participatory guarantee certification schemes which build
2021). producer-consumer networks are all ways to support
agroecological transitions by consumers (high confidence)
(Catacora-Vargas et al., 2017; Pérez-Marin et al., 2017; Mier y
Terán Giménez Cacho et al., 2018; Anderson et al., 2019a;
HLPE, 2019; Borsatto et al., 2020; González de Molina, 2020).
· Transitions to agroecology at a global scale, however, may
require considerable dietary shifts which vary by region, have
implications for total food production and farm level revenues,
especially in the short term (medium confidence, (Muller et al.,
2017; Seufert and Ramakutty, 2017; Barbieri et al., 2019;
Rosa-Schleich et al., 2019; Smith et al., 2019b; 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 inequalities, policy and
market disincentives that support large-scale monocultures
(Anderson et al., 2019a; Holt-Giménez et al., 2021; Snapp et
al., 2021).
Long-term investment: Timeframes are an · In the short term, without policy support the costs of
important consideration, as an agroecological implementing agroecological practices at the farm scale can
transition involves multiple overlapping outweigh ecological and adaptation benefits, although the
stages, of reducing chemical inputs, timeframe required is context-specific (Padel et al., 2020).
experimenting with and applying new
agroecological practices and adjusting them, · In the long-term, implementing agroecological practices can
redesigning the farm, strengthening short increase yields, yield stability, farm profitability, reduce risks
value chains and producer networks and build resilience alongside ecological, health and social co-
(Gliessman, 2014; Padel et al., 2020). benefits, but impacts are context-specific (Section 5.4.4.4,
Rosa-Schleich et al., 2019; Bezner Kerr et al., 2021; Snapp et
al., 2021).
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· 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 et al., 2017; Bezner Kerr
et al., 2019; Kansanga et al., 2021), while in the UK, farmers
transitioning to agroecological practices took 3 or more years to
realize benefits (Padel et al., 2020).
Policy tools: Investment in agroecological · Farm scale and landscape diversity can affect the capacity
approaches that are designed for socio- for producers to implement agroecological systems. Small
ecological context, farmer-led schools, co- to mid-sized farms can more effectively integrate
learning platforms, and networks of farmers, agroecological methods such as increasing landscape
scientists, private sector and civil society can diversity, on-farm diversity and intercrops (medium
support agroecological transitions at a confidence) (Garibaldi et al., 2016; Herrero et al., 2017;
regional scale (high confidence) (Coe et al., HLPE, 2019). Barriers to adopting agroecological practices
2014; Catacora-Vargas et al., 2017; Pérez- for small to mid-sized farms include limited market options,
Marin et al., 2017; Mier y Terán Giménez subsidy and policy disincentives, lack of extension support,
Cacho et al., 2018; Anderson et al., 2019a; knowledge and insecure land tenure (Jacobi et al., 2017;
González de Molina, 2020; Lampkin et al., Kongsager, 2017; Hernández-Morcillo et al., 2018; Iiyama
2020; Padel et al., 2020; Snapp et al., 2021). et al., 2018; Anderson et al., 2019a; Gerard et al., 2020).
Policies can provide incentives (e.g., price
premiums, access to credit, extension · Barriers for large farms to transition to agroecological
service, taxes, regulation) to support practices include knowledge gaps, cost, significant
agroecological transitions by producers infrastructure and farm design changes, labour, psycho-
(HLPE, 2019; Rosa-Schleich et al., 2019; social adjustments, policy disincentives and market lock-ins
Gerard et al., 2020; SAPEA, 2020). (Hill, 2014; Rosa-Schleich et al., 2019; Lampkin et al.,
2020).
Other drivers of agroecological transitions · Some policies and initiatives support large-sized farms to
can include crises (environmental, economic, transition to agroecology (Zhou et al., 2014; Liebman and
or social), social movements, changing Schulte, 2015; Ajates Gonzalez et al., 2018; Bellon and
socio-cultural values, addressing social Ollivier, 2018; Lampkin et al., 2020; Padel et al., 2020)
inequities, and discourse (Pérez-Marin et al.,
2017; Mier y Terán Giménez Cacho et al., Further research could provide context-specific information about
2018; Anderson et al., 2019a). economic and ecological benefits of some practices and
combinations, with effective policies to support their implementation
(high confidence) (HLPE, 2019; Rosa-Schleich et al., 2019; 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 et al., 2020; Mottet et al., 2020) including annual
reporting to the UNFCCC (Snapp et al., 2021).
1
2
3 5.14.1.2 Climate services
4
5 Climate services, understood as the production, translation, communication and use of climate information in
6 decision-making processes, can contribute to adaptation efforts in agricultural systems (medium agreement,
7 low evidence). Climate services can support decision-makers in agriculture by providing tailored information
8 that can inform the implementation of specific adaptation options (Vaughan, 2018; Buontempo et al., 2019;
9 Dobardzic et al., 2019; Hank et al., 2019).
10
11 For some high- and medium-income countries, evidence suggests that climate services have been
12 underutilized (Mase and Prokopy, 2014), with limited evidence in these countries of the impact of climate
13 services on yields, income, and food security and nutrition. In low-income countries, use of climate services
14 can increase yields, incomes and promote changes in farmers' practices (low confidence) (Roudier et al.,
15 2014; Roudier et al., 2016; Tarchiani et al., 2017; Ouedraogo et al., 2018). There is low confidence that
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1 climate services are delivering on their potential, whether they are being accessed by the vulnerable, and how
2 these services are contributing to food security and nutrition (Ouedraogo et al., 2018; Vaughan et al., 2019).
3
4 Improved design and delivery of climate services can enhance effectiveness (medium confidence). Ways to
5 enhance the impact of climate services include integrating information from multiple sources at different
6 scales (Bouroncle et al., 2019), participatory collection and analysis of climate information (Loboguerrero
7 AM, 2018; Tesfaye et al., 2019; Rossa, 2020), and making forecast information available in local languages
8 and as verbal communications for farmers who cannot read (Nkiaka et al., 2019).
9
10 In countries with limited climate data, crowd sourcing (outsourcing data collection to the public) (Minet et
11 al., 2017) and digital tools present an opportunity for addressing climate risk (medium confidence) (Osgood
12 et al., 2018; Thornton, 2018; Partey et al., 2020; Sotelo et al., 2020). Bundling additional services such as
13 market information with climate information may be effective at plugging information gaps (low confidence)
14 (Chatuphale and Armstrong, 2018; Dalberg, 2019; Tesfaye et al., 2019)
15
16 There may be inequality in access to climate services; their use may tend to benefit large-scale operations
17 and disadvantage small-and medium-scale farmers and others who face issues of access due to social and
18 economic inequity; also some groups such as pastoralists have not yet benefitted from climate services (high
19 confidence) (Furman et al., 2014; Muema et al., 2018; Awazi et al., 2019; Nyantakyi-Frimpong, 2019;
20 Paudyal et al., 2019; Vaughan et al., 2019; Nidumolu et al., 2020; Partey et al., 2020). Other challenges
21 include technology ignorance, data privacy and security, data access permissions, software and system
22 compatibility, and understanding how to use and derive value from accessed data (Chatuphale and
23 Armstrong, 2018; Drewry et al., 2019). More work is needed to understand the factors that prevent farmers
24 and fishers from benefiting from this new information. Recent assessments suggest that access to, and value
25 of, climate and weather information can be enhanced by the development of digital tools (including radio,
26 text messages, etc.) appropriate to the specific needs of different vulnerable groups, as well as by including
27 these groups in their development and building their capacity (medium confidence) (Camacho and Conover,
28 2019; Gumucio et al., 2020; Sultan et al., 2020).
29
30 5.14.1.3 Insurance as a climate impact risk management tool
31
32 Insurance is a financial adaptation strategy increasingly used in agriculture and aquaculture. A relatively new
33 approach to agricultural insurance risk is the use of financial derivative products, such as index-based
34 agricultural insurance (IBAI), marketed by financial institutions to farmers to help them deal with weather-
35 related production risks (Isakson, 2015; Jensen and Barrett, 2017). The basic idea is to rely on easily
36 observed weather indices, such as precipitation or temperature, that co-vary with farm production. Insurance
37 payments are received when the metric trigger for a region is reached, eliminating the need to collect farm-
38 specific information. Proponents of index insurance argue that it can resolve the information costs and
39 incentive problems inherent in rural financial markets, such as adverse selection, and allow provision of
40 insurance coverage at a fraction of the costs of loss-based polices (Jensen and Barrett, 2017). Buyers of index
41 policies do not have to prove their ownership of assets with weather-related losses. This lowers transactions
42 costs and makes it more affordable to insure small plots of land.
43
44 The creation of index insurance requires significant prior research and extensive data that may not be
45 available or sufficient in lower income countries, including identifying the most appropriate farm and climate
46 variables to include and financial and regulatory support from the public sector (Economic Commission for
47 Latin America and the Caribbean and Central American Agricultural Council of the Central American
48 Integration System, 2013; Economic Commission for Latin America and the Caribbean and System, 2014).
49 Some insurance providers bundle it with other services, such as fertilizer use or seeds that may not be useful
50 to particular farmers and can increase their overall capital costs (Isakson, 2015). Although proponents see
51 IBAI as a way to mitigate farmers' risks associated with more variable weather patterns (Greatrex et al.,
52 2015), critics argue that derivative-based insurance products tend to benefit wealthier farmers and fail in
53 assisting the poorest and most marginalized farmers (Isakson, 2015; Taylor, 2016). Thus far, there is low
54 agreement and medium evidence regarding the adaptation potential of derivatives-based insurance products,
55 signaling a need for further research in this area.
56
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1 5.14.1.4 Community-based adaptation approaches
2
3 Community-based adaptation (CbA) strategies, which involve locally-driven, place-based adaptation
4 approaches, can help build adaptive capacity to climate change impacts, but require explicit attention to
5 power dynamics, respect for local and Indigenous knowledge systems, adequate resources, future climatic
6 trends and coordination at multiple levels of governance to be effective (high confidence) (Spires et al.,
7 2014; Fernández-Giménez et al., 2015; Nagoda, 2015; Ashley et al., 2016; Berner et al., 2016; Ensor et al.,
8 2016; Avtar et al., 2019; Lam et al., 2019; Silwal et al., 2019; McNamara et al., 2020; Piggott-McKellar et
9 al., 2020; Rossa, 2020; Uchiyama et al., 2020). Since AR5, there is strong evidence that participation of local
10 stakeholders in adaptation planning and implementation improve communities' capacity to monitor and
11 respond to climate change impacts on food, fibre, and forestry systems, provided that adequate resources and
12 local knowledge on climate change exist. Participatory monitoring of climate change impacts, and
13 participatory scenario development to develop community action plans are examples, which can help
14 strengthen community preparation for and response to climate impacts.
