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

== 5.12 Food Security, Consumption and Nutrition ==

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=== 5.12.1 Introduction ===

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Food security and nutrition are key desired outcomes of food systems. Climate change is already contributing to reduced food security and nutrition and will continue to do so ( ''high confidence'' ) (Sections 5.4, 5.5, 5.8, 5.9, 5.10). Climate change impacts affect all four dimensions of food security: availability, access, utilisation and stability (Table 5.14), through both direct and indirect pathways.

'''Table 5.14 |''' Impacts from climate change drivers on the four dimensions of food security. Adapted from Table 5.1 in SRCCL.

{| class="wikitable"
|-
! '''CIDs and mechanism for food security impacts'''

! '''Examples of regions and groups most affected'''

! '''References'''

|-
| colspan="3"| '''Food security dimension: Availability'''

|-
| '''Increased heat and drought''' reduce crop and animal productivity and soil fertility and increase land degradation for some regions and crops.

| Countries in which a large proportion relies on agriculture for livelihoods.

Food production systems that rely on rainfed agriculture and pastoral rangeland. Urban populations and the poor.

| [[#FAO--2018|FAO et al. (2018)]] , [[#Dury--2019|Dury et al. (2019)]] , [[#Mbow--2019|Mbow et al. (2019)]] , [[#5.4|Section 5.4]] and 5.5).

|-
| '''Extreme heat''' affects crop productivity. Combined with high humidity reduces agricultural labour capacity and animal productivity.

| Countries and sectors that rely extensively on outdoor manual agricultural labour and experience high temperatures and humidity

| [[#Zander--2015|Zander et al. (2015)]] , [[#Kjellstrom--2016|Kjellstrom et al. (2016)]] , [[#Ioannou--2017|Ioannou et al. (2017)]] , [[#Mitchell--2017|Mitchell et al. (2017)]] , [[#FAO--2018|FAO et al. (2018)]] , [[#Flouris--2018|Flouris et al. (2018)]] , [[#Kjellstrom--2018|Kjellstrom et al. (2018)]] , Levi et al. (2018).

|-
| '''Increasing temperatures and precipitation changes''' increase and shift crop and livestock pests and diseases

| East African pastoral groups who experienced increased livestock morbidity and mortality from RVF in El Niño years.

| [[#Bebber--2015|Bebber (2015)]] , [[#FAO--2018|FAO et al. (2018)]] , [[#Mbow--2019|Mbow et al. (2019)]] , Sections 5.4.1.3 and 5.5.1.3

|-
| '''Increasing temperatures and drought stress''' has led to higher post-harvest losses due to mycotoxins.

| Tropical and subtropical regions with limited food safety surveillance

| [[#Miller--2016|Miller (2016)]] , [[#FAO--2018|FAO et al. (2018)]] , [[#5.11|Section 5.11]]

|-
| '''Rising ocean temperatures, marine heatwaves and ocean acidity''' has reduced availability of fish in coastal communities.

| Coastal people and coastal areas of tropical countries with high dependence on fisheries, e.g., West African coastal communities

| [[#Hilmi--2014|Hilmi et al. (2014)]] , [[#Golden--2016|Golden et al. (2016)]] , [[#Bindoff--2019|Bindoff et al. (2019)]] , [[#5.8|Section 5.8]] and 5.9

|-
| '''Increased number and intensity of extreme events such as cyclones''' lead to reduced food production and distribution from crop damage, increased pest incidence and transportation disruption.

| Delta regions where there are high populations and are often important food production regions, e.g., Cyclone Nargis in Myanmar estimated to reduce crop production by 19%, production declined for subsequent 3 years.

| [[#Omori--2020|Omori et al. (2020)]]

|-
| '''Increased atmospheric CO''' 2 '''concentrations''' increase total plant biomass and plant sugar content, which can increase crops as well as pests and weeds. High CO 2 also reduces transpiration during drought, which can increase plant drought resistance.

| All regions are anticipated to have increased atmospheric CO 2 concentrations, but due to impacts of other CIDs (e.g., drought, heat stress, pests), the impacts on crop growth, forage and subsequent food availability are mixed.

| [[#Iizumi--2018|Iizumi et al. (2018)]] ; [[#Canadell--2021|Canadell et al. (2021)]] , [[#Ranasinghe--2021|Ranasinghe et al. (2021)]] , Cross-Chapter Box MOVING PLATE this chapter)

|-
| colspan="3"| '''Food security dimension: Access'''

|-
| Increased '''drought''' and '''flood events''' and increased pests and disease from '''rising temperatures''' lead to loss of agricultural 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.

| Low-income smallholder farmers and pastoralists in Ethiopia, Mali, Niger, Malawi, Zambia and Tanzania.

| [[#Saronga--2016|Saronga et al. (2016)]] , [[#Giannini--2017|Giannini et al. (2017)]] , [[#FAO--2018|FAO et al. (2018)]] [[#Mbow--2019|Mbow et al. (2019)]] [[#Omori--2020|Omori et al. (2020)]]

|-
| Increase in number and intensity of '''extreme weather events (e.g., droughts, floods''' ) lead to increased food prices, which often leads to lower dietary diversity as well as lower consumption levels.

| Low-income consumers.

Women and girls.

| [[#FAO--2018|FAO et al. (2018)]] , [[#Mbow--2019|Mbow et al. (2019)]] , Ilboudo Nébié et al. (2021)

|-
| '''Extreme events''' (e.g., floods) disrupt food storage and transport networks, reducing access and availability of food supplies.

| Countries dependent on food imports, e.g., Small Island Developing States. Poor 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.

| [[#Toufique--2014|Toufique and Belton (2014)]] , [[#FAO--2018|FAO et al. (2018)]] , [[#Hickey--2020|Hickey and Unwin (2020)]] , Algur et al. (2021)

|-
| colspan="3"| '''Food security dimension: Utilisation (food quality and safety)'''

|-
| I '''ncreased temperatures''' reduce food safety caused by microorganisms, including increased mycotoxins in food and feed.

| Countries with limited food safety surveillance systems.

| [[#FAO--2018|FAO et al. (2018)]] , [[#Mbow--2019|Mbow et al. (2019)]] , [[#5.11|Section 5.11]]

|-
| Climate change '''extreme events''' make fruits and vegetables relatively unaffordable compared with less-nutrient-dense foods.

| Urban low-income households and rural households who purchase the majority of their food. Children in regions such as West Africa, with lower access to diverse food types as a result of climate impact drivers, e.g., drought.

| An et al. (2018), Algur et al. (2021), [[#Baker--2020|Baker and Anttila-Hughes (2020)]] , [[#Niles--2021|Niles et al. (2021)]]

|-
| '''Rising air temperature''' , '''ocean warming and high CO''' 2 '''conditions''' increase risk of food poisoning and pollutant contamination of food through increased prevalence of pathogens, HAB and increased contaminant bioaccumulation and threaten human health.

| Low-income tropical countries where current ability to reduce and monitor mycotoxin contamination is limited. Coastal Indigenous Peoples and other poor populations in coastal areas of tropical countries with high dependence on fisheries, e.g., west African coastal communities

| [[#Golden--2016|Golden et al. (2016)]] , [[#Bindoff--2019|Bindoff et al. (2019)]] , Sections 5.7, 5.8, 5.9, 5.11

|-
| '''Increased atmospheric CO''' 2 '''concentrations''' reduce nutritional quality of grains, some fruits and vegetables.

| Low-income households who have limited access to range of diverse foods.

| [[#Mbow--2019|Mbow et al. (2019)]] , [[#5.4|Section 5.4]]

|-
| '''Rising ocean temperatures, marine heatwaves and ocean acidity''' reduce fish populations, which reduces consumption of fish high in iron, zinc, omega-3 fatty acids and vitamins in areas where fish populations decline.

| Coastal areas of tropical countries; coastal Indigenous Peoples and other groups who rely on fisheries.

| [[#Golden--2016|Golden et al. (2016)]] ; [[#Bindoff--2019|Bindoff et al., 2019]] ; [[#5.7|Section 5.7]] , 5.8, 5.9

|-
| colspan="3"| '''Food security dimension: Stability'''

|-
| '''Increased frequency and severity of extreme events''' (e.g., '''droughts''' and '''heatwaves)''' lead to greater instability of supply through production losses and disruption to food transport.

| Landlocked countries; low-income countries reliant on imports; low-income households in areas prone to floods.

| [[#Toufique--2014|Toufique and Belton (2014)]] , [[#FAO--2018|FAO et al. (2018)]] , Algur et al. (2021), [[#5.11|Section 5.11]]

|-
| '''Increased drought''' and '''flood events''' and increased pests and disease from '''rising temperatures''' lead to unstable incomes from agriculture and fisheries.

| Small-scale producers (crops and livestock) and fishers

| Ruiz Meza, (2015), [[#FAO--2018|FAO et al. (2018)]] , Sections 5.8, 5.9

|-
| Climate change '''extreme events''' increase food prices due to climate shocks.

| Low-income countries reliant on imports; urban low-income households and rural households who purchase the majority of their food.

| [[#Bene--2015|Bene et al. (2015)]] , [[#Peri--2017|Peri (2017)]] , [[#Mbow--2019|Mbow et al. (2019)]] , [[#5.11|Section 5.11]]

|-
| '''Increased drought''' and '''flood events''' and increased pests and disease from '''rising temperatures''' cause widespread crop failure. '''Rising ocean temperatures, marine heatwaves and ocean acidity''' lead to dramatic decline in fisheries, contributing to migration and conflict.

| Coastal communities in West Africa, Southeast Asia and other tropical countries highly dependent on fisheries.

| [[#Golden--2016|Golden et al. (2016)]] , [[#Bindoff--2019|Bindoff et al. (2019)]] [[#Mbow--2019|Mbow et al. (2019)]]

|-
| '''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.

| Australia, most Asian regions, Europe, Central and South America and North America.

