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

== 5.11 The Supply Chain from Post-harvest to Food ==

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The food system is more than just the production of food. It includes domestic and international transportation, storage, processing, market infrastructure and institutions that make up value chains, as well as the food environment in which consumers make food purchasing decisions ( [[#HLPE--2017a|HLPE, 2017a]] ). Climate change impacts along the value chain alter availability, access and stability of food security. Nutrition-dense foods tend to be more perishable and are thus more vulnerable to limitations of food storage and transportation infrastructure ( [[#Ickowitz--2019|Ickowitz et al., 2019]] ). Climate-change-related damage to food in storage (e.g., electricity failures and loss of cold storage) and transportation infrastructure (e.g., extreme weather events damaging roads and other infrastructure) could significantly decrease availability and increase the cost of highly perishable, nutritious foods such as fruits, vegetables, fish, meat and dairy.

This discussion of the post-harvest food system (i.e., after production or catch) focuses on three key elements—food safety, storage, and domestic and international transactions—that could see significant climate change impacts, either directly or indirectly. Higher temperatures and humidity can increase post-harvest loss from pests and diseases, increase occurrence of food-borne diseases and contamination, and raise the cost of refrigeration and other forms of preservation. Extreme weather events can cause disruptions to food transport networks and storage infrastructure. Changes in regional weather can cause production centres to shift locations, potentially requiring changes in storage and processing locations. Prices to producers and consumers will change, although directions and magnitudes are determined by local conditions and policies.

Food ''loss'' is the harvest not used by industry or for food. Food ''waste'' is the subset of food loss that is potentially recoverable for food use. As a product moves in the post-harvest chain to end users, post-harvest food loss from climate change can occur from improper handling to damage from microorganisms, insects, rodents or birds. Post-harvest losses in quality can be the result of stresses and damage to a plant or animal before harvest, including from climate change ( [[#Hodges--2011|Hodges et al., 2011]] ; [[#Medina--2015a|Medina et al., 2015a]] ). Food ''waste'' caused by climate change may occur at both retail units and homes because fresh ingredients and freshly prepared foods are vulnerable to quality reduction and spoilage from exposure to higher temperatures and humidity. Food waste also contributes to climate change by utilising resources that emit GHGs ( [[#Galford--2020|Galford et al., 2020]] ).

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'''Box 5.8: Climate Adaptation and Maladaptation in Cocoa and Coffee Production'''
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Coffee and cocoa are important crops in low-latitude regions where agriculture is projected to be heavily impacted by climate change. Both crops are at risk from climate change impacts by 2050 ( [[#Baca--2014|Baca et al., 2014]] ; [[#Ovalle-Rivera--2015|Ovalle-Rivera et al., 2015]] ; [[#Chemura--2016|Chemura et al., 2016]] ; [[#Schroth--2016|Schroth et al., 2016]] ; [[#Bacon--2017|Bacon et al., 2017]] ; [[#Schreyer--2018|Schreyer et al., 2018]] ; [[#de%20Sousa--2019|de Sousa et al., 2019]] ; [[#Lahive--2019|Lahive et al., 2019]] ; [[#Pham--2019|Pham et al., 2019]] ; [[#Cilas--2020|Cilas and Bastide, 2020]] ). Chocolate and coffee are notable among foods in that their carbon footprint ranges from negative to high, as these industries include both low-input agroforestry systems that have many co-benefits, and high-input monoculture systems where crops are grown without shade, in some cases on sites that have been deforested ( [[#Poore--2019|Poore and Nemecek, 2019]] ). While the coffee industry in many countries has already transitioned from agroforestry to full-sun production ( [[#Jha--2014|Jha et al., 2014]] ), the cocoa industry is at a turning point, with many growers deciding whether to move to the potentially more productive ‘full-sun system’, despite a general view that the agroforestry system is more resilient to climate change impacts ( [[#Rajab--2016|Rajab et al., 2016]] ; [[#Schroth--2016|Schroth et al., 2016]] ; [[#Farrell--2018|Farrell et al., 2018]] ; [[#Niether--2020|Niether et al., 2020]] ).