15
16 Community-based monitoring of forests, coral reefs, seagrass and mangroves are examples of local natural
17 resource assessment that can support food security and livelihoods while informing regional and national
18 climate change planning tools (Carter et al., 2014; Gevaña et al., 2018; Avtar et al., 2019). Negotiation
19 amongst many stakeholders at multiple scales, including inclusive mechanisms to address power inequities
20 in governance structures and communities, may be needed for CbA to be effective (Avtar et al., 2019;
21 McNamara et al., 2020). Indigenous knowledge and community-based management of fisheries and
22 aquaculture in the Arctic and Asia (Roux et al., 2019; Chen and Cheng, 2020; Galappaththi et al., 2020a;
23 Schott et al., 2020; Galappaththi et al., 2021) provide adaptive strategies for sustainable use. (Iticha and
24 Husen, 2019). Community-based climate services in the Andes (managed through a collaboration of
25 smallholder producers and an international partnership) built capacity and knowledge of climate change
26 dynamics as well as trust in local climate institutions, providing meaningful information for regional
27 responses to climate change impacts (Rossa, 2020). Community-based participatory scenario planning can
28 help identify multiple climate stressors and vulnerabilities to develop effective adaptation plans (Fernández-
29 Giménez et al., 2015; Bennett et al., 2016; Cross-Chapter Box MOVING PLATE this Chapter).
30
31 An assessment of 32 different CbA initiatives in the Pacific Islands, including addressing risks to food
32 security, found high performing projects had 6 key entry points: effective methods to improve adaptive
33 capacity, appropriate to the local context, which moved beyond narrow geographical definitions of
34 community to consider equity of impact, and ecosystem-based approaches, jointly addressing climatic and
35 non-livelihood pressures and consideration of future climatic trends (McNamara et al., 2020). Low-
36 performing initiatives, in contrast, were not sustained; these overlooked future climatic trends in their
37 initiatives, such as beehive susceptibility to climate extremes, and had dependent, unequal relationships that
38 lacked genuine local approval or ownership and did not fit local values and context (Spires et al., 2014;
39 McNamara et al., 2020; Piggott-McKellar et al., 2020). CbA initiatives can also suffer from not having
40 adequate local knowledge of potential strategies to address future climatic scenarios, and may lead to
41 maladaptation, increasing socio-economic inequities in communities (Nagoda, 2015). Addressing inequity in
42 power dynamics and building technical adaptive capacity of local people are some of the ways that CbA
43 initiatives can support more resilient food systems (McNamara et al., 2020).
44
45 5.14.1.5 Local and regional food systems' strengthening and food sovereignty
46
47 Food sovereignty brings together adaptation options based on agroecological methods, access to resources,
48 collective and CbA (HLPE, 2019). Addressing food security and nutrition in light of climate change impacts
49 and vulnerabilities is considered to arise from a mixture of globalised supply chains and local production, not
50 one or the other (Blesh et al., 2019; Stringer et al., 2020). Evidence on strengthening local and regional food
51 systems with a food sovereignty approach, in terms of access to resources (land, seeds, water), shortened
52 food chains and CbA strategies suggest that these strategies can positively contribute to climate change
53 adaptation in many contexts (medium confidence)(SRCCL) but can also lead to conflict especially regarding
54 management of mobile resources such as fisheries (Section 5.8, Cross-Chapter Box MOVING PLATE this
55 Chapter). All these options can build adaptation through actions that strengthen local capacities and the
56 power to act within food systems. Securing and recognising tenure for Indigenous Peoples (Hurlbert et al.,
57 2019) and local communities (Oates et al., 2020) can improve their ability to adapt by increasing the
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1 incentive to invest in resilient infrastructure and sustainable land management practices. Community seed
2 banks and networks strengthen local seed systems and realize farmers' rights favouring access to a variety of
3 local genetic resources, with landraces often more adapted to the local social, cultural, and ecological
4 environment and needs, and better adapted to harsh environments without external inputs (Mousseau, 2015;
5 Bisht et al., 2018; Maharjan and Maharjan, 2018; Otieno et al., 2018; Mbow et al., 2019). This plays a key
6 role in participatory plant breeding (section 5.4.4.5; FAO, 2019e). The integration of informal and formal
7 seed system elements is important for the adaptive capacity of smallholder farmers (Westengen and Brysting,
8 2014; Westengen and Berg, 2016; FAO, 2019e).
9
10 Strengthening both local and regional food systems is a strategy to increase resilience (Schipanski et al.,
11 2016; Palmer et al., 2017)resource use efficiency (Mu et al., 2019) and self-reliance (medium evidence, low
12 agreement) (Griffin et al., 2015; Chapin et al., 2016; Karg et al., 2016). Collective trademarks (Quiñones-
13 Ruiz et al., 2015) and participatory guarantee systems (Niederle et al., 2020) are examples of innovative
14 institutional strategies to strengthen local and regional food systems. In the urban context, the city-region
15 food system (CRFS) approach is motivated by reducing dependence on international trade and associated
16 instability and to facilitate local decision-making (Karg et al., 2016). CRFS includes a network within a
17 regional landscape around one urban center and surrounding peri-urban and rural regions (Blay-Palmer et al.,
18 2018). Urban and peri-urban agriculture are promoted as effective strategies to adapt to climate change in
19 different contexts (see Section 5.12.5.3, Dubbeling, 2015; Lwasa et al., 2015). In order to cope with the
20 effects of climate change, strengthening regional food systems is becoming an explicit part of urban and
21 regional policy, being tested in many different cities worldwide (Dubbeling et al., 2017; Blay-Palmer et al.,
22 2018; Berner et al., 2019; Sellberg et al., 2020; van der Gaast et al., 2020). Strengthening both local and
23 regional food systems has to be balanced against limitations and tradeoffs, since modelling exercises of
24 regionalization scenarios show urban agriculture cannot achieve food security in areas with rapid population
25 growth (Le Mouël et al., 2018). Furthermore, international trade can compensate in cases where the regional
26 system fails due to extreme events or other related climate shocks (Section 5.11.8).
27
28 5.14.2 Enabling Conditions for Implementing Adaptation
29
30 5.14.2.1 Addressing social inequalities in food systems
31
32 Addressing gender and other social inequalities (e.g., racial, ethnicity, age, income, geographic location) in
33 markets, governance and control over resources is a key enabling condition for climate resilient transitions in
34 land and aquatic ecosystems (high confidence) (Pearse, 2017; Vermeulen et al., 2018; Blesh et al., 2019; Rao
35 et al., 2019b; Cross-Chapter Box GENDER in Chapter 18, Section 5,13,1; Tavenner et al., 2019). Adaptation
36 strategies can have negative impacts on marginalized social groups and worsen socio-economic inequities
37 unless explicit efforts are made to address unequal power dynamics and differences in access to resources in
38 agricultural, fisheries, aquaculture, livestock and forestry systems (high confidence) (Glemarec, 2017; Haji
39 and Legesse, 2017; Nagoda and Nightingale, 2017; Nightingale, 2017; Rao et al., 2019b; Huyer and Partey,
40 2020; Mikulewicz, 2020; Taylor and Bhasme, 2020; Eriksen et al., 2021). Technical approaches to
41 adaptation that ignore inequities can worsen them, see for example the case study on Climate Smart
42 Agriculture (Box 5.12). Enabling environments support inclusive decision-making, capacity-building, shifts
43 in social rules, norms and behaviours and access to resources for marginalized groups for climate change
44 adaptation (e.g., Tschakert et al., 2016; Ziervogel, 2019; Eriksen et al., 2021; Garcia et al., 2021).
45
46
47 [START BOX 5.12 HERE]
48
49 Box 5.12: Is Climate-smart Agriculture Overlooking Gender and Power Relations?
50
51 Climate-smart agriculture (CSA) is an approach that aims to increase agricultural productivity, enhance food
52 security, adapt to climate change and, where possible, reduce GHG emissions. The effective implementation
53 of climate-smart practices is conceptually linked to an enabling environment in which policies, institutions
54 and finance can reorient agricultural systems, thereby supporting development and enhancing food security
55 in a changing climate (Lipper et al., 2014; Karttunen et al., 2017). However, the concept has received
56 criticism based on the absence of conceptual clarity of the interrelations between productivity, food security,
57 adaptation and mitigation (Arenas-Sanchez et al., 2019) and because of limited evidence on the efficacy of
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1 CSA for achieving adaptation and mitigation outcomes at a global scale (Arslan et al., 2015; Lamanna et al.,
2 2016; Chandra et al., 2018). Some argue that CSA operates within an apolitical framework that tends to
3 minimize issues concerning power, inequality, and access, and is overly focused on technical approaches
4 (Taylor, 2017; HLPE, 2019). CSA is explicitly referenced by more than 30 countries in their Intended
5 Nationally Determined Contributions (INDCs) (Ross et al., 2016), but measuring the degree of its
6 implementation still represents a challenge.
7
8 There is low agreement, medium evidence on the relationship between CSA and equity (Allen, 2018;
9 Karlsson et al., 2018). CSA can potentially benefit women if they are able to take advantage of
10 improvements in productivity, food security and adaptation decision making as a result of the
11 implementation of CSA practices. Nevertheless, these advantages can be unequally realized given male
12 domination in receiving information and extension services, as well as financial or resource access (Jost et
13 al., 2016). Some argue that CSA may undermine gender equity (Collins, 2018), entrench and solidify power
14 (Haapala, 2018), and result in the disproportional allocation of new labour-intensive activities to women
15 (Jost et al., 2016). Uptake of some climate-smart technologies can further marginalize the most
16 disadvantaged local groups (Roncoli et al., 2009; Haapala, 2018). Unequal sharing of benefits and burdens
17 with respect to emission reduction costs among different agricultural groups have also been observed
18 (Budiman, 2019).
19
20 In contrast, emerging research points to the potential of CSA as a supporting condition for gender equity,
21 provided that equity and power concerns are explicitly included in the approach (Chanana-Nag and
22 Aggarwal, 2020). Some CSA technologies and practices, such as direct seeding, green manuring, and laser
23 land levelling, can have a significant role in reducing the gender gap in labour burden for women in
24 agriculture, (Khatri-Chhetri et al., 2020). The use of participatory approaches can facilitate community-based
25 adaptation of gender-sensitive CSA practices (Rosimo, 2018). CSA may also empower both men and
26 women: in two villages in India, CSA adoption empowered both sexes in decision making and use and
27 control of income (Hariharan et al., 2018).
28
29 In general CSA programs have tended to overlook questions of inequity (medium confidence), including
30 limited attention to social conditions that promote business-as-usual pathways, although this is now
31 changing. Addressing questions of rights, social injustice, unequal power relations and inequality would help
32 make CSA-related policy responses more effective in addressing vulnerability (Chandra et al., 2017; Clapp
33 and Isakson, 2018; Karlsson et al., 2018; Westengen et al., 2018; Ellis and Tschakert, 2019; Eriksen et al.,
34 2019; Westengen et al., 2019).