The benefits of yield gains at high latitudes may be tempered by greater risks of pests and pathogen damages.

| [[#Jones--2012|Jones and Barbetti (2012)]] , [[#IPPC%20Secretariat--2021|IPPC Secretariat (2021)]] , [[#Ranasinghe--2021|Ranasinghe et al. (2021)]]

|}

Global food security improved dramatically in the 20th century even as global population increased from 2 to 6 billion. While some may assume that global food security is primarily provided by large-scale producers, research since AR5 has shown the sizeable role of small and mid-sized food producers in Asia, Africa and Latin America contributing to global food security and nutrition, while being highly vulnerable to climate change impacts on food security ( [[#Samberg--2016|Samberg et al., 2016]] ; [[#Herrero--2017|Herrero et al., 2017]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Ricciardi--2018|Ricciardi et al., 2018]] ). In 2019, more than 750 million people in the world, almost 1 in 10 people, suffered from severe food insecurity, a figure which has risen since 2014 in every region except North America and Europe

( [[#FAO--2020|FAO et al., 2020]] ). Overnutrition, a result of high-calorie unbalanced diets, is also rising, with over 2 billion adults overweight or obese ( [[#FAO--2018|FAO et al., 2018]] ; [[#Swinburn--2019|Swinburn et al., 2019]] ; [[#FAO--2020|FAO et al., 2020]] ; [[#Venkatesh%20Mannar--2020|Venkatesh Mannar et al., 2020]] ; [[#WHO--2021|WHO, 2021]] ). Many low- and middle-income countries now have both high under- and overnutrition rates ( [[#FAO--2018|FAO et al., 2018]] ).

There are multiple drivers of food security, including changing dietary patterns, urbanisation and population growth ( [[#HLPE--2017b|HLPE, 2017b]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Swinburn--2019|Swinburn et al., 2019]] ). Vulnerability to climate change impacts on food insecurity and malnutrition is worsened by other underlying causes, including poverty, multiple forms of inequity (e.g., gender, racial, income), low access to water and sanitation, macroeconomic shocks and conflict ( [[#Smith--2015|Smith and Haddad, 2015]] ; [[#Clay--2018|Clay et al., 2018]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Cook--2019|Cook et al., 2019]] ). Climate change frequently acts to compound these drivers of food insecurity (Table 5.14).

The coronavirus disease 2019 (COVID-19) pandemic has increased vulnerability to food insecurity and malnutrition of particular groups and sectors in the food system, including low-income households, farmworkers, food service workers, informal food market sellers and low-income countries dependent on food imports (Cross-Chapter Box COVID in Chapter 7). Climate change will compound pandemic vulnerabilities in the food system ( ''high agreement'' , ''low evidence'' ) ( [[#HLPE--2020|HLPE, 2020]] ; UNDRR (United Nations Office for Disaster Risk Reduction, Regional Office for Asia and Pacific), 2020; [[#WFP-FSIN--2020|WFP-FSIN, 2020]] ). The pandemic may also increase coordination among sectors and a willingness to address food system weaknesses made visible by the impacts of COVID-19 ( [[#Blay-Palmer--2020|Blay-Palmer et al., 2020]] ; [[#Cohen--2020|Cohen, 2020]] ; [[#Ramos--2020|Ramos et al., 2020]] ).

Ecosystem services, the provisioning, supporting and regulating mechanisms we all depend on for food security and nutrition, are also undermined by climate change impacts ( [[#5.4.3|Section 5.4.3]] ). Even in the absence of climate change, our current food system threatens to exceed planetary, regional or local boundaries of long-term sustainable development ( [[#Campbell--2017|Campbell et al., 2017]] ). Climate change will make efforts to reduce this threat more difficult to achieve ( ''medium confidence'' ), though many solutions to enhancing food security are also potential climate change adaptation responses (Sections 5.4, 5.6, 5.8, 5.10, 5.14).

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=== 5.12.2 Mechanisms for Climate Change Impacts on Food Security ===

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Climate change is increasing the number of people experiencing food insecurity through greater incidence and severity of climatic impact drivers (CIDs), ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ) such as extreme heat, drought and floods. Increasing CO 2 concentrations have positive effects on food and forage crops by enhancing photosynthesis and alleviating drought stresses (5.4.3.1, 5.5.3.1) but have negative effects on nutrient concentrations in food crops. Ocean acidification is also caused by increasing CO 2 , causing negative impacts on aquatic systems. Tropospheric ozone concentrations already hinder crop production ( [[#5.4.1.4|Section 5.4.1.4]] ). Several CIDs increase the number of people experiencing food insecurity ( ''high confidence'' ) (SROCC 2019, [[#FAO--2018|FAO et al., 2018]] ; [[#Mbow--2019|Mbow et al., 2019]] ; [[#Baker--2020|Baker and Anttila-Hughes, 2020]] ; Table 5.12).

Vulnerability to climate impacts on food security and nutrition varies by region and group. Countries that experience CIDs such as extreme heat, severe drought or floods and have a large proportion of the population dependent on rainfed agriculture or livestock for their livelihoods and food supply have experienced rising food insecurity due to climate change impacts ( [[#FAO--2018|FAO et al., 2018]] ; [[#Cooper--2019|Cooper et al., 2019]] ; [[#Mbow--2019|Mbow et al., 2019]] ). Children in Sub-Saharan Africa are particularly at risk of undernutrition and mortality from increasing temperatures ( [[#Belesova--2019|Belesova et al., 2019]] ; [[#Baker--2020|Baker and Anttila-Hughes, 2020]] ). An additional estimated 5.9 million children became underweight because of rising temperatures in 51 countries affected by ENSO intensity in 2015–2016 ( [[#Anttila-Hughes--2021|Anttila-Hughes et al., 2021]] ). Low-income urban households and marginalised groups such as landless and ethnic minorities are at risk of increased food insecurity due in part to climate change extreme events such as extended drought, floods or cyclones that interrupt supply chains and impact livelihoods ( [[#Rodriguez-Llanes--2016|Rodriguez-Llanes et al., 2016]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Algur--2021|Algur et al., 2021]] ). A systematic review in India found that women often experience greater workloads and stress during drought events ( [[#Algur--2021|Algur et al., 2021]] ).

In the subsequent sections, the four dimensions of food security will be discussed in relation to observed and projected impacts and vulnerabilities (Table 5.14).

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=== 5.12.3 Observed Impacts ===

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<span id="impacts-on-food-availability"></span>
==== 5.12.3.1 Impacts on food availability ====

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All food production systems (crops, livestock, marine, fish, mixed, aquaculture) have been undermined by climate change and are expected to experience larger impacts in the future as described in earlier sections (see Sections 5.4.1, 5.5, 5.8, 5.9, 5.10). In addition, sudden production losses from extreme climate events can reduce food security ( [[#FAO--2018|FAO et al., 2018]] ; [[#Cottrell--2019|Cottrell et al., 2019]] ; [[#FAO--2020|FAO et al., 2020]] ; [[#Anttila-Hughes--2021|Anttila-Hughes et al., 2021]] ). For example, a 2007 drought-induced crop failure in southern Africa led to severe food insecurity in Lesotho because of the land-locked country’s dependence on imports from South Africa that aggravated food availability and access under conditions of declining food production and land degradation ( [[#Verschuur--2021|Verschuur et al., 2021]] ). Pest and disease outbreaks in both crops and livestock due to climate change (Sections 5.4.1, 5.5.1) have also impacted food availability and access (see Box 5.8 Desert Locust case study). Loss in labour productivity from climate-change-related heat stress is a growing problem.