Shade-grown cocoa and coffee agroforestry systems provide an array of ecosystem services, including regulating pests and diseases, maintaining soil fertility, maintaining biodiversity and carbon sequestration ( ''high confidence'' ) ( [[#Jha--2014|Jha et al., 2014]] ; [[#Rajab--2016|Rajab et al., 2016]] ; [[#Cerda--2017|Cerda et al., 2017]] ; [[#Pham--2019|Pham et al., 2019]] ). For example, a comparison of Indonesian cocoa stands found that total carbon stocks above and below ground were five times higher in multi-shade agroforestry stands compared with monoculture stands (57 compared with 11 Mg C ha −1 ), and total NPP was twice as high (18 compared with 9 Mg C ha −1 yr −1 ). The extra carbon sequestration was achieved without any notable difference in cocoa yield ( [[#Rajab--2016|Rajab et al., 2016]] ). At higher levels of shade, there can be negative impacts on the yield of the understory crop, but careful management of shade trees allows for both crops to thrive ( [[#Andreotti--2018|Andreotti et al., 2018]] ; [[#Blaser--2018|Blaser et al., 2018]] ; [[#Niether--2020|Niether et al., 2020]] ).

Cocoa grown under shade in some situations may be more resilient to climate change ( [[#Schwendenmann--2010|Schwendenmann et al., 2010]] ; [[#Schroth--2016|Schroth et al., 2016]] ). [[#Schwendenmann--2010|Schwendenmann et al. (2010)]] implemented drought experimentally in the field and found shade trees increased drought resilience. Shade trees insulate the understory crop from the warming and drying sun ( [[#Schroth--2016|Schroth et al., 2016]] ). On the other hand, full-sun cocoa systems may be more climate resilient in some cases ( [[#Abdulai--2018|Abdulai et al., 2018]] ), as interactions between understory trees and shade trees are complex; in addition to shade effects, evapotranspiration and root interactions must be considered ( [[#Niether--2017|Niether et al., 2017]] ; [[#Wartenberg--2020|Wartenberg et al., 2020]] ). Moving to a full-sun system may also involve additional inputs in irrigation, fertilizer and labour. Neither (2020) reviewed the literature comparing the two cocoa production systems and concluded that the agroforestry system was superior in terms of climate adaptation.

The choice of cropping system will have wide-reaching consequences for climate vulnerability and climate justice. Coffee and cocoa are often a main source of income for small-scale producers who are among the most vulnerable to climate hazards ( [[#Bacon--2014|Bacon et al., 2014]] ; [[#Schroth--2016|Schroth et al., 2016]] ). Most of their produce is exported by large corporations and sold to relatively better-off consumers. In the context of climate justice, underlying structural inequities (socioeconomic, ethnicity, gender, caste), marginality and poverty help to shape the vulnerabilities of small-scale farmers to climate hazards ( [[#Beckford--2016|Beckford and Rhiney, 2016]] ; [[#Schreyer--2018|Schreyer et al., 2018]] ). Climate change may compound their vulnerability, if for example the loss of pollination services leads to a reduction in productivity ( [[#Avelino--2015|Avelino et al., 2015]] ). Adaptation needs to consider the inequities associated with the commodity chain, and the adaptative capacity of producers as they seek to move into the more advanced processing stages of the commodity chain to realise higher returns from their exports ( [[#Ovalle-Rivera--2015|Ovalle-Rivera et al., 2015]] ). Blue Mountain Coffee is a ‘specialty’ coffee associated with a protected area forest ecosystem that attracts a high price premium owing to its distinct flavour and aroma. The livelihoods of coffee farmers in this region are characterised by multiple socioeconomic, environmental and institutional stressors related to climate change, pests, plant diseases and production costs. Some coping strategies employed by these coffee farmers have increased their susceptibility to future climate impacts ( [[#Guido--2019|Guido et al., 2019]] ). Davis (2017) showed that these coffee farmers’ food security challenges could be alleviated by improved marketing of fruit tree products under shade coffee farming systems. Adaptation measures in such systems need to consider co-benefits and negative trade-offs, especially in vulnerable communities, to avoid widening further the inequities, rural livelihood loss, migration and marginalisation, and ensure progress towards the SDGs ( ''high confidence'' ).

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<span id="current-and-future-climate-change-impacts-on-food-safety"></span>
=== 5.11.1 Current and Future Climate Change Impacts on Food Safety ===

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Emerging food safety risks from climate change include those posed by toxigenic fungi, plant- and marine-based bacterial pathogens, HABs and increased use of chemicals (plant protection products, veterinary drugs) potentially leaving residues in food (European Food Safety Authority Panel on Plant Protection Products and their Residues et al., 2017; [[#Deeb--2018|Deeb et al., 2018]] ; [[#Mbow--2019|Mbow et al., 2019]] ; [[#FAO--2020|FAO et al., 2020]] ).