35
36 [END BOX 5.12 HERE]
37
38
39 [START BOX 5.13 HERE]
40
41 Box 5.13: Supporting youth adaptation in food systems
42
43 Young people are key agents in agri-food systems: both a vulnerable group, and one that can foster systemic
44 change (high confidence) (Brooks et al., 2019; Figure X; IFAD, 2019; Flynn and Sumberg, 2021; HLPE,
45 2021). Food systems are the largest source of employment for young people, but do not always provide
46 adequate livelihoods or decent working conditions (HLPE, 2021). Regions with more youthful populations
47 such as Sub-Saharan Africa, South Asia, and Central America - are both highly vulnerable to climate change
48 impacts, and reliant on agriculture, forestry, aquaculture, and fisheries for livelihoods (Brooks et al., 2019;
49 IFAD, 2019; HLPE, 2021). Rural youth in these sectors are particularly vulnerable, often with less access to
50 land, water, capital, and other resources, shaped by family and social relations, and fewer opportunities (high
51 confidence) (Chingala et al., 2017; Ricker-Gilbert and Chamberlin, 2018; IFAD, 2019; Yeboah et al., 2020;
52 Flynn and Sumberg, 2021; Nhat Lam Duyen, 2021). In these vulnerable regions, climate change compounds
53 other drivers such as poverty to increase youth out-migration to urban areas or other regions (medium
54 confidence) (Zin et al., 2019; Weinreb et al., 2020; HLPE, 2021; Stoltz et al., 2021; Voss, 2021), which can
55 further worsen rural economies. Young low-income rural women may be particularly marginalized and
56 vulnerable due to systemic gender inequities in access to land, credit, employment, institutions, and other
57 resources (medium confidence) (Sah Akwen, 2017; IFAD, 2019; Flynn and Sumberg, 2021).
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1
2 Youth play a critical role in all sectors of the food system (HLPE, 2021; Figure Box 5.13.1) and some are
3 actively pursuing work and innovation in agri-food systems (medium confidence) (Sah Akwen, 2017; 2019;
4 Yeboah et al., 2020; Flynn and Sumberg, 2021). Climate change impacts may reduce youth employment
5 options in food systems in some regions, while they are often politically marginalized (Brooks et al., 2019;
6 IFAD, 2019; HLPE, 2021). At the same time, due to heightened awareness about climate change, youth may
7 be more willing to apply climate adaptation strategies (medium confidence) (Ali and Erenstein, 2017; Jiri et
8 al., 2017; Sah Akwen, 2017; Chamberlin and Sumberg, 2021; Doherty et al., 2021). Agri-food policy
9 implementation of adaptation strategies could increase inclusive participation of youth to meet their needs
10 (HLPE, 2021). Inclusive investments in water management, infrastructure, agri-food science, and policies
11 that increase youth access to land, credit, knowledge, education, skills, and other crucial resources can
12 support dignified and rewarding agri-food employment (Ahsan and Mitra, 2016; Brooks et al., 2019; HLPE,
13 2021). Digital technologies can support agrifood adaptations, but digital divides must be overcome to avoid
14 worsening inequities (HLPE, 2021). Initiatives which protect and strengthen youth engagement and
15 employment in the all points of the food system, including recognition of youth's critical role and agency
16 through rights-based approaches, can support sustainable food transitions (HLPE, 2021). Harnessing youth
17 innovation and vision to address climate change alongside other SDGs such as gender inequity and rural
18 poverty, will be a crucial strategy to ensure resilient economies in food systems (high confidence) (Laube,
19 2016; Brooks et al., 2019; IFAD, 2019; Abay et al., 2021; HLPE, 2021).
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1
2
3 Figure Box 5.13.1: Youth agency, engagement, and employment in food system (HLPE, 2021)
4
5
6 [END BOX 5.13 HERE]
7
8
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1 5.14.2.2 Incorporating Indigenous knowledge and local knowledge
2
3 Indigenous knowledge (IK) and local knowledge (LK), while an important component of many adaptation
4 strategies (Reyes-García, 2014; Roue, 2018), continues to be marginalized in food systems; greater
5 integration will increase effectiveness (high confidence) (Ford et al., 2015; Brugnach et al., 2017; Figueroa-
6 Helland et al., 2018). Where Indigenous Peoples have access to and control over their lands and natural
7 resources, food systems can potentially be more sustainably managed and more resilient (high confidence)
8 (Rumbach and Foley, 2014; O'Connell-Milne, 2015; Camacho et al., 2016; Janhiainen, 2017; Kihila, 2018).
9 For example, Solomon Islands, community-based adaptation combining with IK-informed community
10 mapping helped boost agricultural yields sustainably (Leon et al., 2015), and in China people living in rich
11 plant resource regions have used their wild plants IK to complement the decrease of crop yields during
12 extreme droughts to ensure food security (Zhang et al., 2016). These cases have led scientists and local
13 communities to call for more practical actions to bridge local knowledge, Indigenous knowledge, and formal
14 science (Borquez et al., 2017; Klenk et al., 2017; Mukhopadhyay, 2017; Olorunfemi, 2017; Reyes-Garcia et
15 al., 2019). Despite this increased public and scientific recognition, Indigenous knowledge is often not
16 acknowledged or used.
17
18 Effective adaptation requires a more holistic approach that includes the recognition of Indigenous rights,
19 governance systems and laws (high confidence) (Robinson et al., 2016a; Brugnach et al., 2017; Magni, 2017;
20 McMillen et al., 2017; McNeeley, 2017; Pearce et al., 2018), and to couple IK with proactive and regionally
21 coherent adaptation plans, actions, and cooperation (Shaffer, 2014; Melvin et al., 2017; Forbis Jr. and
22 Hayhoe, 2018; Makondo and Thomas, 2018).
23
24 Supporting Indigenous groups' knowledge and other excluded social groups can help preserve and harness
25 underutilized resources to enhance nutritional and economic security, with careful measures in protecting
26 Indigenous intellectual rights and avoiding commodification exploitation (Nakashima et al., 2012; Nandal
27 and Bhardwaj, 2014; Ghosh-Jerath et al., 2015; Ebert, 2017). In some regions there has been a loss of
28 Indigenous knowledge about food systems, reducing adaptive capacity (Richards et al., 2019; Panikkar and
29 Lemmond, 2020). Knowledge exchange between Indigenous elders and youth can support adaptive capacity
30 (Osterhoudt, 2018; Richards et al., 2019; Zin et al., 2019). Education utilizing Indigenous knowledge and
31 local knowledge can help prevent maladaptation options (high confidence) (Melvin et al., 2017; Taremwa,
32 2017; Forbis Jr. and Hayhoe, 2018; Narayan et al., 2020). There are examples of integrating IK and LK into
33 resource management systems, school curricula and in local institutions with existing decision-making
34 process to strengthen their capacity to address climate change (Huaman and Valdiviezo, 2014; McNamara
35 and Prasad, 2014; Abah et al., 2015; Mistry and Berardi, 2016; Tschakert et al., 2017; McNeeley et al., 2018;
36 McNeeley et al., 2020). However, there are limitations of IK and LK to address future climate impacts.
37 Therefore, it is important that science-based knowledge and other knowledge coalesce to produce solutions
38 that are sustainable and viable in the face of projected impacts of climate change. Community-based
39 adaptation approaches can integrate IK and LK and more formal knowledge systems, provided efforts to
40 establish relationships of respect, trust and common understanding between different stakeholders involved
41 (Herath et al., 2015; Camacho et al., 2016; Fidelman et al., 2017; Inaotombi and Mahanta, 2019; Lam et al.,
42 2019).
43
44 5.14.2.3 System transformation and policy enablers
45
46 Recent literature highlights the future challenges of producing the quantities of food needed to feed a
47 growing world population in a way that satisfies nutritional needs, benefits everyone equally and equitably,
48 and minimises the negative impacts of food systems on the environment and the natural resource base. There
49 is broad agreement that current trajectories towards the SDGs and countries' commitments under the Paris
50 Agreement are slow and that transformation of food systems is needed (medium agreement, robust evidence)
51 (Campbell et al., 2018; Brondizio et al., 2019; Dury et al., 2019; EAT-LANCET, 2019; FAO, 2019f; Food
52 and Land Use Coalition, 2019; Sachs et al., 2019; Searchinger, 2019a; Searchinger T, 2019b; Loboguerrero
53 et al., 2020; Meridian Institute, 2020; Steiner A, 2020).
54
55 Recent reviews have summarised literature on production system transformations, driven at least in part by a
56 changing climate or changing climate variability. Such transformations may involve sometimes substantial
57 shifts in farm and livelihood enterprises and land configurations, including intensification, diversification,
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1 sedentarisation, as well as abandonment of agriculture (Vermeulen et al., 2018; Thornton et al., 2019).
2 Relevant literature is summarised in Table 5.24, showing reported farmers' perceptions of the drivers of
3 change and the different outcomes of these changes. The consequences of these production system
4 transitions have been mixed; in about 40% of cases, the outcomes at household level have been
5 unequivocally beneficial. In the other cases, there were detrimental effects on livelihoods, or a mixture of
6 positive and negative effects. The effects on nutritional security reported in these studies were limited.
7 Different enablers of change appear critical if transitions are to have positive outcomes. Policy environments,
8 defined in terms of multi-level governance structures and institutions, are a key driver of systems change, as
9 well as being enablers of and barriers to adaptation responses (Xu et al., 2008; Namgay et al., 2014; Galvin
10 et al., 2015; Schmidt and Pearson, 2016; Liao and Fei, 2017). Policies around property and grazing rights are
11 directly linked to small-scale food producer vulnerability, and land ownership changes will pose a key
12 challenge as climate change impacts in the marginal lands intensify (Reid et al., 2014). Collective action at
13 multiple scales and effective governance structures are also a key enabler of transformational change, for
14 helping community initiatives overcome economic, social, and technical barriers, and to strengthen social
15 capital and farmer knowledge (Haglund et al., 2011; Reed et al., 2017; Vermeulen et al., 2018; Fedele et al.,
16 2019). Market development has been shown to be a critical factor for successful adaptation at scale in sub-
17 Saharan Africa (Ouédraogo et al., 2017; Iiyama et al., 2018; Totin et al., 2018). At the same time, financing
18 mechanisms may be a crucial enabler for different food system actors: de-risking agricultural production and
19 food system investments for producers and input suppliers, for example, that address core market failures
20 and compensate actors for extra short-term costs that can lead to longer-term benefits, particularly for small-
21 scale producers and businesses with comparatively low access to technologies and services (Vermeulen et
22 al., 2018; Millan, 2019; see Section 5.14.2.5).
23
24 The examples in Table 5.24 highlight the uneven impact of adaptation programs and projects in general, due
25 in part to differences in institutional support and failure of policies to take into account inequalities (Clay and
26 King, 2019; Nightingale et al., 2020). Focusing on transformational adaptation, Vermeulen(2018) suggested
27 the need to expand the remit of adaptation planning to consider the multi-functionality of agriculture and a
28 system-wide view of food production and consumption. Several authors argue that transformational change
29 must address the personal, practical, and political spheres, in view of the role of power relations and
30 worldviews in shaping practices, food security and inequity (O'Brien, 2015; Nightingale, 2017; O'Brien,
31 2018; Eriksen et al., 2019; Gosnell et al., 2019). If it involves new or unfamiliar technology, transformation
32 may also be highly disruptive, and the added vulnerabilities of food system actors at risk will need to be
33 addressed (Herrero et al., 2020; see Box5.5).