Climate change affects agricultural labour productivity through increased intensity and frequency of heat stress events, with those performing physical labour in high humidity and ambient temperatures most vulnerable to heat stress ( ''high confidence'' ) (Hsiang et al.; [[#FAO--2018|FAO et al., 2018]] ; [[#Kjellström--2019|Kjellström et al., 2019]] ; [[#Antonelli--2020|Antonelli et al., 2020]] ; [[#Shayegh--2020|Shayegh et al., 2020]] ). Labour capacity, supply and productivity loss in moderate outdoor work due to heat stress is estimated between 2% and 14%, depending on the location and indicator ( [[#Ioannou--2017|Ioannou et al., 2017]] ; [[#Kjellstrom--2018|Kjellstrom et al., 2018]] ), with an overall estimate of 5.3% loss in productivity for outdoor work between 2000 and 2015 ( ''medium confidence'' ) ( [[#Watts--2018|Watts et al., 2018]] ) but as high as 14% in low-income tropical countries ( [[#Antonelli--2020|Antonelli et al., 2020]] ; [[#Shayegh--2020|Shayegh et al., 2020]] ). Highly vulnerable occupation groups affected by heat stress include farmers, farmworkers and livestock keepers working outdoors in low-income tropical countries ( ''high confidence'' ) ( [[#Zander--2015|Zander et al., 2015]] ; [[#Kjellstrom--2016|Kjellstrom et al., 2016]] ; [[#Flouris--2018|Flouris et al., 2018]] ; [[#Kjellstrom--2018|Kjellstrom et al., 2018]] ; [[#Levi--2018|Levi et al., 2018]] ). Farmworkers and small-scale food producers in high- and middle-income countries involved in outdoor labour are also affected by heat stress ( [[#Zander--2015|Zander et al., 2015]] ; [[#Gosling--2018|Gosling et al., 2018]] ; [[#Szewczyk--2018|Szewczyk et al., 2018]] ; [[#Watts--2021|Watts et al., 2021]] ). There is also evidence that heat stress is affecting labour supply through variation in nutrition intake ( [[#Antonelli--2020|Antonelli et al., 2020]] ).

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<span id="impacts-on-food-access-physical-economic-and-socio-cultural-and-vulnerabilities"></span>
==== 5.12.3.2 Impacts on food access (physical, economic and socio-cultural) and vulnerabilities ====

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Increased extreme events (e.g., droughts, floods and tropical storms; [[#Seneviratne--2021|Seneviratne et al., 2021]] ) due to climate change are key drivers of recent rises in food insecurity rates and severe food crises in some regions ( ''high confidence'' ) ( [[#5.4.1|Section 5.4.1]] , [[#Yeni--2017|Yeni and Alpas, 2017]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Cooper--2019|Cooper et al., 2019]] ; [[#Baker--2020|Baker and Anttila-Hughes, 2020]] ; [[#Bogdanova--2021|Bogdanova et al., 2021]] ; [[#Ilboudo%20Nébié--2021|Ilboudo Nébié et al., 2021]] ). Extreme weather events reduce physical and economic access to food, increase food prices, and compound underlying conditions of food insecurity and malnutrition such as low access to diverse healthy foods and safe water ( [[#FAO--2018|FAO et al., 2018]] ; [[#Niles--2021|Niles et al., 2021]] ). Increased incidence of severe drought conditions since 2005 is contributing to food insecurity in affected regions, including Africa, Asia and the Pacific (Chapter 7, [[#Phalkey--2015|Phalkey et al., 2015]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Cooper--2019|Cooper et al., 2019]] ; [[#Ilboudo%20Nébié--2021|Ilboudo Nébié et al., 2021]] ; [[#Verschuur--2021|Verschuur et al., 2021]] ;). In Arctic western Siberia, high temperatures, melting ice and forest and tundra fires have degraded reindeer pastures; Indigenous Peoples have reduced traditional diets and increased purchased food with increases in hypertension and related health impacts ( [[#Bogdanova--2021|Bogdanova et al., 2021]] ).

There is growing evidence that anthropogenic climate warming has already intensified climate extreme events induced by large-scale SST oscillations such as ENSO ( [[#Herring--2018|Herring et al., 2018]] ; [[#Seneviratne--2021|Seneviratne et al., 2021]] ). For example, the 2015–2016 El Niño, the strongest in the past 145 years, induced severe droughts in Southeast Asia and eastern and southern Africa, some intensified by anthropogenic warming ( [[#Funk--2018|Funk et al., 2018]] ). As a result, 20.5 million people faced acute food insecurity in 2016 ( [[#FSIN--2017|FSIN, 2017]] ) and an estimated additional 5.9 million children became underweight ( [[#Anttila-Hughes--2021|Anttila-Hughes et al., 2021]] ).

Weather extreme events increased food prices and food price volatility ( [[#Peri--2017|Peri, 2017]] ), thereby worsening food insecurity ( [[#Shiferaw--2014|Shiferaw et al., 2014]] ; [[#Bene--2015|Bene et al., 2015]] ; [[#Miyan--2015|Miyan, 2015]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Ilboudo%20Nébié--2021|Ilboudo Nébié et al., 2021]] ). Rising food prices can affect conflict, political instability and migration ( [[#Bush--2017|Bush and Martiniello, 2017]] ), but the relationship between climate change, political instability and conflict is often mediated by other underlying factors such as poor governance (Chapter 7.2.7, [[#Mach--2019|Mach et al., 2019]] ; [[#Selby--2019|Selby, 2019]] ).

Low-income urban and rural households who are net food buyers are particularly affected by food price increases, with reduction in consumption of diverse food groups ( ''high confidence'' ) ( [[#Green--2013|Green et al., 2013]] ; [[#Villasante--2015|Villasante et al., 2015]] ; [[#FAO--2018|FAO et al., 2018]] ). Depending on the context, particular groups, including women, ethnic and religious minorities, will be more vulnerable to worsening food insecurity from climate change impacts ( [[#Clay--2018|Clay et al., 2018]] ; [[#Jantarasami--2018|Jantarasami et al., 2018]] ; [[#Nature%20climate%20change%20Editorials--2019|Nature climate change Editorials, 2019]] ; [[#Algur--2021|Algur et al., 2021]] and see Cross-Chapter Box GENDER in Chapter 18). Indigenous Peoples are often more vulnerable to climate change, due to conditions of poverty, limited resources, discrimination and marginalisation ( ''high confidence'' ) ( [[#Smith--2016|Smith and Rhiney, 2016]] ; [[#Vinyeta--2016|Vinyeta et al., 2016]] ; [[#Jantarasami--2018|Jantarasami et al., 2018]] ). Indigenous Peoples may experience loss of culturally significant foods and declining traditional ecological knowledge ( [[#Dounias--2017|Dounias and Ichikawa, 2017]] ; [[#Ross--2020|Ross and Mason, 2020]] ; 5.7).

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<span id="impacts-on-food-utilisation-and-vulnerabilities"></span>
==== 5.12.3.3 Impacts on food utilisation and vulnerabilities ====

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Food utilisation refers to the way the body most effectively uses food, and includes food preparation, food quality and intra-household distribution. Food utilisation is affected by climate change in several ways: food safety, dietary diversity and food quality ( [[#Aberman--2014|Aberman and Tirado, 2014]] ).

Climate change have increased food safety risks ( ''high confidence'' ), including foodborne zoonotic animal diseases (5.5), and marine toxins from HABs (Sections 5.8, 5.9) and mycotoxins ( [[#5.11|Section 5.11]] ). Other foodborne and waterborne infectious diseases such as cholera are further covered in Chapter 7.

Weather variability and extreme events ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ) have reduced availability and access to diverse foods to sell and to purchase in rural markets, thereby reducing access to affordable, diverse foods for both rural small-scale producers and net consumers, particularly for landlocked and low-income countries ( ''high confidence'' ) ( [[#Pant--2014|Pant et al., 2014]] ; [[#Villasante--2015|Villasante et al., 2015]] ; [[#Alston--2016|Alston and Akhter, 2016]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Park--2019|Park et al., 2019]] ; [[#Niles--2021|Niles et al., 2021]] ) and otherwise marginalised communities ( [[#Algur--2021|Algur et al., 2021]] ). One study of 87 countries and 150 extreme events estimated that low-income food deficit and landlocked countries had reduced nutrient supply ranging from −1.6 to −7.6% of average supply, a significant portion of a healthy child’s average dietary intake ( [[#Park--2019|Park et al., 2019]] ).

Rural children in low-income countries are at particular risk of undernutrition from climate change impacts, due to a combination of factors: potential reduction in food quantity and quality from heat impacts; greater exposure from outdoor play and agricultural activities; and increased likelihood of heat exhaustion and vector-borne and diarrheal diseases ( [[#Oppenheimer--2016|Oppenheimer and Anttila-Hughes, 2016]] ). A study of child growth data in 30 countries in Africa between 1993 and 2012 found that increased temperature was significantly related to children’s wasting ( [[#Baker--2020|Baker and Anttila-Hughes, 2020]] ). Another study examined 30 years of climate data and child dietary diversity outcomes in 19 countries, and found that higher-than-average annual temperatures correlated with declines in child diet diversity at levels equal to or greater than other factors which often are the focus of policy, such as market access or education ( [[#Niles--2021|Niles et al., 2021]] ).

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<span id="impacts-on-food-stability"></span>
==== 5.12.3.4 Impacts on food stability ====

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Climate change has already changed the start and duration of the growing season and increased variability of rainfall in some places, with impacts on food intake and nutritional status and income for low-income and small-scale producers ( ''medium evidence'' , ''high agreement'' , ( [[#FAO--2018|FAO et al., 2018]] ; [[#Cooper--2019|Cooper et al., 2019]] ). Evidence to date suggests that climate change has negative impacts on the stability of food supply over the medium to long term, thereby affecting food stability ( [[#Myers--2017b|Myers et al., 2017b]] ). Increasing number and intensity of adverse weather events, driven by climate change ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ), are important factors decreasing food stability, through reduced availability, increased local price volatility, reduced livelihoods for food producers and disruption to food transport ( [[#Toufique--2014|Toufique and Belton, 2014]] ; [[#Verma--2014|Verma et al., 2014]] ; [[#Ruiz%20Meza--2015|Ruiz Meza, 2015]] ; [[#Clay--2018|Clay et al., 2018]] ; [[#FAO--2018|FAO et al., 2018]] ; [[#Mbow--2019|Mbow et al., 2019]] ).