Mycotoxins, produced by toxigenic fungi found on many crops, contaminate food and feed and cause a wide range of adverse impacts to human and animal health. Climate change can affect the growth and geographical expansion of these fungi ( ''high confidence'' ) ( [[#Wild--2015|Wild et al., 2015]] ; [[#Battilani--2016|Battilani, 2016]] ; [[#FAO%20and%20WHO--2016|FAO and WHO, 2016]] ; [[#Watson--2016b|Watson et al., 2016b]] ; [[#Alshannaq--2017|Alshannaq and Yu, 2017]] ; [[#Chen--2018a|Chen et al., 2018a]] ; [[#Avery--2019|Avery et al., 2019]] ; [[#Milicevic--2019|Milicevic et al., 2019]] ; [[#Van%20der%20Fels-Klerx--2019|Van der Fels-Klerx et al., 2019]] ; [[#FAO--2020a|FAO, 2020a]] ; [[#FAO--2020|FAO et al., 2020]] ).

''Aspergillus flavus'' is a fungus that infects a range of crops and can reduce grain quality. Several strains also produce aflatoxin, a particularly problematic mycotoxin ''.'' Increasing CO 2 and drought stress has little effect on growth of ''Aspergillus'' but significantly increases the production of aflatoxin ( [[#Medina--2015b|Medina et al., 2015b]] ).

In Europe, one estimate is that the risk of aflatoxin contamination will increase in maize in a +2°C temperature scenario in Europe, with nearly 40% of Europe exceeding the current legal limits (Battilani and Toscano, 2016). In Malawi, maize aflatoxin levels above European Union (EU) legal thresholds are possible for most of the country by mid-21st century (Warnatzsch and Reay, 2020). The occurrence of toxin-producing fungi will increase and expand from tropical and subtropical areas into new regions and where appropriate capacity for surveillance and risk management is lacking ( ''medium confidence'' ) ( [[#Miller--2016|Miller, 2016]] ). The increase in toxigenic fungi in crops, and consequent contamination of staple foods with mycotoxins, will increase the risks of human and animal exposure ( ''high confidence'' ) (Botana and Sainz, 2015; [[#Rose--2015|Rose and]] [[#Wu--2015|Wu, 2015]] ; [[#Battilani--2016|Battilani, 2016]] ; [[#Avery--2019|Avery et al., 2019]] ; [[#Bosch--2019|Bosch et al., 2019]] ; [[#Milicevic--2019|Milicevic et al., 2019]] ; [[#Moretti--2019|Moretti et al., 2019]] ; [[#Van%20der%20Fels-Klerx--2019|Van der Fels-Klerx et al., 2019]] ; [[#FAO--2020a|FAO, 2020a]] ).

In aquatic systems, toxins produced during HABs also cause food safety problems ( ''high confidence'' ) ( [[#Botana--2016|Botana, 2016]] ; [[#Estevez--2019|Estevez et al., 2019]] ; [[#5.8|Section 5.8]] ). Increased poleward expansion of ''Vibrio'' in coastal mid- to high-latitude areas has been observed ( [[#Baker-Austin--2017|Baker-Austin et al., 2017]] ). ''Vibrio'' -related mortalities from finfish consumption are expected to rise with climate change (water temperature, salinity, oxygen and pH) ( ''medium confidence'' ) ( [[#Mohamad--2019a|Mohamad et al., 2019a]] ; [[#Mohamad--2019b|Mohamad et al., 2019b]] ). For shellfish species, oxygen deficits ( [[#Mohamad--2019b|Mohamad et al., 2019b]] ), sea level rise ( [[#Deeb--2018|Deeb et al., 2018]] ) and temperature ( [[#Green--2019|Green et al., 2019]] ) will be most important for food safety.

Food safety is also anticipated to worsen from increased contaminant bioaccumulation under climate-induced warming ( ''high confidence'' ) (Sections 3.5.8, 3.5.9, 5.8, 5.9, [[#Bindoff--2019|Bindoff et al., 2019]] ;), with changes in pathogen, parasite, fungi and virus abundance and virulence ( [[#Bondad-Reantaso--2018|Bondad-Reantaso et al., 2018]] ). Coastal communities who depend on fisheries for livelihoods and nutrition are especially vulnerable ( [[#Hilmi--2014|Hilmi et al., 2014]] ; [[#Golden--2016|Golden et al., 2016]] ; [[#Bindoff--2019|Bindoff et al., 2019]] ).