34
35 "Transformation", defined by IPCC (2019a) as `b a change in the fundamental attributes of natural and
36 human systems', is defined here as a redistribution of at least a third in the primary factors of production
37 (land, labor, capital) and/or the outputs and outcomes of production (the types and amounts of production
38 and consumption of goods and services arising from multifunctional agricultural systems) (Vermeulen et al.,
39 2018; Thornton et al., 2019).
40
41
42 Table 5.24: Agricultural and livelihood system transformations from systematic searches of the literature, which are at
43 least partially attributable to climatic factors and that involve increased or decreased system integration, and major
44 consequences of the change. Information in the table is from the references cited. Sources: updated from (Vermeulen et
45 al., 2018; Thornton et al., 2019).
Underlying Primary Drivers Major Processes of Consequences of Reference
Production System of Change as Change as Reported Change, if Reported
Stated
Extensive grassland-based systems
Extensive grassland- Government Sedentarisation Income decline, asset Liao and Fei,
based, NW China policy, climate Diversification (crops, holding decline (2017)
wages)
Extensive grassland- Multiple climatic Diversification (wages, Livestock accumulation López-i-Gelats
based, Peruvian and non-climatic livestock assets, land) in wealthy households, et al., (2015)
Andes drivers Extensification asset diversification in
poorer households
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Extensive grassland- Government Sedentarisation Increased risk, loss of Namgay et al.,
Diversification (crops) cultural identity, (2014)
based, Bhutan policy, labour Exit improved market access,
livelihood "lock-in" Megersa et al.,
constraints, climate Livestock herd (inability to change (2014)
diversification (more rapidly)
Extensive grassland- Increase in climate small stock and camels, Enhanced household
based, Borana, variability, fewer cattle) resilience
Ethiopia resource Sedentarisation
degradation Diversification (crops, Increased food Xu et al.
Extensive grassland- Government off-farm wages, trade) production, increased (2008)
based, Tibet policy, climate Sedentarisation disease burden
Diversification (crops) Weakened institutions Schmidt and
Extensive grassland- Government and cultural practices, Pearson
based, Afar, Ethiopia policy, climate Sedentarisation deteriorating natural (2016)
Diversification (crops, resources
Extensive grassland- Government wages, remittances) Nutritional status Galvin et al.
Intensification remains poor (2015)
based, Kajiado, policy, climate, Sedentarisation
Diversification
Kenya population growth (cashmere sales, forest
products)
Extensive grassland- Government Diversification Fodder shortages, forest Lkhagvadorj
based, Mongolian policy, climate (decreases in sheep and over-use, unsustainable et al. (2013)
Altai goats, increases in cattle, land-use system
decreases in grain
Extensive grassland Increasing drought, production, increases in Increased household Du et al.
based, Mongolia grassland fruit and vegetable income from off-farm (2016)
degradation production) employment, more
Exit from agriculture diverse diets
Diversification (crops,
Extensive grassland- Climate change wages, migration) Decreasing adaptive Ogalleh et al.
capacity, over- (2012)
based, northern and variability dependence on local
knowledge for
Kenya adaptation
Extensive systems with crops
Extensive with Multiple Intensification (richer Wildlife conflicts, loss Shackleton et
crops, Eastern Cape, households)
South Africa Economic Exit and abandonment of cultural identity al. (2013)
globalisation, (poorer households)
Extensive with climate change Livelihood Reduced vulnerability to Lennox (2015)
crops, Peruvian diversification climate change, but
highlands Climate Diversification (dairy potential loss of both
production, wage agrobiodiversity and
Extensive with Climate variability, migration) food self-sufficiency
crops, East Africa temperature change Conversion (away from identified by the author
staple crops to feed
Extensive with production) Increasing household Rufino et al.
crops, Ghana Intensification (feed vulnerability (2013)
production)
Diversification (crops, Reduced vulnerability Antwi-Agyei
livestock, wages) et al. (2018)
Intensification (crops,
intercrops)
Diversification (off-farm
activities)
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Extensive Annual and Diversification and Increased household Konchar et al.
smallholder seasonal warming. integration (from resilience owing to (2015)
cropping, Nepal Increased growing buckwheat and diversification of
precipitation with barley to vegetables and production Haglund et al.
Extensive changes in patterns. fruit trees) (2011)
smallholder mixed Droughts and Large-scale regeneration Increased household
system, Niger famines, and land of native trees and income, effects on
degradation shrubs in the arable household food security
landscape not yet know
Other mixed coastal and forest systems
Coastal rice-based, Increased salinity Diversification (from Increased household Faruque et al.
Bangladesh due to reduced dry rice cultivation to income, increased (2017)
season flows from aquaculture of shrimp engagement of women,
Smallholder rivers in India, use and prawn) increased human disease
cropping systems, of groundwater for vulnerability
coastal Bangladesh irrigation Diversification
Increasing (reallocation of land Mixed impacts on Fenton et al.
Smallholder mixed frequency and from crops to household incomes and (2017)
cropping in forested severity of floods aquaculture) seasonal migration
landscapes in since 2008 Exit (migration away frequency
Indonesia from village)
Floods, drought, Diversification Locally, increased Fedele et al.
crop and livestock (reallocation of land household incomes in (2018)
disease from forests to rubber general; more widely,
plantations and rice) some trade-offs with
Intensification biodiversity, water,
(agroforestry) carbon stocks
Extensification
(reforestation, forest
protection)
1
2
3 5.14.2.4 Finance needs and strategies for adaptation
4
5 Current understanding of finance flows and needs for adaptation in crop agriculture, livestock, fisheries,
6 aquaculture, and forest products relies primarily on top-down projections, with limited data (UNFCCC,
7 2018; Buchner et al., 2019; Jachnik et al., 2019). By one estimate, in 2017/2018, agriculture, forestry, and
8 land use received 24% of public adaptation finance (totaling USD 7 billion; half via multilateral development
9 finance institutions and one-quarter from governments) and 35% of international grants (with 71% used for
10 adaptation) (Buchner et al., 2019). According to data from OECD (2020), finance flows for agriculture,
11 forestry and fisheries have risen fairly linearly from ca. USD 1.46 billion in 2010 (the year the Rio marker on
12 climate change adaptation was introduced) to ca. 5.5 billion in 2018. Over the entire tracked period the three
13 subsectors combined received a total of USD 29.82 billion for activities with principal and significant
14 adaptation components.4 However, the dataset only includes climate-related development finance from
15 bilateral, multilateral, and private philanthropic sources, whereas private sector finance flows are not
16 captured as this is notoriously difficult to track (UNEP, 2016; OECD, 2020; cross-ref to Cross-Chapter Box
17 FINANCE in Chapter 17). Most of the funding (85%) was directed towards agriculture with forestry (12%)
18 and fisheries (3%) receiving significantly less, but across the subsectors, there is consistency in the sense that
19 policy and administrative management and development receive the lion's share of support, which is
20 predominantly given in the form of grants (72%) while debt instruments (26%) and equity and shares in
21 collective investment vehicles (2%) contribute less. From a regional perspective, 80% were directed to
22 Africa (47%), Asia-Pacific (27%), and Latin America and Caribbean States (7%), whereas Eastern Europe
23 and Western Europe and Other States received (2%) each and 17% were destined for `developing countries'
4 For reference, the SEI Aid-Atlas (https://aid-atlas.org) only reports flows where adaptation is the principal objective,
and therefore adaptation spending on agriculture, forestry and fisheries for the same period is significantly lower with
USD 16.52 billion, i.e., 21.4% of total adaptation spending.
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1 without regional tags. Finally, it is noteworthy that 38% of adaptation finance in agriculture, forestry and
2 fisheries is marked as also having mitigation benefits and roughly a quarter of funding is reported as having
3 principal or significant gender objectives.
4
5 Whether current levels of growth in adaptation finance for agriculture, forestry and fisheries is keeping up
6 with estimated needs cannot be assessed because of the large uncertainties that surround adaptation cost
7 estimates (Cross-Chapter Box FINANCE in Chapter 17). There is hence high agreement that better
8 assessment of adaptation costs of climate impacts requires considerably more research (Watkiss, 2015; Diaz
9 and Moore, 2017). A recent study focusing on investments needed to offset the effects of climate change on
10 the prevalence of hunger concludes that investments in agricultural R+D have to increase from USD 1.62
11 billion to USD 2.77 billion per year between 2015 and 2050 (Sulser et al., 2021a). In addition to agricultural
12 R+D, significant investment increases in water and infrastructure in the range of USD 12.7 billion and USD
13 10.8 billion are required, respectively, a considerable portion of which is relevant to the food system. In total,
14 Sulser et al. (2021a) estimate that annual investment between USD 21.47 billion and USD 29.8 billion are
15 needed to avoid sliding back from climate-change related increases in the prevalence of hunger but recognize
16 the shortcomings of their approach and acknowledge that "a full analysis of adaptation to climate change in
17 agriculture would require including many other social, economic, and environmental dimensions". For
18 comparison, World Bank (2010) estimated global costs of USD 70-100 billion per year for agriculture,
19 forestry and fisheries, infrastructure, water resources, health, ecosystem services, coastal zones, and extreme
20 weather events to adapt to an approximately 2°C warmer world between 2010 and 2050. While the World
21 Bank includes more sectors, more recent publications consider the resulting figures to be significantly too
22 low (Baarsch et al., 2015; UNEP, 2016; Rossi and Miola, 2017; Hallegatte et al., 2018; Markandya and
23 González-Eguino, 2019; Chapagain et al., 2020; cross-ref to WGII Cross-Chapter Box FINANCE in Chapter
24 17). Therefore, despite the methodological and data challenges, further efforts are needed to better capture
25 the economic risks of climate change and provide estimates of adaptation costs at global to national scales as
26 well as across sectors (Watkiss, 2015; Diaz and Moore, 2017).
27
28 Financial barriers limit implementation of adaptation options in agriculture, fisheries, aquaculture, and
29 forestry (high confidence) (Shukla et al., 2019; FAO et al., 2020). Finance strategies can contribute to
30 adaptation in these sectors in different ways (Table 5.25) and to different degrees. Standardized strategies
31 have not yet been developed for specific adaptation needs and, in current practice, finance strategies are
32 opportunistically deployed, with developing countries facing particular challenges due to under-developed
33 financial mechanisms (Omari-Motsumi et al., 2019).
34
35
36 Table 5.25: Potential adaptation finance strategies for categories of climate-related risks in the agriculture, fisheries,
37 aquaculture, and forestry sectors.