<div id="box-5.9:-desert-locust-case-study:-climate-as-compounding-effect-on-food-security" class="h2-container box-container"></div>

'''Box 5.9: Desert Locust Case Study: Climate as Compounding Effect on Food Security'''
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At the end of 2019, desert locust swarms infested Eastern Africa and caused widespread damage to crops and pastures, threatening food security and livelihoods ( [[#Kimathi--2020|Kimathi et al., 2020]] ; [[#Salih--2020|Salih et al., 2020]] ). The FAO estimates that over 200,000 ha of crop and pastureland were damaged, rendering 2 million people in the region acutely food insecure ( [[#IGAD--2020|IGAD, 2020]] ). The desert locust infestation was facilitated by two tropical cyclones that created desert lakes in a usually dry region of Saudi Arabia. Moist soils, warm temperatures and ample vegetation provided a suitable environment for desert locust breeding and migration to Yemen and Somalia, where the pest remained uncontrolled due to conflict and spread to neighbouring countries. A series of political and socioeconomic weaknesses such as armed conflict, limited financial resources and lack of early actions compounded the impact of the current invasion and made it the most damaging in 70 years ( [[#Meynard--2020|Meynard et al., 2020]] ; [[#Salih--2020|Salih et al., 2020]] ).

Although desert locusts have been here for centuries, this recent outbreak can be linked to a unique feature of the positive IOD event, in part caused by long-term trends in SSTs ( [[#Wang--2020a|Wang et al., 2020a]] ). The warming of the western Indian Ocean has increased frequency and intensity of severe weather, including tropical cyclones ( [[#Roxy--2014|Roxy et al., 2014]] ; Murakami H, 2017; [[#Roxy--2017|Roxy et al., 2017]] ). Under a 1.5°C warmer climate, extreme positive IODs are anticipated to occur twice as often, which could also increase the occurrence of pest outbreaks ( [[#Cai--2018|Cai et al., 2018]] ).

Climate change increases the need for robust adaptation measures, such as transnational early-warning systems, biological control mechanisms, crop diversification and further technological innovations in areas of sound and light stimulants, remote sensing, and modelling for tracking and forecasting of movement ( [[#Maeno--2018|Maeno and Ould Babah Ebbe, 2018]] ; [[#Peng--2020|Peng et al., 2020]] ). The desert locust outbreak and the role of the Indian Ocean warming show that the impacts of climate change can increase unpredictable events. Extreme weather events act as a compounding effect, exacerbated further by weak governance systems, political instability, limited financial resources and poor early-warning systems ( [[#Meynard--2020|Meynard et al., 2020]] ).

<div id="5.12.4" class="h2-container"></div>

<span id="projected-impacts-on-food-security"></span>
=== 5.12.4 Projected Impacts on Food Security ===

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<div id="5.12.4.1" class="h3-container"></div>

<span id="food-availability-and-access"></span>
==== 5.12.4.1 Food availability and access ====

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Climate change will have negative effects on food security and nutrition in 2050 ( ''high agreement'' , ''medium evidence'' ) ( [[#Amjath-Babu--2016|Amjath-Babu et al., 2016]] ; [[#Springmann--2016|Springmann et al., 2016]] ; [[#Lloyd--2018|Lloyd et al., 2018]] ; [[#Richardson--2018|Richardson et al., 2018]] ; see Chapter 7; [[#Hasegawa--2021a|Hasegawa et al., 2021a]] ). How many people are affected will depend considerably on non-climatic drivers of food security ( [[#van%20Dijk--2021|van Dijk et al., 2021]] ), but modelling studies agreed that climate change would increase the risk of food insecurity. For example, one study comparing an RCP8.5 scenario with one that has zero climate impacts estimates 65 million additional people (10% increase) will experience food insecurity due to climate change impacts in 2050 (modelling results in [[#Nelson--2018|Nelson et al., 2018]] ). Another study accounting for climate extreme events estimates that, by 2050, the number of people at risk of hunger will increase by 20% and 11% under high- and low-emission scenarios, respectively, owing to a once-per-100-year extreme climate event ( [[#Hasegawa--2021a|Hasegawa et al., 2021a]] ). Sub-Saharan Africa and South Asia in this study were projected to be at the greatest risk, with triple the amount of South Asia’s current food reserves needed to offset such an extreme event. Models suggest that food security and malnutrition impacts will be much more severe from 2050 onwards relative to pre-2050, but the scale and extent of the impacts will strongly depend on the GHG emission scenario ( [[#FAO--2018a|FAO, 2018a]] ; [[#Richardson--2018|Richardson et al., 2018]] ). Due to CIDs and non-climate drivers of food insecurity, Sub Saharan Africa is projected to be the hardest hit, followed by South Asia and Central and South America, but contingent on adaptation level ( [[#Richardson--2018|Richardson et al., 2018]] ; [[#Hasegawa--2021a|Hasegawa et al., 2021a]] ).

Without adaptive measures, heat stress impacts on agricultural labour will increase with climate change ( ''high confidence'' ) ( [[#Im--2017|Im et al., 2017]] ; [[#Levy--2019|Levy and Roelofs, 2019]] ; [[#Hertel--2020|Hertel and de Lima, 2020]] ). Climate-change-related heat stress will reduce outdoor physical work capacity on a global scale. Depending on GHG concentrations, some regions will experience losses of 200–250 outdoor workdays per year at century’s end. Using results from one study reporting experimental procedures to assess loss of work capacity ( [[#Foster--2021|Foster et al., 2021]] ), regions hardest hit in an SSP5-8.5 scenario include much of South Asia, tropical Sub-Saharan Africa and parts of Central and South America (Figure 5.18). [[#de%20Lima--2021|de Lima et al. (2021)]] projected that negative impacts of warming on crop yields and labour capacity would affect crop production and cost for workers and labour-saving mechanisation, raising food price by 5% at +3° from the baseline period (1986–2005) globally, with significant implications for vulnerable regions (sub-Saharan Africa and Southeast Asia). Large uncertainties, however, exist around population diversity and adaptive capacity ( [[#Vanos--2019|Vanos et al., 2019]] ). Agricultural labour productivity impacts of heat attributed to climate change are expected to be worse in low- and middle-income countries ( [[#Kjellstrom--2016|Kjellstrom et al., 2016]] ). Adaptation options needed to protect agricultural worker productivity outdoors and reduce occupational heat illnesses and deaths include cooled working environments, improved surveillance systems and education on the need to monitor ( ''high confidence'' ) ( [[#Xiang--2016|Xiang et al., 2016]] ; [[#Quiller--2017|Quiller et al., 2017]] ; [[#Flouris--2018|Flouris et al., 2018]] ; [[#Day--2019|Day et al., 2019]] ; [[#Vanos--2019|Vanos et al., 2019]] ). Currently available options, however, are more difficult to achieve in lower-income economies ( [[#Kjellstrom--2016|Kjellstrom et al., 2016]] ; [[#Im--2017|Im et al., 2017]] ).

<div id="_idContainer073" class="Figure"></div>

[[File:c5f97e3d249455b4f00acfd5f50fead7 IPCC_AR6_WGII_Figure_5_018.png]]

'''Figure 5.18 |''' '''The number of days per year where physical work capacity (PWC) is less than 60% based on average daily air temperature and relative humidity (Foster et al.''' ''', 2021).''' PWC is defined as the maximum physical work output that can be reasonably expected from an individual performing moderate-to-heavy work in a ‘cool’ reference environment of 15°C. Values plotted are from the early (A) and end of century (B) for SSP5-8.5 using ensemble means from the ISI-MIP CMIP6 data set. See SM5.4 for details.

Under higher-emission scenarios, food availability will be further reduced after 2050, due to the potential for widespread crop failure and decline in livestock and fisheries stocks ( [[#Mbow--2014|Mbow et al., 2014]] ; [[#Kelley--2017|Kelley et al., 2017]] ; [[#Challinor--2018|Challinor et al., 2018]] ; [[#Hendrix--2018|Hendrix, 2018]] ; [[#Bindoff--2019|Bindoff et al., 2019]] ). At +3°C from the preindustrial era, all food production sectors will experience greater, and pronounced, losses due to climate change compared with +1.5°C or +2°C (see Sections 5.2, 5.4.3, 5.8.3 and 5.9.3).