Occurrence of bacterial pathogens such as ''Salmonella'' and ''Campylobacter'' will increase with rising temperatures ( ''high confidence'' ). Foodborne pathogen risks will increase through multiple mechanisms, though in general the impacts of climate change on different pathogens are uncertain ( [[#Akil--2014|Akil et al., 2014]] ; [[#Hellberg--2016|Hellberg and Chu, 2016]] ; [[#Lake--2018|Lake and Barker, 2018]] ). Even species within a genus can be affected differently. For example, higher CO 2 levels depress the growth rate of ''F. graminearum'' , an economically important pathogen on barley but have little effect on ''F. verticillioides'' , which is the most reported fungal species infecting maize.

Increases in rainfall intensity will have some effect on the transport of heavy metals by enhancing runoff from soil and increasing the leaching of heavy metals into water systems, with magnitudes dependent on local conditions ( ''high confidence'' ) ( [[#Joris--2014|Joris et al., 2014]] ; [[#Wijngaard--2017|Wijngaard et al., 2017]] ). Methyl mercury (MeHg) is highly neurotoxic and nephrotoxic and bioaccumulates and biomagnifies through the food web via dietary uptake (fish, seafood, mammals) ( [[#Fort--2016|Fort et al., 2016]] ). Ocean warming facilitates methylation of mercury, and the subsequent uptake of methyl mercury in fish and mammals has been found to increase by 3–5% for each 1°C rise in water temperature ( [[#Booth--2005|Booth and Zeller, 2005]] ; [[#FAO--2020a|FAO, 2020a]] ). A changing climate will release mercury from snow and ice, raising the amount of mercury in aquatic ecosystems, although its importance relative to industrial sources is unknown ( [[#Morrissey--2005|Morrissey et al., 2005]] ).

Increased frequency of inland floods has been associated with contamination of food with toxic and fat-soluble persistent organic pollutants (POPs), polychlorinated biphenyls (PCBs) and dioxins ( [[#Lake--2014|Lake et al., 2014]] ; [[#Tirado--2015|Tirado, 2015]] ; [[#Alava--2017|Alava et al., 2017]] ). Exposure to POPs can lead to serious health effects, including certain cancers, birth defects and impairments to the immune, reproductive and neurological systems.

Climate change–contaminant interactions may alter the bioaccumulation and biomagnification of POPs and PCBs as well as MeHg ( [[#Alava--2017|Alava et al., 2017]] ). Of particular concern is the pollution risk influenced by climate change in Arctic ecosystems and the bioamplification of POPs and MeHg in seafoods resulting in long-term contamination of traditional foods in Indigenous communities ( [[#Tirado--2015|Tirado, 2015]] ; [[#Alava--2017|Alava et al., 2017]] ).

The high risk associated with emerging zoonoses (animal diseases that can infect humans) and alterations in the distribution, survival and transmission of vectors and associated pathogens and parasites could lead to an increased use of veterinary drugs and more rapid development of microbial resistance (European Food Safety Authority et al., 2020; [[#FAO--2020a|FAO, 2020a]] ) and higher veterinary drug residues in food of animal origin, potentially posing health issues for humans ( [[#Beyene--2015|Beyene et al., 2015]] ; [[#FAO--2018|FAO et al., 2018]] ; European Food Safety Authority et al., 2020). These outcomes will depend, at least in part, on the extent of changes in current regulatory systems for veterinary drugs. Pre-harvest stress on animals can increase the contamination of meat products with zoonoses. Climate change may also increase rodent populations and rodent-born zoonoses ( [[#Naicker--2011|Naicker, 2011]] ). Extreme weather events that cause flooding, such as hurricanes or extreme rain events, increase the chance of inundating areas that contain waste from animal farms where antibiotics are used for production, increasing the spread of antibiotic-resistant bacteria into the surrounding environment ( [[#FAO--2020a|FAO, 2020a]] ).

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=== 5.11.2 Current and Future Climate Change Impacts on Food Loss in Storage, Distribution and Processing ===

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The potential for climate-change-based food losses exists in all parts of the food system—post-harvest storage, distribution and processing—with the potential for impacts in one part of the system to be passed on to other elements ( [[#Davis--2021|Davis et al., 2021]] ). Storing a product destined for food use makes it available in times other than immediately after harvest, which is especially important for products with a pronounced seasonal availability or that are not available from other regions with different seasons. Storage of fresh products (meat, fish, fruits and vegetables) even with the best cold storage technology results in some quality loss relatively quickly. Higher temperatures increase the cost of maintaining quality. One estimate is that an increase in outdoor temperature from 17°C to 25°C increases cold storage power consumption by about 11% ( [[#James--2010|James and James, 2010]] ). Post-harvest storage of roots and cereals is subject to physical and quality losses from damage by mice, rats and birds and by microorganisms such as the toxigenic fungi discussed above, all of which are expected to increase in warmer and more humid conditions.