Finance Reduced food Low food safety / Diminished Declining
strategies availability dietary health livelihoods ecosystem services
Reduce § Avoid staple § Diversify § Increase § Incentivize
vulnerability failure: Vouchers to production producer capacity: improved
producers for strategies: Invest in Fund technical management:
improved production alternative crops / assistance programs Improved access to
inputs species / harvest credit based on
methods environmental
performance
Anticipate / § Minimize § Diversify § Moderate food § Minimize
minimize impact of extreme products in supply price spikes: resource depletion:
impacts weather: Fund early chains: Finance National food Subsidize micro-
warning systems processing reserves lending for water-
equipment for efficient
alternative food technologies
products
Steer capital § Develop § Build § Increase § Disincentivize
toward climate-resilient nutrition-sensitive resilience of supply low-resilience
climate production food systems: chain infrastructure: production: Screen
resilience technologies: Fund Finance early-stage Finance improved investments based
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Finance Reduced food Low food safety / Diminished Declining
strategies availability dietary health livelihoods ecosystem services
R&D for improved market building for storage and transport on climate risk
genetics (crops, fish, diversified food
livestock) and products facilities disclosures
management
Pool climate- § Distribute § De-risk § Insure against § Detect high-
related risks climate-related diversified food supply chain risks: risk production
risks: Securitize supply chains: Subsidized index systems: Invest in
investments in Invest in producer insurance programs supply chain
production systems aggregation to monitoring /
improve supply traceability
chain efficiency mechanisms
Compensate § Compensate § Avoid food § Avoid selling § Ecological
for climate- for production shortages: Subsidize off productive restoration: Direct
related losses: Financial food importation assets: Fund social development aid to
impacts transfers to affected support for low- land rehabilitation
producers income households projects
1
2
3 Many types of financial instruments are employed by diverse actors (Table 5.26) guided by their mandates
4 (e.g., development, commerce), capacity (investor, intermediary, donor), and risk appetite. Actors within a
5 sector or local production area can coordinate their financial strategies toward common objectives (e.g.,
6 reduced supply chain loss) or participate in joint financial action such as blended finance structures that
7 combine commercial and concessionary finance to catalyze additional private investment, enrich the pipeline
8 of bankable projects, and test business models (FAO, 2020b).
9
10
11 Table 5.26: Potential adaptation finance objectives for major actors in agriculture, fisheries, aquaculture, and forestry
12 sectors.
Actors Potential adaptation finance objectives
Private sector Focused on capturing positive externalities (i.e., lower risks or costs) from adaptation
investments (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 et al., 2020).
Production § Supply chain transactions (e.g., trade finance)
companies or § Sustainable agricultural infrastructure (e.g., capital investment in storage or
cooperatives
processing facilities to reduce exposure to climate risks)
§ Developing or accessing advisory services (weather data; agronomic information)
(Orchard, 2019)
§ Risk management (e.g., insurance / reinsurance; budget reserves)
Financial § Ownership shares in established companies (i.e., private equity) or large publicly
investors and
intermediaries traded companies (i.e., listed equities)
(e.g. banks, asset § Debt issuance (e.g., working capital; catastrophe bonds; emergency loans)
managers, venture § Real estate investment
capital; non-bank § Financial derivatives
financial § Technological research and development
institutions) § (Impact investors) Bespoke non-financial sustainability objectives (e.g., fairtrade
products; financial inclusion) (Havemann et al., 2020)
Public sector Encompassing nearly-commercial (e.g., specialized commodity boards; bond issuances),
partially subsidized (e.g., low-interest loans), and fully subsidized (e.g., R&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).
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Actors Potential adaptation finance objectives
Government § Strengthen enabling environments for sustainable production and ecosystem
agencies and protection (e.g., price transparency; information exchange; international
multilateral coordination)
institutions
§ Support demonstration projects for sustainable land and resource management
(e.g., grants)
§ Disaster risk reduction (e.g., national disaster funds; social protection programs;
contingent credit lines; sovereign / subsovereign insurance (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)
§ Incentivize and de-risk commercial investments (e.g., interest rate reduction
programs, structured financing, guarantee funds) (Woodard et al., 2019)
1
2
3 Expanding access to financial services and pooling climate risks can enable and incentivize climate change
4 adaptation (medium confidence) (Shukla et al., 2019). To mobilize financial instruments (Table 5.27) toward
5 adaptation needs, individual actors can apply an adaptation lens to existing or new activities, accounting for
6 investment characteristics (e.g., development stage; cash flow profile), requirements (e.g., amount; risk-
7 return), and context (e.g., regulatory landscape) (Havemann et al., 2020). Risk-layering can match financial
8 instruments to severity and probability climate risks (Chatterjee, 2019).
9
10
11 Table 5.27: Major types of financial instruments suitable to adaptation finance in agriculture, fisheries, aquaculture, and
12 forestry sectors (adapted from (Havemann et al., 2020))
Financial instrument Description
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 Ownership of lower-tier shares in a company (e.g., Common stock) or collective
equity investment vehicle (e.g., first-loss tranche)
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 et al., 2019)
Loan, bond, note, credit Direct or indirect provision of capital (e.g., operating loans; dedicated credit line
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
Emergency loan delivery)
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 Subsidized 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
Securitized investments Aggregation of equity or debt to offer marketable securities to a wider pool of
investors with different risk-return appetites
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 et al., 2019)
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Financial instrument Description
Credit guarantee Compensation for specified losses incurred by agricultural lenders
Payment, performance, De-risking mechanism for transactions between providers and buyers of goods /
surety bonds services; may be used in trade finance and other forms of intermediation
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 Compensation for specified market-related losses (e.g., price or currency
insurance fluctuation)
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 or other concessionary funding contingent on achievement of defined
grants adaptation outcomes (with possible third-party verification requirement); may
support development and testing of new approaches (i.e., design funding;
challenges / prizes)
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 programs) and other fiscal measures (e.g., infrastructure
development; funding R&D in climate-resilient practices or technologies) (Shukla
et al., 2019)
Development aid International or domestic programs that directly or indirectly fund adaptation
actions including financial transfers (e.g., producer support or anti-poverty
programs) and subsidized credit (medium confidence) (Shukla et al., 2019)
Planning grants Financial support to governments for adaptation planning (e.g., via readiness
programs)
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
programs (e.g., for larger capital borrowing), insurance (e.g., more granular risk
assessment), or digital strategies (e.g., crowdfunding; smallholder credit)
(Agyekumhene et al., 2018)
Payment for Ecosystem Funds delivered to land and resource managers in exchange for compliance with
Services (PES) 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)
1
2
3 5.14.2.5 Constraints on adaptation finance for food, feed, fibre, and other ecosystem products
4
5 Flow of adaptation finance in the agriculture, fisheries, aquaculture, and forestry sectors is impeded by weak
6 measurement and benchmarking of financial and resilience outcomes (Kramer et al., 2019; Negra et al.,
7 2020), and challenges in assessing repayment capacity of investee producers and companies (medium
8 confidence). Immature information systems (e.g., weak analytics; fragmented standards) (Woodard et al.,
9 2019; Negra et al., 2020) inhibit effective due diligence and impact assessment, contributing to uncertainty
10 and low investor confidence (Havemann et al., 2020; NGFS, 2020). Improved characterization of adaptation
11 finance strategies (e.g., insurance, subsidies, blended finance) requires increased transaction volume (Millan
12 et al., 2019) and analysis of financial (e.g., risk-return profile; investor demand) and resilience (e.g., reduced
13 vulnerability) effects.
14
15 Use of climate-resilient financial strategies and instruments is limited by weak incentives, which commonly
16 take the form of high upfront costs (Verdolini et al., 2018), high transaction and intermediation costs
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1 (Havemann et al., 2020), and relatively long pay-off time. Tenant producers may not experience benefits
2 from adaptation investments (Woodard et al., 2019). Investors seek low-risk, liquid investments, and credit-
3 worthy counterparties (Havemann et al., 2020) yet small- and medium-sized producers and supply chain
4 actors often lack access to formal credit. Given limited experience and weak information for adaptation
5 finance, sub-optimal outcomes may include imbalanced allocation of public and private finance (e.g., to less
6 vulnerable regions and producers; to lower-resilience investments; to short-term benefits) as well as
7 inequitable division of risks and returns (e.g., within blended finance structures) (Clapp, 2017; World Bank,
8 2018; Attridge and Engen, 2019). Additionally, while risk-sharing finance strategies can deliver adaptation
9 benefits, they do not inherently reduce overall risk and commonly cover only specified types of risks (Kellett
10 and Peters, 2014; Watson et al., 2015).
11
12 Methods to strengthen adaptation finance include updating regulations and policies to support adaptation
13 finance instruments (e.g., climate accounting standards), requiring climate-risk disclosure, improved
14 information-sharing among public and private sector actors and devolving funding to local actors (medium
15 confidence) (Global Commission on Adaptation, 2019; Millan et al., 2019).
16
17 5.14.3 Climate-resilient Development Pathways
18
19 Climate-resilient development pathways (CRDPs) introduced in AR5 (Denton, 2014) can briefly be
20 described as "development trajectories that integrate adaptation and mitigation to realize the goal of
21 sustainable development" (see IPCC (2019a)) for a more extensive definition). Several characteristics were
22 proposed in SR1.5 by which such CRDPs could be identified: consistency with principles of sustainable
23 development; ability to deliver poverty reduction; ability to enhance social, gender, racial, ethnic, and
24 intergenerational equity; ability to deliver resilience to climate change and other shocks and stresses; and
25 ability to protect species, biodiversity, and ecosystem goods and services. There is an increasing literature,
26 assessed in SR1.5, on adaptation pathways approaches, generally for specific regions, locations, and
27 subsectors.
28
29 Two recent examples directly related to agriculture and food are the following: sustaining agrarian
30 livelihoods to mid-century of Nicaraguan small-scale coffee producers using analyses of suitability and
31 coffee quality changes under a SRES A2 emissions scenario (Läderach et al., 2017); and development of
32 participatory pathways to mid-century under RCPs 4.5 and 8.5 support regional adaptation planning in
33 Hawke's Bay, New Zealand for agricultural producers and rural communities (Cradock-Henry et al., 2020).
34 CRDPs mentioned in SROCC include shifting from providing coastal defences to adapting to seawater
35 inundation in coastal regions (Renaud et al., 2015) and retreating coastal megacities (Solecki et al., 2017).
36 Pathways frameworks continue to be used to frame the broad-scale challenges of development and climate
37 change, thereby linking different types of food system actor with different responses through time using a
38 variety of approaches, top down and participatory, qualitative, and quantitative (Butler et al., 2016; Antle et
39 al., 2017; Thornton and Comberti, 2017; Collste et al., 2019; Loboguerrero et al., 2020; Stringer et al., 2020).
40
41 While there is consensus that the concept of CRDPs is useful, there are major challenges in identifying,
42 operationalising, monitoring, and evaluating them (Lin et al., 2017; Bloemen et al., 2018). Management
43 approaches seldom integrate across spatio-temporal scales and may be unable to address unidirectional
44 change and extreme events (Holsman et al., 2019). The socio-economic complexities and implications of
45 pursuing integrated outcomes make it difficult to evaluate synergies and trade-offs associated with different
46 actions in local contexts through time (Thornton and Comberti, 2017; Ellis and Tschakert, 2019; Holsman et
47 al., 2019; Orchard, 2019). Case studies by Lo (2019) of transformation in a fishing town in south China and
48 by Gajjar (2019) on undesirable path dependencies in development trajectories in urban and rural India show
49 that overall adaptive capacity of populations may be decreased though politicization and entrenchment of
50 existing inequalities, severely limiting the possibilities for future adaptation. A further challenge of
51 implementation is timely detection of tipping points and abrupt exposure events in both climate and
52 environmental systems (Lenton et al., 2019; Trisos et al., 2020), which may alter the efficacy of current and
53 planned adaptation actions, necessitating a switch to other, more transformational strategies; in such cases,
54 re-energizing food system actors' commitment to adaptation action may well be needed (Bloemen et al.,
55 2018).