Food insecurity from food price spikes due to reduced agricultural production associated with climate impact drivers such as drought can lead to both domestic and international conflict, including political instability ( [[#Abbott--2017|Abbott et al., 2017]] ; [[#Bush--2017|Bush and Martiniello, 2017]] ; [[#WEF--2017|WEF, 2017]] ; [[#D’Odorico--2018|D’Odorico et al., 2018]] ; [[#de%20Amorim--2018|de Amorim et al., 2018]] ;Chapter 7.2.7). While climate change impacts, including drought impacts on food security, are important risk factors for conflict, other key drivers are often more influential, including low socioeconomic development, limited state capacity, weak governance, intergroup inequities and recent histories of conflict ( ''medium confidence'' ) ( [[#Mach--2019|Mach et al., 2019]] ; [[#Selby--2019|Selby, 2019]] ; Chapter 7.2.7). The interaction between extreme weather events, conflict and human migration may increase vulnerability of particular communities of low-income countries ( [[#WEF--2017|WEF, 2017]] ; [[#D’Odorico--2018|D’Odorico et al., 2018]] ; [[#de%20Amorim--2018|de Amorim et al., 2018]] ; Chapter 7). Further research is needed to better understand how increased drought risk under future climate change might affect food prices and water availability ( [[#Abbott--2017|Abbott et al., 2017]] ).

<div id="5.12.4.2" class="h3-container"></div>

<span id="projected-impacts-on-food-safety-and-quality"></span>
==== 5.12.4.2 Projected Impacts on Food Safety and Quality ====

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Increasing levels of CO 2 directly contribute to reduced food quality by reducing levels of protein, iron, zinc and some vitamins, varying by crop species and cultivars ( ''high confidence'' ) ( [[#5.4.3|Section 5.4.3]] , [[#Myers--2014|Myers et al., 2014]] ; [[#Smith--2015|Smith and Haddad, 2015]] ; [[#Bisbis--2018|Bisbis et al., 2018]] ; [[#Scheelbeek--2018|Scheelbeek et al., 2018]] ; [[#Weyant--2018|Weyant et al., 2018]] ; [[#Zhu--2018a|Zhu et al., 2018a]] ). Higher levels of CO 2 are predicted to lead to 5–10% reductions in a wide range of minerals and nutrients ( [[#Loladze--2014|Loladze, 2014]] ). Climate warming will also reduce food quality of seafood, by changing the LC-PUFA content in phytoplankton ( [[#5.8|Section 5.8]] ; [[#Hixson--2016|Hixson and Arts, 2016]] ).

<div id="5.12.4.3" class="h3-container"></div>

<span id="reaching-sustainable-development-goal-2"></span>
==== 5.12.4.3 Reaching Sustainable Development Goal 2 ====

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Current projections indicate that it is ''highly likely'' that the UN SDG2 (‘Zero Hunger’) by 2030 will not be achieved, with climate impacts on one of several drivers of food security and nutrition preventing this goal, including in Africa, Small Island States and South Asia ( ''high confidence)'' ( [[#FAO--2018|FAO et al., 2018]] ; [[#Otekunrin--2019|Otekunrin et al., 2019]] ; [[#Singh--2019|Singh et al., 2019]] ; [[#Atukunda--2021|Atukunda et al., 2021]] ; [[#Kumar--2021|Kumar et al., 2021]] ; [[#Vogliano--2021|Vogliano et al., 2021]] ). Integrated policy strategies that consider synergies and trade-offs between different food system components would strengthen the likelihood of meeting SDG2 goals ( [[#Dyngeland--2020|Dyngeland et al., 2020]] ; [[#Lipper--2020|Lipper et al., 2020]] ; [[#Vogliano--2021|Vogliano et al., 2021]] ) ( [[#Grosso--2020|Grosso et al., 2020]] ). Adaptation options which address climate risks for food security and nutrition are discussed below.

<div id="box-5.10:-food-safety-interactions-with-food-security-and-malnutrition" class="h2-container box-container"></div>

'''Box 5.10: Food Safety Interactions with Food Security and Malnutrition'''
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Climate change significantly increases the future food safety risks ( ''high confidence'' ) (Sections 5.8.2, 5.8.3, 5.11.1, Box 5.9). Increasing temperatures and drought stress are expected to lead to greater aflatoxin contamination of food crops. Aflatoxins, a major foodborne hazard, contaminate staple crops and are associated with various health risks, including stunting in children and cancer ( [[#Koshiol--2017|Koshiol et al., 2017]] ). In LICs, children with high exposure to aflatoxins were found to be more likely to suffer from micronutrient (zinc and vitamin A) deficiencies ( [[#Watson--2016b|Watson et al., 2016b]] ). Climate change is expected to cause decreases in micro- and macronutrient content of foods, leading to an increased burden of infectious diseases, diarrhea and anaemia, with an estimated 10% increase in disability-adjusted life years (DALYs) by 2050 associated with undernutrition and micronutrient deficiencies ( [[#Aberman--2014|Aberman and Tirado, 2014]] ; [[#Smith--2018|Smith and Myers, 2018]] ; [[#Weyant--2018|Weyant et al., 2018]] ; [[#Zhu--2018a|Zhu et al., 2018a]] ; [[#Ebi--2019|Ebi and Loladze, 2019]] ; [[#FAO--2020a|FAO, 2020a]] ; [[#Sulser--2021b|Sulser et al., 2021b]] ).

Children in low-income countries will be at greater risk of undernutrition from these multiple climate change impacts, including lower food availability, quality and safety and increased risk of diarrheal disease ( ''high confidence'' ) ( [[#Aberman--2014|Aberman and Tirado, 2014]] ). One study of 30 countries in Africa estimated that, by 2100, increased temperatures under RCP8.5 could increase children’s wasting by 37% in western Africa and 25% in southern Africa ( [[#Baker--2020|Baker and Anttila-Hughes, 2020]] ).

The combination of climate change and the presence of arsenic in paddy rice fields is expected to increase the toxic heavy metal content of rice and reduce production by 2100, threatening food security and food safety mainly in low-income countries where rice is the main staple ( [[#Neumann--2017|Neumann et al., 2017]] ; [[#Muehe--2019|Muehe et al., 2019]] ; [[#Farhat--2021|Farhat et al., 2021]] ).

'''Table 5.17 |''' Examples of adaptation responses to drought and floods by food security level and time frame. Adapted from Ilboudo Nébié et al. (2021) Table 4, with information from [[#Bahadur--2015|Bahadur et al. (2015)]] ; [[#Costella--2017|Costella et al. (2017)]] ; [[#Gros--2019|Gros et al. (2019)]] ; Ulrichs et al. (2019); [[#Medina%20Hidalgo--2020|Medina Hidalgo et al. (2020)]] ; [[#Bacon--2021|Bacon et al. (2021)]] ; and [[#Verschuur--2021|Verschuur et al. (2021)]] .

{| class="wikitable"
|-
!
! colspan="3"| '''Food insecurity level and time frame of adaptation'''

!
|-
! '''Adaptation response to drought or floods'''

! '''Acute, s''' '''hort ter''' '''m'''

! '''Moderate,''' '''medium ter''' '''m'''

! '''Chronic, l''' '''ong ter''' '''m'''

! '''Resilience type'''

|-
| Forecast-based financing (provides unconditional cash in advance of extreme event)

| X

|
| rowspan="3"| ''Anticipatory'' : people and systems are better prepared for climate shock by reduced exposure or vulnerability.

|-
| Early-warning systems/climate services and education for disaster preparation

| X

| X

| X

|-
| Social protection programmes with regular provisions which allow for asset building, e.g., savings, building of informal networks, purchase of livestock

| X

| X

|
|-
| Humanitarian food aid and malnutrition treatment

| X

| X

|
| rowspan="4"| ''Absorptive capacity'' : people or systems cope with climate-related shocks or systems while and immediately after they occur.

|-
| Home-grown nutrition-sensitive school feeding programmes

|
| X

| X

|-
| Social protection programmes with short-term targeted response, e.g., short-term cash transfers, food assistance for asset building such as wells

| X

|
|-
| Weather index insurance program

| X

| X

| X

|-
| Regional grain banks run by farmer associations

|
| X

| X

| rowspan="7"| ''Adaptive capacity'' : can adjust to long-term climate risks and disasters, reduce vulnerability to future shocks.

|-
| Savings, credit and local food procurement support for smallholder farmers

|
| X

| X

|-
| Agroecosystem diversification, other agroecological practices to strengthen ecosystem services in long term (see Box 5.10)

|
| X

| X

|-
| Rainwater evacuation infrastructure combined with flood management and waste collection and urban gardening

|
| X

| X

|-
| Drought- or flood-resistant crop varieties

|
| X

| X

|-
| Expand trade partners beyond climactically connected partners

|
| X

| X

|-
| Gender transformative or responsive agriculture programmes

|
| X

| X

|}

<div id="5.12.5" class="h2-container"></div>

<span id="adaptation-options-for-food-security-and-nutrition"></span>
=== 5.12.5 Adaptation Options for Food Security and Nutrition ===

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Since AR5, there has been increased research on adaptation options that address climate risks for food security and nutrition. In this section, cultivar improvements, urban and peri-urban agriculture, changing dietary patterns, integrated multi-sectoral approaches and rights-based approaches are assessed for their potential as an adaptation option that addresses food security and nutrition. Feasibility and effectiveness assessment of several options is in [[#5.1|Section 5.1]] 4.