56
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1 Integrated modelling of CRDPs will increasingly be needed to throw light on key SDG synergies and trade-
2 offs into the future (Bleischwitz et al., 2018). In investigating possible future pressures on land under the
3 Shared Socio-economic Pathways (SSP), Doelman (2018) projected that the largest changes take place in
4 sub-Saharan Africa in SSP3 and SSP4, mostly because of continued high population growth coupled with
5 (projected) sluggish increases in agricultural efficiency, among other things, leading to expansion of
6 agricultural land for crop and livestock production and reduced food security. Lassaletta (2019) evaluated
7 global pig production in the SSPs and concluded that the future sustainability of pig systems will depend on
8 production efficiency improvements coupled with other factors such as use of alternative feed sources and
9 use of slurries on cropland. Such studies will be increasingly important for quantifying the potential trade-
10 offs and synergies between different SDGs, to guide adaptation (and mitigation) action along CRDPs in the
11 future. The current lack of widely accepted and simple-to-measure indicators for tracking progress in
12 adaptation is a significant hurdle to overcome. There is a large literature on the desirable characteristics of
13 future global food systems, but much less on robust analysis that explicitly addresses and evaluates the
14 pathways towards these desired futures. Gerten (2020) estimate that 10.2 billion people can be supported
15 within key planetary boundaries via spatially redistributed cropland and dietary changes, among other
16 actions. There are few if any analyses for detailing the plausible pathways to move towards such a future in
17 ways that are socially, economically, and environmentally acceptable through time; whether such pathways
18 could indeed be made climate-resilient is unknown. Appropriate monitoring and rapid feedback to food
19 system actors on what is working and why, will be critical to the successful operationalisation of adaptation
20 actions within CRDPs (Bosomworth and Gaillard, 2019).
21
22
23 [START CROSS-WORKING GROUP BOX BIOECONOMY HERE]
24
25 Cross-Working Group Box BIOECONOMY: Mitigation and Adaptation via the Bioeconomy
26
27 Authors: Henry Neufeldt (Denmark/Germany), Göran Berndes (Sweden), Almut Arneth (Germany), Rachel
28 Bezner Kerr (USA/Canada), Luisa F Cabeza (Spain), Donovan Campbell (Jamaica), Jofre Carnicer Cols
29 (Spain), Annette Cowie (Australia), Vassilis Daioglou (Greece), Joanna House (UK), Adrian Leip
30 (Italy/Germany), Francisco Meza (Chile), Michael Morecroft (UK), Gert-Jan Nabuurs (Netherlands),
31 Camille Parmesan (UK/USA), Julio C Postigo (USA/Peru), Marta G. Rivera-Ferre (Spain), Raphael Slade
32 (UK), Maria Cristina Tirado von der Pahlen (USA/Spain), Pramod K. Singh (India), Peter Smith (UK)
33
34 Summary statement
35
36 The growing demand for biomass offers both opportunities and challenges to mitigate and adapt to
37 climate change and natural resource constraints (high confidence). Increased technology innovation,
38 stakeholder integration and transparent governance structures and procedures at local to global scales are
39 key to successful bioeconomy deployment maximizing benefits and managing trade-offs (high
40 confidence).
41
42 Limited global land and biomass resources accompanied by growing demands for food, feed, fibre, and fuels,
43 together with prospects for a paradigm shift towards phasing out fossil fuels, set the frame for potentially
44 fierce competition for land5 and biomass to meet burgeoning demands even as climate change increasingly
45 limits natural resource potentials (high confidence).
46
47 Sustainable agriculture and forestry, technology innovation in biobased production within a circular
48 economy and international cooperation and governance of global trade in products to reflect and
49 disincentivize their environmental and social externalities, can provide mitigation and adaptation via
50 bioeconomy development that responds to the needs and perspectives of multiple stakeholders to achieve
51 outcomes that maximize synergies while limiting trade-offs (high confidence).
52
53 Background
54
5 For lack of space the focus is on land only although the bioeconomy also includes sea-related bioresources.
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1 There is high confidence that climate change, population growth and changes in per capita consumption will
2 increase pressures on managed as well as natural and semi-natural ecosystems, exacerbating existing risks to
3 livelihoods, biodiversity, human and ecosystem health, infrastructure, and food systems (Conijn et al., 2018;
4 IPCC, 2018; IPCC, 2019b; Lade et al., 2020). At the same time, many global mitigation scenarios presented
5 in IPCC assessment reports rely on large GHG emissions reduction in the AFOLU sector and concurrent
6 deployment of reforestation/afforestation and biomass use in a multitude of applications (Rogelj et al., 2018;
7 Hanssen et al., 2020; AR6 WG Chapter 3 and Chapter 7; Canadell et al., 2021; Lee et al., 2021)
8
9 Given the finite availability of natural resources, there are invariably trade-offs that complicate land-based
10 mitigation unless land productivity can be enhanced without undermining ecosystem services
11 (e.g.,Obersteiner et al., 2016; Campbell et al., 2017; Caron et al., 2018; Conijn et al., 2018; Heck et al., 2018;
12 WRI, 2018; Smith et al., 2019c). Management intensities can often be adapted to local conditions with
13 consideration of other functions and ecosystem services, but at a global scale the challenge remains to avoid
14 further deforestation and degradation of intact ecosystems, in particular biodiversity-rich systems (cross-ref
15 to Cross-Chapter Box on NBS-NATURAL in Chapter 2), while meeting the growing demands. Further,
16 increased land-use competition can affect food prices and impact food security and livelihoods (To and
17 Grafton, 2015; Chakravorty et al., 2017), with possible knock-on effects related to civil unrest (Abbott et al.,
18 2017; D'Odorico et al., 2018).
19
20 Developing new biobased solutions while mitigating overall biomass demand growth
21
22 Many existing biobased products have significant mitigation potential. Increased use of wood in buildings
23 can reduce GHG emissions from cement and steel production while providing carbon storage (Churkina et
24 al., 2020). Substitution of fossil fuels with biomass in manufacture of cement and steel can reduce GHG
25 emissions where these materials are difficult to replace. Dispatchable power based on biomass can provide
26 power stability and quality as the contribution from solar and wind power increases (cross-ref WGIII-
27 Chapter 6), and biofuels can contribute to reducing fossil fuel emissions in the transport and industry sectors
28 (cross-ref WGIII-Chapter10 and Chapter11). The use of biobased plastics, chemicals and packaging could be
29 increased, and biorefineries can achieve high resource-use efficiency in converting biomass into food, feed,
30 fuels, and other biobased products (Aristizábal-Marulanda and Cardona Alzate, 2019; Schmidt et al., 2019).
31 There is also scope for substituting existing biobased products with more benign products. For example,
32 cellulose-based textiles can replace cotton, which requires large amounts of water, chemical fertilizers, and
33 pesticides to ensure high yields.
34
35 While increasing and diversified use of biomass can reduce the need for fossil fuels and other GHG-intensive
36 products, unfavourable GHG balances may limit the mitigation value. Growth in biomass use may in the
37 longer term also be constrained by the need to protect biodiversity and ecosystems' capacity to support
38 essential ecosystem services. Biomass use may also be constrained by water scarcity and other resource
39 scarcities, and/or challenges related to public perception and acceptance due to impacts caused by biomass
40 production and use. Energy conservation and efficiency measures and deployment of technologies and
41 systems that do not rely on carbon, e.g., carbon-free electricity supporting, inter alia, electrification of
42 transport as well as industry processes and residential heating (IPCC, 2018; UNEP, 2019), can constrain the
43 growth in biomass demand when countries seek to phase out fossil fuels and other GHG-intensive products
44 while providing an acceptable standard of living. Nevertheless, demand for biobased products may become
45 high where full decoupling from carbon is difficult to achieve (e.g., aviation, biobased plastics, and
46 chemicals) or where carbon storage is an associated benefit (e.g., wood buildings, BECCS, biochar for soil
47 amendments), leading to challenging trade-offs (e.g., food security, biodiversity) that need to be managed in
48 environmentally sustainable and socially just ways.
49
50 Changes on the demand side as well as improvements in resource-use efficiencies within the global food and
51 other bio-based systems can also reduce pressures on the remaining land resources. For example, dietary
52 changes toward more plant-based food (where appropriate) and reduced food waste can provide climate
53 change mitigation along with health benefits (Cross-ref WGIII-Chapter 7.4 and 12.4, Willett et al., 2019) and
54 other co-benefits with regard to food security, adaptation and land use (Mbow et al., 2019; Smith et al.,
55 2019c; cross-ref WGII chapter 5 ). Advancements in the provision of novel food and feed sources (e.g.,
56 cultured meat, insects, grass-based protein feed and cellular agriculture) can also limit the pressures on finite
57 natural resources (WGIII Chapter 12.4, Parodi et al., 2018; Zabaniotou, 2018).
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1
2
3 [START BOX CROSS-WORKING GROUP BOX BIOECONOMY.1 HERE]
4
5 Box Cross-Working Group Box BIOECONOMY.1: Circular bioeconomy
6 Circular economy approaches (Cross ref WGIII-12.6) are commonly depicted by two cycles, where the
7 biological cycle focuses on regeneration in the biosphere and the technical cycle focuses on reuse,
8 refurbishment, and recycling to maintain value and maximize material recovery (Mayer et al., 2019a).
9 Biogenic carbon flows and resources are part of the biological carbon cycle, but carbon-based products can
10 be included in, and affect, both the biological and the technical carbon cycles (Kirchherr et al., 2017; Winans
11 et al., 2017; Velenturf et al., 2019). The integration of circular economy and bioeconomy principles has been
12 discussed in relation to organic waste management (Teigiserova et al., 2020), societal transition and policy
13 development (Directorate-General for Research Innovation, 2018; Bugge et al., 2019) as well as COVID-19
14 recovery strategies (Palahi et al., 2020). To maintain the natural resource base, circular bioeconomy
15 emphasizes sustainable land use and the return of biomass and nutrients to the biosphere when it leaves the
16 technical cycle.
17
18 Biomass scarcity is an argument for adopting circular economy principles for the management of biomass as
19 for non-renewable resources. This includes waste avoidance, product reuse and material recycling, which
20 keep down resource use while maintaining product and material value. However, reuse and recycling is not
21 always feasible, e.g., when biofuels are used for transport and biobased biodegradable chemicals are used to
22 reduce ecological impacts where losses to the environment are unavoidable. A balanced approach to
23 management of biomass resources could take departure in the carbon cycle from a value-preservation
24 perspective and the possible routes that can be taken for biomass and carbon, considering a carbon budget
25 defined by the Paris Agreement, principles for sustainable land use and natural ecosystem protection.
26
27 [END BOX CROSS-WORKING GROUP BOX BIOECONOMY.1 HERE]
28
29
30 Land use opportunities and challenges in the bioeconomy
31
32 Analyses of synergies and trade-offs between adaptation and mitigation in the agriculture and forestry
33 sectors show that outcomes depend on context, design, and implementation, so actions have to be tailored to
34 the specific conditions to minimize adverse effects (Kongsager, 2018). This is supported in literature
35 analyzing the nexus between land, water, energy, and food in the context of climate change which
36 consistently concludes that addressing these different domains together rather than in isolation would
37 enhance synergies and reduce trade-offs (Obersteiner et al., 2016; D'Odorico et al., 2018; Soto Golcher and
38 Visseren-Hamakers, 2018; Froehse and Schilling, 2019; Momblanch et al., 2019).
39
40 Nature-based solutions addressing climate change can provide opportunities for sustainable livelihoods as
41 well as multiple ecosystem services, such as flood risk management through floodplain restoration,
42 saltmarshes, mangroves or peat renaturation (Cross-Chapter Box NATURAL in Chapter 2; UNEP, 2021).
43 Climate-smart agriculture can increase productivity while enhancing resilience and reducing GHG emissions
44 inherent to production (Lipper et al., 2014; Nabuurs et al., 2018; Verkerk et al., 2020; Singh and Chudasama,
45 2021). Similarly, climate-smart forestry considers the whole value chain and integrates climate objectives
46 into forest sector management through multiple measures (from strict reserves to more intensively managed
47 forests) providing mitigation and adaptation benefits (WGIII Section 7.3).
48
49 Agroecological approaches can be integrated into a wide range of land management practices to support a
50 sustainable bioeconomy and address equity considerations (HLPE, 2019). Relevant land-use practices, such
51 as agroforestry, intercropping, organic amendments, cover crops and rotational grazing, can provide
52 mitigation and support adaption to climate change via food security, livelihoods, biodiversity and health co-
53 benefits (Ponisio et al., 2015; Garibaldi et al., 2016; D'Annolfo et al., 2017; Bezner Kerr et al., 2019; Clark et
54 al., 2019; Córdova et al., 2019; HLPE, 2019; Mbow et al., 2019; Renard and Tilman, 2019; Sinclair et al.,
55 2019; Bharucha et al., 2020; Bezner Kerr et al., 2021;WGII Cross-Chapter Box NATURAL in Chapter 2).
56 Strategic integration of appropriate biomass production systems into agricultural landscapes can provide
57 biomass for bioenergy and other biobased products while providing co-benefits such as enhanced landscape
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1 diversity, habitat quality, retention of nutrients and sediment, erosion control, climate regulation, flood
2 regulation, pollination and biological pest and disease control (WGIII Chapter12 Box on UNCCD-LDN,
3 Christen and Dalgaard, 2013; Asbjornsen et al., 2014; Holland et al., 2015; Ssegane et al., 2015; Dauber and
4 Miyake, 2016; Milner et al., 2016; Ssegane and Negri, 2016; Styles et al., 2016; Zumpf et al., 2017; Cacho et
5 al., 2018; Alam and Dwivedi, 2019; Cubins et al., 2019; HLPE, 2019; Olsson et al., 2019; Zalesny et al.,
6 2019; Englund et al., 2020). Such approaches can help limit environmental impacts from intensive
7 agriculture while maintaining or increasing land productivity and biomass output.
8
9
10
11 Figure Cross-Working Group Box BIOECONOMY.1: Left: High-input intensive agriculture, aiming for high yields
12 of a few crop species, with large fields and no semi-natural habitats. Right: Agroecological agriculture, supplying a
13 range of ecosystem services, relying on biodiversity and crop and animal diversity instead of external inputs, and
14 integrating plant and animal production, with smaller fields and presence of semi-natural habitats. Credit: Jacques
15 Baudry (left); Valérie Viaud (right), published in van der Werf et al. (2020)
16
17
18 Transitions from conventional to new biomass production and conversion systems include challenges related
19 to cross-sector integration and limited experience with new crops and land use practices, including needs for
20 specialized equipment ( WGII Chapter 5.10, Thornton and Herrero, 2015; HLPE, 2019 ). Introduction of
21 agroecological approaches and integrated biomass/food crop production can result in lower food crop yields
22 per hectare, particularly during transition phases, potentially causing indirect land use change, but can also
23 support higher and more stable yields, reduce costs, and increase profitability under climate change (Muller
24 et al., 2017; Seufert and Ramakutty, 2017; Barbieri et al., 2019; HLPE, 2019; Sinclair et al., 2019; Smith et
25 al., 2019c; Smith et al., 2020a). Crop diversification, organic amendments, and biological pest control
26 (HLPE, 2019) can reduce input costs and risks of occupational pesticide exposure and food and water
27 contamination (Gonzalez-Alzaga et al., 2014; European Food Safety Authority Panel on Plant Protection
28 Products and their Residues et al., 2017; Mie et al., 2017), reduce farmers' vulnerability to climate change
29 (e.g., droughts and spread of pests and diseases affecting plant and animal health (Delcour et al., 2015; FAO,
30 2020a)) and enhance provisioning and sustaining ecosystem services, such as pollination (D'Annolfo et al.,
31 2017; Sinclair et al., 2019).
32
33 Barriers toward wider implementation include absence of policies that compensate landowners for providing
34 enhanced ecosystem services and other environmental benefits, which can help overcome short term losses
35 during the transition from conventional practices before longer term benefits can accrue. Other barriers
36 include limited access to markets, knowledge gaps, financial, technological, or labour constraints, lack of
37 extension support and insecure land tenure (Jacobi et al., 2017; Kongsager, 2017; Hernández-Morcillo et al.,
38 2018; Iiyama et al., 2018; HLPE, 2019). Regional-level agroecology transitions may be facilitated by co-
39 learning platforms, farmer networks, private sector, civil society groups, regional and local administration,
40 and other incentive structures (e.g., price premiums, access to credit, regulation) (Coe et al., 2014; Pérez-
41 Marin et al., 2017; Mier y Terán Giménez Cacho et al., 2018; HLPE, 2019; Valencia et al., 2019; SAPEA,
42 2020). With the right incentives, improvements can be made with regard to profitability, making alternatives
43 more attractive to landowners.
44
45 Governing the solution space
46
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1 Literature analyzing the synergies and trade-offs between competing demands for land suggest that solutions
2 are highly contextualized in terms of their environmental, socioeconomic, and governance-related
3 characteristics, making it difficult to devise generic solutions (Haasnoot et al., 2020). Aspects of spatial and
4 temporal scale can further enhance the complexity, for instance where transboundary effects across
5 jurisdictions or upstream-downstream characteristics need to be considered, or where climate change
6 trajectories might alter relevant biogeophysical dynamics (Postigo and Young, 2021). Nonetheless, there is
7 broad agreement that taking the needs and perspectives of multiple stakeholders into account in a transparent
8 process during negotiations improves the chances of achieving outcomes that maximize synergies while
9 limiting trade-offs (Ariti et al., 2018; Metternicht, 2018; Favretto et al., 2020; Kopácek, 2021; Muscat et al.,
10 2021). Yet differences in agency and power between stakeholders or anticipated changes in access to or
11 control of resources can undermine negotiation results even if there is a common understanding of the
12 overarching benefits of more integrated environmental agreements and the need for greater coordination and
13 cooperation to avoid longer-term losses to all (Aarts and Leeuwis, 2010; Weitz et al., 2017). There is also the
14 risk that strong local participatory processes can become disconnected from broader national plans, and thus
15 fail to support the achievement of national targets. Thus, connection between levels is needed to ensure that
16 ambition for transformative change is not derailed at local level (Aarts and Leeuwis, 2010; Postigo and
17 Young, 2021).
18
19 Decisions on land uses between biomass production for food, feed, fibre, or fuel, as well as nature
20 conservation or restoration and other uses (e.g., mining, urban infrastructure), depend on differences in
21 perspectives and values. Because the availability of land for diverse biomass uses is invariably limited,
22 setting priorities for land-use allocations therefore first depends on making the perspectives underlying what
23 is considered as `high-value' explicit (Fischer et al., 2007; Garnett et al., 2015; de Boer and van Ittersum,
24 2018; Muscat et al., 2020). Decisions can then be made transparently based on societal norms, needs and the
25 available resource base. Prioritization of land-use for the common good therefore requires societal
26 consensus-building embedded in the socioeconomic and cultural fabric of regions, societies, and
27 communities. Integration of local decision-making with national planning ensures local actions complement
28 national development objectives.
29
30 International trade in the global economy today provides important opportunities to connect producers and
31 consumers, effectively buffering price volatilities and potentially offering producers in low-income countries
32 access to global markets, which can be seen as an effective adaptation measure (Baldos and Hertel, 2015;
33 Costinot et al., 2016; Hertel and Baldos, 2016; Gouel and Laborde, 2021; WGII Section 5.11). But there is
34 also clear evidence that international trade and the global economy can enhance price volatility, lead to food
35 price spikes and affect food security due to climate and other shocks, as seen recently due to the COVID-19
36 pandemic (WGII Chapter 5.12, Cottrell et al., 2019; WFP-FSIN, 2020; Verschuur et al., 2021 ). The
37 continued strong demand for food and other biobased products, mainly from high- and middle-income
38 countries, therefore, requires better cooperation between nations and global governance of trade to more
39 accurately reflect and disincentivize their environmental and social externalities. Trade in agricultural and
40 extractive products driving land-use change in tropical forest and savanna biomes is of major concern
41 because of the biodiversity impacts and GHG emissions incurred in their provision (CCP7, Hosonuma et al.,
42 2012; Forest Trends, 2014; Henders et al., 2015; Curtis et al., 2018; Pendrill et al., 2019; Seymour and
43 Harris, 2019; Kissinger et al., 2021).
44
45 In summary, there is significant scope for optimizing use of land resources to produce more biomass while
46 reducing adverse effects (high confidence). Context-specific prioritization, technology innovation in
47 biobased production, integrative policies, coordinated institutions and improved governance mechanisms to
48 enhance synergies and minimize trade-offs can mitigate the pressure on managed as well as natural and
49 semi-natural ecosystems (medium confidence). Yet, energy conservation and efficiency measures, and
50 deployment of technologies and systems that do not rely on carbon-based energy and materials, are essential
51 for mitigating biomass demand growth as countries pursue ambitious climate goals (high confidence).
52
53 [END CROSS-WG BOX BIOECONOMY HERE]
54
55
56 [START FAQ5.1 HERE]
57
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1 FAQ5.1: How is climate change (already) affecting people's ability to have enough nutritious food?
2
3 Climate change has already made feeding the world's people more difficult. Climate related hazards have
4 become more common, disrupting the supply of crops, meat, and fish. Rapid changes in weather patterns
5 have put financial strain on producers, while also raising prices and limiting the choices and quality of
6 produce available to consumers.
7
8 Most of our food comes from crops, livestock, aquaculture, and fisheries. Global food supply increased
9 dramatically in the last century, but ongoing climate change has begun to slow that growth, reducing the
10 gains that would have been expected without climate change. Regionally, negative effects are apparent in
11 regions closer to the equator, with some positive effects further north and south.
12
13 Climate impacts are also negatively affecting the quality of produce, from changes in micronutrient content
14 to texture, colour, and taste changes that reduce marketability. With warmer and more humid condition,
15 many food pests thrive, food decays more quickly and food contains more toxic compounds produced by
16 fungi and bacteria.