<div id="5.12.5.1" class="h3-container"></div>

<span id="potential-barriers-and-challenges-for-genetically-modified-crops-to-address-food-security-and-nutrition"></span>
==== 5.12.5.1 Potential, barriers and challenges for genetically modified crops to address food security and nutrition ====

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While biotechnology can be used as an adaptation strategy ( [[#5.4.4.3|Section 5.4.4.3]] ), there is low confidence that genetically modified (GM) crops can increase food security and nutrition in smallholder farming systems relative to alternative agronomic strategies ( [[#National%20Academies%20of%20Sciences%20Engineering%20and%20Medicine--2016|National Academies of Sciences Engineering and Medicine, 2016]] ; [[#Qaim--2016|Qaim, 2016]] ). Some underline their potential in building resilience to changing climatic conditions, in the form of enhanced drought/heat tolerance, pest/disease protection and/or reduced land usage, thus serving to bolster food security and nutrition ( [[#Sainger--2015|Sainger et al., 2015]] ; [[#Muzhinji--2021|Muzhinji and Ntuli, 2021]] ). Others suggest that the empirical evidence supporting GM crops as a climate-resilience strategy remains thin ( [[#Leonelli--2018|Leonelli, 2018]] ). Technical and social barriers and potential solutions are summarised in Table 5.15.

'''Table 5.15 |''' Barriers, challenges and potential solutions for GM crops.

{| class="wikitable"
|-
! '''Barriers and challenges'''

! '''Examples and potential solutions to barriers'''

|-
| Major challenges as a food security and nutrition adaptation include the introgression of GM traits into host varieties ( [[#Dowd-Uribe--2014|Dowd-Uribe, 2014]] ), and confusion around proper growing practices that can accelerate resistance ( [[#Iversen--2014|Iversen et al., 2014]] ; [[#Fischer--2015|Fischer et al., 2015]] ). The combination of the kinds of traits and restrictions that come from the predominant intellectual property rights instruments used in their commercialisation, and concentration of plant and animal breeding industry ( [[#Bonny--2017|Bonny, 2017]] ) mean that benefits from released GM crops tend to be captured disproportionately by farmers with more land, wealth and education ( [[#Afidchao--2014|Afidchao et al., 2014]] ; [[#Ali--2018|Ali and Rahut, 2018]] ; [[#Azadi--2018|Azadi et al., 2018]] ) but also increase debt levels for growers ( [[#Dowd-Uribe--2014|Dowd-Uribe, 2014]] ; [[#Leguizamón--2014|Leguizamón, 2014]] ).

Underlying gender inequities also play a critical role in shaping food security and nutrition outcomes associated with the introduction of GM crops, in part due to unequal control over income and agricultural decision making; in some cases, women reported decreased workload and enhanced decision-making power ( [[#Gouse--2016|Gouse et al., 2016]] ), while in others the introduction of GM crops could increase workload and devalue womens’ role as seed savers ( [[#Carro-Ripalda--2014|Carro-Ripalda and Astier, 2014]] ; [[#Addison--2016|Addison and Schnurr, 2016]] ).

Major hurdles for GM crops include translating promising research results into real-world farming systems and consumer trust in the food product. Experimental programmes have been dogged by issues, including complications with the introgression of GM traits into high-performing varieties ( [[#Dowd-Uribe--2016|Dowd-Uribe and Schnurr, 2016]] ; [[#Stone--2017|Stone and Glover, 2017]] ), strict management regimes that clash with the realities of smallholder agricultural systems ( [[#Iversen--2014|Iversen et al., 2014]] ; [[#Whitfield--2015|Whitfield et al., 2015]] ), and a lack of attention to farmer decision making ( [[#Schnurr--2019|Schnurr, 2019]] ).

| One case study is the Water Efficient Maize for Africa (WEMA) programme, a public–private partnership that transplants a cold shock protein B, known as Droughtgard, into maize in order to mitigate yield losses from drought. Proponents suggest that this GM venture, which will be distributed free to smallholder farmers, represents the best strategy for ensuring stable yields in the face of climatic change across Africa ( [[#Kyetere--2019|Kyetere et al., 2019]] ). Critics argue that WEMA maize is not a good fit with the smallholder farming systems it is designed to benefit, with particular concerns around how farmers will access the extra inputs, credit and labour that WEMA maize requires to be successful ( [[#Schnurr--2019|Schnurr, 2019]] ).

Emergent genome-edited crops are considered a more precise, accessible and accelerated means of targeting stressors that matter to poor farmers, but evidence is limited ( [[#Kole--2015|Kole et al., 2015]] ; [[#Haque--2018|Haque et al., 2018]] ; [[#Zaidi--2019|Zaidi et al., 2019]] ). A more iterative and flexible adaptation approach beyond just genomic improvement to tackle the multiplicity of factors limiting smallholder production is anticipated to increase the likelihood that these promising technologies can enhance food security and nutrition ( ''medium confidence'' ) ( [[#Giller--2017|Giller et al., 2017]] ; [[#Stone--2017|Stone, 2017]] ; [[#Montenegro%20de%20Wit--2019|Montenegro de Wit, 2019]] ).

To address food security and nutrition, future breeding needs to move from just enhancing agronomic traits of a single crop to improving multiple traits of multiple crops suited to local conditions that will increase climate resilience of farming systems. To make breeding technologies scale-neutral, the policy structure needs to support and protect smallholders ( ''medium confidence'' ).

|}

<div id="5.12.5.2" class="h3-container"></div>

<span id="urban-and-peri-urban-agriculture-vertical-and-horizontal"></span>
==== 5.12.5.2 Urban and peri-urban agriculture, vertical and horizontal ====

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Urban areas have more than half of the global population and consume about 70% of the total food supply ( [[#FAO--2019b|FAO, 2019b]] ). The urban population is projected to grow further to about 70% of the global population by 2050 ( [[#UN--2018|UN, 2018]] ). Direct evidence supporting climate resilience of urban and peri-urban agriculture (UPA) is limited and contextual, but there is ''medium confidence'' of multi-functional benefits from UPA, depending on regions and types of UPA ( [[#Artmann--2018|Artmann and Sartison, 2018]] ; [[#Kareem--2020|Kareem et al., 2020]] ). UPA takes different forms of production, and can be broadly classified into four categories, depending on operating characteristics and capital inputs (Table 5.16) ( [[#Goldstein--2016|Goldstein et al., 2016]] ). Controlled environments can protect crops, livestock and fish from extreme weather events or pest and disease outbreak ( [[#Mohareb--2017|Mohareb et al., 2017]] ). Innovative indoor farming such as vertical farming can be highly productive with minimal water and nutrient supply but can be capital intensive with high energy demand ( [[#O’Sullivan--2019|O’Sullivan et al., 2019]] ), and those with aquaponics can be water demanding ( [[#Love--2015|Love et al., 2015]] ). Currently, commodities are often limited to crops with short growing seasons such as leafy vegetables. Vertically grown crops are more expensive than field-grown produce and, thus, not accessible for low-income urban dwellers ( [[#Al-Kodmany--2018|Al-Kodmany, 2018]] ). Community and institutional unconditioned (outdoor) farms and gardens are better positioned to provide increased access to healthy food to those who need it ( [[#Eigenbrod--2015|Eigenbrod and Gruda, 2015]] ; [[#Goodman--2019|Goodman and Minner, 2019]] ).

'''Table 5.16 |''' Urban agriculture classifications based on operating characteristics and capital inputs ( [[#Goldstein--2016|Goldstein et al., 2016]] ; [[#O’Sullivan--2019|O’Sullivan et al., 2019]] ), and a summary of literature search on positive and negative aspects.

{| class="wikitable"
|-
! colspan="3"| '''Summary of urban and peri-urban agriculture and evidence for improved food security and nutrition'''

|-
! colspan="3"| ''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--2014|Revi et al., 2014]] ; [[#Artmann--2018|Artmann and Sartison, 2018]] ; [[#FAO--2019b|FAO, 2019b]] ; [[#Mbow--2019|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--2014|Martellozzo et al., 2014]] ; [[#Badami--2015|Badami and Ramankutty, 2015]] ; [[#Algert--2016|Algert et al., 2016]] ; [[#Mohareb--2017|Mohareb et al., 2017]] ; [[#Clinton--2018|Clinton et al., 2018]] ; [[#Kriewald--2019|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 Description'''

! '''Synergies'''

! '''Trade-offs'''

|-
| ''Ground-based Unconditioned''

| rowspan="4"| * Multi-species cropping can increase access to diverse healthy foods and reduce food costs for low-income households ( [[#Algert--2016|Algert et al., 2016]] ; [[#Horst--2017|Horst et al., 2017]] ).
* Green cover helps to attenuate heat island effects, and reduce runoff and flood risks ( [[#Lwasa--2015|Lwasa et al., 2015]] ; [[#Di%20Leo--2016|Di Leo et al., 2016]] ; [[#Gondhalekar--2017|Gondhalekar and Ramsauer, 2017]] ; [[#Artmann--2018|Artmann and Sartison, 2018]] ; [[#Small--2019|Small et al., 2019]] ).
* Green garden spaces can reduce vulnerability to heat stress and food insecurity for low-income neighbourhoods and address racial inequities in access to green spaces if UA governance addresses equity concerns ( [[#Horst--2017|Horst et al., 2017]] ; [[#Titz--2019|Titz and Chiotha, 2019]] ; [[#Halvey--2020|Halvey et al., 2020]] ; [[#Hoffman--2020|Hoffman et al., 2020]] ).
* Multi-species cropping helps to conserve biodiversity ( [[#Lovell--2010|Lovell, 2010]] ; [[#Goldstein--2016|Goldstein et al., 2016]] ).
* Skill building and job opportunities ( [[#Lovell--2010|Lovell, 2010]] ; [[#Mok--2014|Mok et al., 2014]] ; [[#Horst--2017|Horst et al., 2017]] ), sometimes in regions and for groups that have been socially and economically disadvantaged ( [[#Horst--2017|Horst et al., 2017]] ).
* CES benefits through cultivation of specific crops, cultural learning, sharing culinary and garden knowledge and strengthening social networks for socially marginalised ethnic, racial groups ( [[#Horst--2017|Horst et al., 2017]] ; [[#Nadeau--2019|Nadeau et al., 2019]] ).
* UPA provides social and health co-benefits such as increased social interaction and physical and mental health benefits ( [[#Horst--2017|Horst et al., 2017]] ; [[#White--2017|White and Bunn, 2017]] ).
* Can divert organic waste produced in cities as compost, to reduce water contamination and input costs ( [[#Menyuka--2020|Menyuka et al., 2020]] ).

| rowspan="4"| * Can increase the value of land and thereby push out lower-income households via gentrification ( [[#Horst--2017|Horst et al., 2017]] ).
* Unconditioned UPA is under strong pressure from other lucrative land use demands and can be difficult to maintain without addressing urban social inequities, ( [[#Martellozzo--2014|Martellozzo et al., 2014]] ; [[#Horst--2017|Horst et al., 2017]] ; [[#White--2017|White and Bunn, 2017]] ).
* Yields are lower than conventional, rural production, and water demand is high ( [[#Goldstein--2016|Goldstein et al., 2016]] ; [[#Bisaga--2019|Bisaga et al., 2019]] ).
* Air, soil and water quality in urban areas can disturb crop production and reduce food safety ( [[#Eigenbrod--2015|Eigenbrod and Gruda, 2015]] ; [[#Titz--2019|Titz and Chiotha, 2019]] ), and create health risks from contamination ( [[#Mok--2014|Mok et al., 2014]] ), causing mixed or even negative public perceptions against the produce ( [[#Specht--2019|Specht et al., 2019]] ; [[#Menyuka--2020|Menyuka et al., 2020]] ). Trace metal contamination in soils and plants is an increased risk in outdoor UPA ( [[#Eigenbrod--2015|Eigenbrod and Gruda, 2015]] ; [[#Titz--2019|Titz and Chiotha, 2019]] ).
* May provide limited job and income opportunities in low-income urban areas ( [[#Daftary-Steel--2015|Daftary-Steel et al., 2015]] ; [[#Biewener--2016|Biewener, 2016]] ).
* Outdoor fields are exposed to rising temperatures and urban heat islands ( [[#Chapman--2017|Chapman et al., 2017]] ). Low water availability may be another limit for UPA as a form of adaptation ( [[#Kareem--2020|Kareem et al., 2020]] ; [[#Tankari--2020|Tankari, 2020]] ). In coastal cities, sea level rise and flooding from climate change impacts may make significant portions of cities unuseable for UPA ( [[#Algert--2016|Algert et al., 2016]] ; [[#Kareem--2020|Kareem et al., 2020]] ).

|-
| Traditional, peri-urban field farms, market gardens, community farms, community gardens, home gardens.

|-
| ''Building-integrated Unconditioned''

|-
| Rooftop gardens, balcony agriculture, and green wall, but production quantity is small.

|-
| ''Ground-based Conditioned''

| rowspan="4"| * Controlled environments can protect crops, livestock and fish from extreme weather events or pest and disease outbreak ( [[#Mohareb--2017|Mohareb et al., 2017]] ).
* Some building-integrated conditioned farms can utilise wastewater and waste heat from buildings or other urban source ( [[#De%20Zeeuw--2011|De Zeeuw et al., 2011]] ; [[#Thomaier--2015|Thomaier et al., 2015]] ; [[#Mohareb--2017|Mohareb et al., 2017]] ).
* Innovative indoor farming such as vertical farming (VF) is highly productive with minimal water and nutrient supply, but highly energy-demanding ( [[#O’Sullivan--2019|O’Sullivan et al., 2019]] ).
* Some initiatives combine with social justice goals and use abandoned buildings in low-income neighbourhoods to grow diverse food types for addressing food security of low-income groups ( [[#Thomaier--2015|Thomaier et al., 2015]] ; [[#Horst--2017|Horst et al., 2017]] ).

| rowspan="4"| * Power outages and/or system failure can easily destroy the production system ( [[#Small--2019|Small et al., 2019]] ).
* Initial costs and energy requirements are substantially higher than those of unconditioned farms ( [[#Goodman--2019|Goodman and Minner, 2019]] ; [[#O’Sullivan--2019|O’Sullivan et al., 2019]] ).
* GHG emissions may be higher than conventional rural agriculture ( [[#Santo--2016|Santo et al., 2016]] ) and full mitigation potential only realised with low-energy systems (WGIII, 12.4).
* Commodities are often limited to short-cycled crops such as leafy vegetables and herbs, and the produce is more expensive, making it difficult for the urban poor to access ( [[#O’Sullivan--2019|O’Sullivan et al., 2019]] ).

|-
| Horticultural farms using glasshouses or polyhouses. Often exist on the city fringes.

Aquaponics that grow fish in aquaculture systems and re-use nutrient-rich wastewater. One of the few options that provide proteins in urban farms.

|-
| ''Building integrated Conditioned''

|-
| 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.

|}

Many UPA farmers are migrant workers or other socially marginalised racial and ethnic groups and often limited by access to land ( [[#Lawanson--2014|Lawanson et al., 2014]] ; [[#Horst--2017|Horst et al., 2017]] ). There is ''high agreement'' that proactive policies for urban design accounting for food–energy nexus and social inclusion including addressing questions of governance and rights to green urban spaces are necessary to enhance food provisioning and to gain multiple functions of UPA ( [[#Lwasa--2014|Lwasa et al., 2014]] ; [[#Horst--2017|Horst et al., 2017]] ; [[#Mohareb--2017|Mohareb et al., 2017]] ; [[#Siegner--2018|Siegner et al., 2018]] ; [[#O’Sullivan--2019|O’Sullivan et al., 2019]] ; [[#Titz--2019|Titz and Chiotha, 2019]] ; [[#Halvey--2020|Halvey et al., 2020]] ).

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<span id="changing-dietary-patterns"></span>
=== 5.12.6 Changing Dietary Patterns ===

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Dietary change in regions with excess consumption of calories and animal-sourced foods to a higher share of plant-based foods with greater dietary diversity and reduced consumption of animal-sourced foods and unhealthy foods (as defined by scientific panels such as EAT-Lancet) has both mitigation and adaptation benefits along with reduced mortality from diet related non-communicable diseases, health, biodiversity and other environmental co-benefits ( ''high confidence'' ) ( [[#Springmann--2016|Springmann et al., 2016]] ; [[#Springmann--2018|Springmann et al., 2018]] ; [[#Branca--2019|Branca et al., 2019]] ; [[#Henry--2019|Henry et al., 2019]] ; [[#Searchinger--2019|Searchinger et al., 2019]] ; [[#Swinburn--2019|Swinburn et al., 2019]] ; [[#Willett--2019|Willett et al., 2019]] ; [[#Rosenzweig--2020|Rosenzweig et al., 2020]] ; Chapter 7.4.2.1.3 and WGIII Chapter 12). Reducing food waste, especially of environment- and climate-costly foods would further extend these benefits ( [[#Rosenzweig--2020|Rosenzweig et al., 2020]] and see [[#5.11|Section 5.11]] ).

Dietary behaviour is complex: shaped by the broader food system ( [[#HLPE--2017a|HLPE, 2017a]] ), the food environment ( [[#Herforth--2015|Herforth and Ahmed, 2015]] ; [[#Turner--2018|Turner et al., 2018]] ) and socio-cultural factors ( [[#Fischler--1988|Fischler, 1988]] ). Since most food-related decisions are made at a subconscious level ( [[#Marteau--2012|Marteau et al., 2012]] ), achieving dietary change for personal health reasons has proven difficult; it seems unlikely that dietary change for climate will be achieved without careful attention to the factors that shape dietary choice and behaviour. Food environments, defined as ‘the physical, economic, political and socio-cultural context in which consumers engage with the food system to make their decisions about acquiring, preparing and consuming food’ ( [[#HLPE--2017a|HLPE, 2017a]] ): 28), include food availability, accessibility, price/ affordability, food characteristics, desirability, convenience and marketing.