17
18 Warming of the oceans has reduced potential fish catch. The increased carbon dioxide in the atmosphere has
19 led to ocean acidification, which is already impacting the production of farmed fish and shellfish. Changes in
20 local climate have forced producers to shift to new locations, change what they grow or where they work
21 (e.g., pole-ward shifting fishing grounds).
22
23 Climate hazards have increased over the past 50 years and are the major cause of sudden losses of production
24 (food production shocks). Food shocks occur following droughts, heatwaves, floods, storms, and outbreaks
25 of climate-related pests and combine to cause multiplying impacts. Climate hazards sometimes disrupt food
26 storage and transport, which impairs the food supply.
27
28 All of these negative impacts can lead to increased food prices, and reduced income for producers and
29 retailers as there are fewer products to sell. Together, these impacts threaten to reduce the supply of varied,
30 nutrient-rich foods to poor populations that already suffer ill health.
31
32
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1
2 Figure FAQ 5.1.1: Trends in food production shocks in different food supply sectors from 1961-2-13 (Cottrell et al.,
3 2019). The red lines in the time series are the annual shock frequency and the dashed line is the decadal mean.
4
5
6 [END FAQ5.1 HERE]
7
8
9 [START FAQ5.2 HERE]
10
11 FAQ5.2: How will climate change impact food availability by mid and late century and who will suffer
12 most?
13
14 Climate change impacts will worsen over time with the period after mid-century seeing more rapid growth in
15 negative impact than in the early part of this century. The impacts will be global but people with fewer
16 resources, and those who live in regions where impacts will worsen more rapidly, will be hurt the most.
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1
2 Climate change impacts will worsen over time, but the extent depends on how rapidly greenhouse gas
3 emissions grow. If the current rate of emissions continues, the impacts will worsen, especially after mid-
4 century with rapid growth in the number and severity of extreme weather events. Yields of plants, animals
5 and aquaculture will decline in most places and marine and inland fisheries will suffer. Food production in
6 some regions will become impossible, either because the crops or livestock there can't survive in the new
7 climatic conditions, or it is too hot and humid for farm workers to be in the fields.
8
9 After harvest, agricultural production passes through the agricultural value chain, supplying animal feeds,
10 industrial uses, and international markets, with some stored for use in the future. Each of these transitions
11 will be affected by climate change. Food storage facilities will face more challenges in dealing with spoilage.
12 Transportation of perishable fruits, vegetables, and meats will become costlier to maintain quality.
13 Households and food services will need to spend more on food preservation.
14
15 Low-income countries and poor people are at higher risk, as they have limited social safety nets, suffer more
16 from rising food prices, and an unstable food supply. But large famers will also be hurt. Rural communities,
17 especially smallholder farmers, pastoralists, and fishers, are extremely vulnerable because their livelihoods
18 mainly depend on their production. The urban poor will have to spend more on food.
19
20 A flood, for example, may force low-income families out of their homes, affect their employment and reduce
21 their access to food supplies, with prices often rising after natural disasters. Families will have less access to
22 safe water supplies, and this combination of lower food supplies, uncertain employment, displacement from
23 home and rising food costs will increase the number of children who are undernourished.
24
25
26
27 Figure FAQ5.2.1: Impacts of climate change in the food system
28
29
30 [END FAQ5.2 HERE]
31
32
33 [START FAQ5.3 HERE]
34
35
36 FAQ5.3: Land is going to be an important resource for mitigating climate change: How is the
37 increasing competition for land threatening global food security and who will be affected the
38 most?
39
40 Climate change will affect food production. To meet future food needs requires greater land shares unless
41 we change what we eat and how we grow food. Additionally, large scale land projects that aim to mitigate
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1 climate change will increase land competition. Less land will then be available for food production,
2 increasing food insecurity. People at greater risk from land competition are smallholder farmers, Indigenous
3 Peoples, and low-income groups.
4
5 Why is land important?
6
7 Land is a limited resource on which humans and ecosystems depend on to grow plants, which capture carbon
8 dioxide and release oxygen, provide food, timber, and other products. We also have cultural, recreational,
9 and spiritual connections to land.
10
11 Why will climate change affect land use?
12
13 Climate change results in more frequent heat waves, extreme rainfall, drought, and rising sea levels, which
14 negatively affect crop yields. More land is thus needed to grow crops, increasing land competition with other
15 food systems that use crops to feed their animals (e.g., livestock, fish). Where land will be flooded, humans
16 cannot grow crops, but food production could be adapted to grow seafood instead. Extensive land allocations
17 aiming at reducing carbon emissions e.g., afforestation, reduce land availability for food. Unless carefully
18 managed, competition for land will increase food prices and food security.
19
20 Solutions to reduce land competition and protect food security
21
22 Sustainable land management allows land to remain productive and support key functions. Other land
23 practices include growing cover crops to improve soil quality. Governments can provide incentives to
24 producers to grow alternative foods and use sustainable practices. Making sure that vulnerable groups (e.g.
25 low-income communities, Indigenous people, and small-scale producers) strengthen land tenure rights will
26 help protect food security.
27
28 Food by-products used as alternative food sources and other products reduce waste and increase
29 sustainability. Dietary changes are another important solution. People that eat high amounts of meat or
30 unhealthy foods could reduce consumption of these foods and have more diverse diets. These dietary
31 changes will benefit their health and reduce pressure on land. Regulated labelling, education and other
32 policies which encourage healthy diets can support these shifts.
33
34
35 5-165 Total pages: 286
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FINAL DRAFT Chapter 5 IPCC WGII Sixth Assessment Report
1 Figure FAQ5.3.1: Climate impacts will increase competition for land use reducing coastal land for crops, affecting
2 food security for vulnerable groups. Adaptation methods like coastal aquaculture and mangrove reforestation reduce
3 climate effects but may increase land competition.
4
5
6 [END FAQ5.3 HERE]
7
8
9 [START FAQ5.4 HERE]
10
11 FAQ5.4: What are effective adaptation strategies for improving food security in a warming world?
12
13 A variety of adaptation options exist to improve food security in a warming world. Examples of adaptation
14 for crop production include crop management and livelihood diversification. For livestock-based systems, an
15 example is matching number of animals with the production capacity of pastures. For fisheries, eliminating
16 overfishing is an effective adaptation practice. For mixed cropping and nature-based systems, an
17 appropriate adaptation is agroforestry.
18
19 Adaptation strategies to enhance food security vary from farm-level interventions to national policies and
20 international agreements. They cover the following dimensions of food security: availability, access,
21 utilization (food quality and safety), and stability.
22
23 For the production of crops, adaptation strategies include field and farm-level options such as crop
24 management, livelihood diversification, and social protection such as crop insurance. The most common
25 field management options are changes in planting schedules, crop varieties, fertilisers, and irrigation. For
26 example, farmers can shift their planting schedules in response to the early or late onset of the rainy season.
27 Moreover, there are new crop insurance schemes that are based on changes in weather patterns.
28
29 For livestock-based systems, adaptation options include matching the number of animals with the production
30 capacity of pastures; adjusting water management based on seasonal and spatial patterns of forage
31 production; managing animal diet; more effective use of fodder, rotational grazing; fire management to
32 control woody thickening of grass; using more suitable livestock breeds or species; migratory pastoralist
33 activities; and activities to monitor and manage the spread of pests, weeds, and diseases.
34
35 For ocean and inland fisheries, adaptation options are primarily concentrated in the socio-economic
36 dimension and governance and management. In general, eliminating overfishing could help rebuild fish
37 stocks, reduce ecosystem impacts, and increase fishing's adaptive capacity. Aquaculture is often viewed as an
38 adaptation option for fisheries declines. However, there are adaptation strategies specific to aquaculture such
39 as proper species selections at the operational level, such as the cultivation of brackish species (shrimp,
40 crabs) in inland ponds during dry seasons and rice-freshwater finfish in wetter seasons.
41
42 For so-called mixed farming systems that produce a combination of crops, livestock, fish, and trees, these
43 systems' inherent diversity provides a solid platform for adaptation. A good example is agroforestry, the
44 purposeful integration of trees or shrubs with crop or livestock systems, increases resilience against climate
45 risks.
46
47 Overall, nature-based systems or ecosystem-based strategies in food systems, such as agroecology, can be a
48 useful adaptation method to increase wild and cultivated food sources. Agroecological practices include
49 agroforestry, intercropping, increasing biodiversity, crop and pasture rotation, adding organic amendments,
50 integration of livestock into mixed systems, cover crops and minimizing toxic and synthetic inputs with
51 adverse health and environmental impacts.
52
53 [END FAQ5.4 HERE]
54
55
56 [START FAQ5.5 HERE]
57
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FINAL DRAFT Chapter 5 IPCC WGII Sixth Assessment Report
1 FAQ5.5: Climate change is not the only factor threatening global food security: other than climate
2 action, what other actions are needed to end hunger and ensure access by all people to nutritious
3 and sufficient food all year round?
4
5 Our food systems depend on many factors other than climate change, such as food production, water, land,
6 energy, and biodiversity. People's access to healthy food can be also be affected by factors such as poverty
7 and physical insecurity. We are all stakeholders in food systems, whether as producers or consumers, and we
8 can all contribute to the goal of a food-secure world by the choices we make in our everyday lives.
9
10 Today more than 820 million people are hungry, and hunger is on the rise in Africa. Two billion people
11 experience moderate or severe food shortages and another 2 billion suffer from overnutrition, a state of
12 obesity or being overweight from unbalanced diets, with related health impacts such as diabetes and heart
13 disease. The changing climate is already affecting food production. These effects are worsening, affecting
14 food production from crops, livestock, fish, and forests in many places where people already don't have
15 enough to eat. Food prices will be affected as a result, with increasing risk that poorer people will not be able
16 to buy enough for their families. Food quality will increasingly be affected too.
17
18 Our ability to grow and consume food depends on many factors other than climate change. There are tight
19 connections between food production, water, land, energy, and biodiversity, for example. Other factors like
20 gender inequality, poverty, political exclusion, remoteness from urban centres and physical insecurity can all
21 affect people's access to healthy food.
22
23 Food systems are complicated (Figure FAQ5.5). To improve food production, supply, and distribution, we
24 need to make changes throughout the food supply chain. For instance: improving the way farmers access the
25 inputs needed to grow food; improving the ways in which food is grown, with climate and market
26 information, training and technical know-how, water-saving and water-harvesting technologies; adopting
27 new low-cost and less carbon-intensive storage and processing methods; and creating local networks of
28 producers and processors For food consumers, we could consider shifts to different diets that are healthier
29 and make more efficient use of natural resources; depending on context, these could involve rebalancing
30 consumption of meat and highly processed foods, reducing food loss and waste, and preparing food in more
31 energy-efficient ways. Policy makers can enable such actions through appropriate price and trade policies,
32 implementing policies for sustainable and low-emission agriculture, providing safety nets where needed, and
33 empowering women, youth, and other socially disadvantaged groups.
34
35 Our food systems need to be robust and sustainable, otherwise we won't be able to manage the additional
36 pressures imposed on them by climate change. We can all contribute to this goal.
37
38
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