There are a range of options to change dietary patterns, but more research is needed in this area, adjusted to the regional, socioeconomic and cultural context. Studies of policy instruments to change diets include changes in subsidies, taxes, marketing regulation and efforts to change the retail physical environment. Subsidies directed at staple foods and animal sourced foods could be shifted towards diversified production of plant-based foods in order to change the relative price of foods and, thus, dietary choice ( [[#Franck--2013|Franck et al., 2013]] ; [[#Harris--2021|Harris et al., 2021]] ). Taxes on animal-sourced foods that are climate-costly and unhealthy, as defined by scientific panels such as the EAT-Lancet report, could similarly impact relative price ( [[#Mbow--2019|Mbow et al., 2019]] ; [[#Willett--2019|Willett et al., 2019]] ). Regulation of marketing could change desirability of climate-unfriendly and unhealthy foods ( [[#Willett--2019|Willett et al., 2019]] ). Many of the same strategies used to increase sales by conventional food marketing efforts hold potential to change the desirability and people’s preferences for plant foods which are strongly shaped by social–cultural norms. Studies have shown that changes to the number, placing or prevalence of vegetarian options on a menu ( [[#Bacon--2018|Bacon and Krpan, 2018]] ; [[#Kurz--2018|Kurz, 2018]] ; [[#Garnett--2019|Garnett et al., 2019]] ; [[#Gravert--2019|Gravert and Kurz, 2019]] ), the relative price of vegetarian options ( [[#Garnett--2021|Garnett et al., 2021]] ) and the ‘access’ (order and distance) to vegetarian options in the retail physical environment ( [[#Garnett--2020|Garnett et al., 2020]] ) can all increase consumption of plant-based foods and decrease meat consumption ( [[#Bianchi--2018|Bianchi et al., 2018]] ). Studies on food environment ‘nudging’ methods found that making the vegetarian meal option the default during conference registration or on a meal plan significantly reduced meat consumption ( [[#Campbell-Arvai--2012|Campbell-Arvai et al., 2012]] ; [[#Hansen--2019b|Hansen et al., 2019b]] ). Studies simply educating people about the negative health and environmental/climate outcomes of meat consumption have been found to have very little impact ( [[#Byerly--2018|Byerly et al., 2018]] ). More research is needed to understand the potential for motivational crowding in shaping pro-climate dietary choice, as has been demonstrated in development ( [[#Agrawal--2015|Agrawal et al., 2015]] ) and conservation interventions ( [[#Rode--2015|Rode et al., 2015]] ).

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<span id="integrated-multisectoral-food-security-and-nutrition-adaptation-options"></span>
=== 5.12.7 Integrated Multisectoral Food Security and Nutrition Adaptation Options ===

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Integrated multi-sectoral strategies that incorporate social protection are effective adaptation responses ( ''high confidence'' ) ( [[#Gros--2019|Gros et al., 2019]] ; [[#Ulrichs--2019|Ulrichs et al., 2019]] ; [[#Medina%20Hidalgo--2020|Medina Hidalgo et al., 2020]] ; [[#Daron--2021|Daron et al., 2021]] ; [[#Ilboudo%20Nébié--2021|Ilboudo Nébié et al., 2021]] ; [[#Verschuur--2021|Verschuur et al., 2021]] ; 7.4.2, Cross-Chapter Box-GENDER in Chapter 18). Social protection programmes, such as cash transfers, weather index insurance and asset-building activities such as well construction, can support short-term responses to acute food insecurity in response to extreme events but can also build adaptive capacity longer term (Table 5.16, [[#Costella--2017|Costella et al., 2017]] ; [[#Ulrichs--2019|Ulrichs et al., 2019]] ). An assessment of an adaptive social protection programme in the Sahel found that tailored seasonal forecasting can improve responsiveness to climate-related extreme events, but investment in capacity building and dialogue between forecasters, community groups and humanitarian organisations is needed ( [[#Daron--2021|Daron et al., 2021]] ). Forecast-based financing, which automatically disperses funds when threshold forecasts are reached for an extreme event ( [[#Coughlan%20de%20Perez--2016|Coughlan de Perez et al., 2016]] ), used in Bangladesh prior to a 2017 flood event allowed low-income, flood-prone communities to access better-quality food in the short term without accruing debt ( [[#Gros--2019|Gros et al., 2019]] ).

Differentiated responses based on food security level and climate risk can be effective. A study of drought impacts on food security in Senegal between 1997 and 2016 recommended different adaptation strategies based on whether the region was a higher risk of acute short-term food insecurity and/or faced higher risk of drought (Table 5.16; [[#Ilboudo%20Nébié--2021|Ilboudo Nébié et al., 2021]] ). Given identified linkages between higher temperatures and extreme events with declines in child dietary diversity, safeguarding diverse diets is one important adaptation priority ( [[#Niles--2021|Niles et al., 2021]] ). Humanitarian responses are appropriate for short-term acute hunger, while in the medium term, home-grown school feeding programmes with diverse foods can support child nutrition and learning, and with local procurement can also increase income and food security of smallholder farmers ( [[#Ilboudo%20Nébié--2021|Ilboudo Nébié et al., 2021]] ). Farmer associations can manage regional staple food storehouses, in which farmers store their harvest and receive credit, and can sell their harvest later in the season and pay back the credit with interest, strengthening local supplies and farmer income ( [[#Ilboudo%20Nébié--2021|Ilboudo Nébié et al., 2021]] ).

A study in Lesotho examined the extent to which climate change increased the likelihood of an acute drought in 2007, and a related food crisis ( [[#Verschuur--2021|Verschuur et al., 2021]] ). Given land degradation, reliance on rainfed agriculture and food imports from neighbouring South Africa, the study recommended crop diversification, increased use of drought tolerant crop varieties and expanded trade partners in the medium to long term, to both strengthen regional food production and reduce risk of crop failure and the likelihood of climate-induced drought from trade partners reducing food imports ( [[#Verschuur--2021|Verschuur et al., 2021]] ). A longitudinal study of smallholder coffee farmers in Nicaragua found that crop diversification, alongside crop management and varietal improvement, would help farmers strengthen food security long term in the face of climate hazards such as drought and coffee leaf rust ( [[#Bacon--2021|Bacon et al., 2021]] ). Another medium- to long-term adaptation response is to address systemic gender, land tenure and other social inequities as part of an inclusive approach ( [[#Bezner%20Kerr--2019|Bezner Kerr et al., 2019]] ; [[#Khatri-Chhetri--2020|Khatri-Chhetri et al., 2020]] ; [[#Bacon--2021|Bacon et al., 2021]] ). This long-term strategy could be part of a human-rights-based approach (HRBA, 5.12.8)

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<span id="incorporating-human-rights-based-approaches-into-food-systems"></span>
=== 5.12.8 Incorporating Human Rights-Based Approaches into Food Systems ===

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A human rights-based approach (HRBA), endorsed by the UN, is one strategy for addressing core inequities that are key drivers for food insecurity and malnutrition of particular groups such as low-income consumers, children, women, small-scale producers and different regions of the world ( [[#FAO--2013|FAO, 2013]] ; [[#Claeys--2017|Claeys and Delgado Pugley, 2017]] ; [[#Caron--2018|Caron et al., 2018]] ; [[#Le%20Mouël--2018|Le Mouël et al., 2018]] ; [[#Springmann--2018|Springmann et al., 2018]] ; [[#Tramel--2018|Tramel, 2018]] ; [[#HLPE--2019|HLPE, 2019]] ; [[#Willett--2019|Willett et al., 2019]] ). Climate change impacts, mitigation and adaptation approaches can also worsen inequities ( [[#Eastin--2018|Eastin, 2018]] ; [[#Borras--2020|Borras et al., 2020]] ). HRBA includes core principles of participation, accountability, non-discrimination, transparency, human rights, empowerment and rule of law, which can be integrated into policymaking and implementation as part of transforming the food system ( [[#FAO--2013|FAO, 2013]] ; [[#Caron--2018|Caron et al., 2018]] ; [[#Toussaint--2020|Toussaint and Martínez Blanco, 2020]] ). The right to well-being can serve as the overarching umbrella of HRBA to addressing climate change within food systems and includes a right to health, right to food, cultural rights, the rights of the child and the right to healthy environment ( [[#Swinburn--2019|Swinburn et al., 2019]] ). An HRBA has a specific focus on those groups who are vulnerable due to poverty, discrimination and historical inequities and involves meaningful participation of vulnerable groups in governance, design and implementation of adaptation and mitigation strategies, including gender responsiveness and integration of Indigenous Peoples’ knowledge (UNHRC 2017; [[#Caron--2018|Caron et al., 2018]] ; [[#Mills--2018|Mills, 2018]] ). There can be conflicts and trade-offs, such as between addressing land rights or traditional fishing grounds, the right to food, and addressing climate justice concerns ( [[#Mills--2018|Mills, 2018]] ; [[#Borras--2020|Borras et al., 2020]] ; [[#5.13|Section 5.13]] ). Adaptation strategies that incorporate HRBA include legislation, programmes that address gender inequities in agriculture, agroecology, recognition of rights to land, fishing areas and other natural resources, protection of culturally significant seeds, and community-based adaptation that explicitly involves marginalised groups in governance ( [[#Mills--2018|Mills, 2018]] ; [[#Tramel--2018|Tramel, 2018]] ; [[#Huyer--2019|Huyer et al., 2019]] ; [[#Borras--2020|Borras et al., 2020]] ; [[#5.1|Section 5.1]] 4).

<div id="5.13" class="h1-container"></div>

<span id="climate-change-triggered-competition-trade-offs-and-nexus-interactions-in-land-and-ocean"></span>