The higher temperatures and humidity will generally raise storage costs and lower the quantity and quality of stored product, reducing producer incomes and raising consumer prices ( ''high agreement'' , ''medium evidence'' ) ( [[#Mbow--2019|Mbow et al., 2019]] ). For example, in the US state of Michigan, climate change will shorten the period of reliably cold local storage of potato by 11–17 days and 14–20 days further south by mid-century and by 15–29 days and 31–35 days, respectively, by late century. These changes would increase future demand for ventilation and/or refrigeration immediately after harvest and again in spring and early summer ( [[#Winkler--2018|Winkler et al., 2018]] ).

Insects are a main source of food loss. Climate change can alter insect damage in at least two ways: increases in reproductive rate from temperature increases and changes in pheromone effectiveness ( ''high confidence'' ). Increasing temperature up to about 40°C raises the rates of insect food digestion and reproduction ( [[#Deutsch--2018|Deutsch et al., 2018]] ), but temperatures above that level are fatal for many insects ( [[#Neven--2000|Neven, 2000]] ). Most insects rely on pheromones to facilitate reproduction. Higher temperatures, but also increases in atmospheric CO 2 and O 3 levels, can affect this process. Insect species that rely on long-range chemical signals (such as ladybirds, aphids, bark beetles and fruit flies) will be most impacted, because these signals suffer from longer exposure to processes that reduce pheromone effectiveness ( [[#Medina--2015b|Medina et al., 2015b]] ; [[#Moses--2015|Moses et al., 2015]] ; [[#Boullis--2016|Boullis et al., 2016]] ; [[#Verheecke-Vaessen--2019|Verheecke-Vaessen et al., 2019]] ).

There are several potential pathways for climate change impacts on processing that would negatively affect quality and appearance, but with limited research to date. For example, some studies have indicated that recent increases in temperature have decreased the appearance and milling quality of rice in the USA and East Asia, owing to increased occurrence of chalky grains ( [[#Lyman--2013|Lyman et al., 2013]] ; [[#Morita--2016|Morita et al., 2016]] ; [[#Masutomi--2019|Masutomi et al., 2019]] ; [[#Ishigooka--2021|Ishigooka et al., 2021]] ). Impacts on quality of perennial crops and annual fruits and vegetables are discussed above ( [[#5.4.3|Section 5.4.3]] and Box 5.2).

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=== 5.11.3 Current and Projected Impacts on Transportation and Distribution: Domestic and International Trade ===

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Regional differences in resource availability are a key underlying driver of domestic and international trade. Climate change can change resource availability, in terms of both quantity and quality, altering trade flows, prices and incomes of producers. Climate change can also affect food access, and its stability can be affected through climate-change-driven disruption of infrastructure ( [[#FAO--2018|FAO et al., 2018]] ; [[#Mbow--2019|Mbow et al., 2019]] ). Extreme events are expected to become more common as climate change progresses. Recent examples illustrate the potential for trade disruptions. In March 2019, Cyclone Idai affected 1.7 million people in Mozambique and 920,000 in neighbouring Malawi, according to United Nations (UN) officials. The World Food Program reported that satellite imagery of flooding in central Mozambique showed an ‘inland ocean’ the size of Luxembourg with potentially large impacts on distribution of existing supplies, and uncertain effects on future food production and availability. The extreme rainfall events in the US state of Iowa in spring 2019 destroyed large numbers of well-built grain silos. In addition, major road and bridge damage required rebuilding.

Trade plays a sizeable role in global food supplies. More than 1 billion people relied on international food trade in the early 21st century ( [[#Fader--2013|Fader et al., 2013]] ; Pradhan, 2014). Domestic and international trade flows can be dramatically affected by climate change impacts ''(medium evidence'' , ''high confidence)'' ( [[#Nelson--2014|Nelson et al., 2014]] ; Pradhan, 2014; [[#Wiebe--2015|Wiebe et al., 2015]] ) ''.'' Since the impacts of climate change will not be uniform, profitable locations for exports production will change. In addition, the effects of increasing local weather variability caused by climate change means increasing variability of food availability for domestic use and international trade. Finally, extreme events driven by climate change can disrupt transportation along the food value chain. Countries more at risk of natural hazards that disrupt transportation and distribution, and with less extensive routes, are more vulnerable to climate change impacts. A global multi-hazard risk assessment ( [[#Koks--2019|Koks et al., 2019]] ) suggests surface and river flooding, which are projected to increase in a warmer climate, are the main hazards for road and railway infrastructure, increasingly disrupting international and domestic transportation of agricultural commodities.

Climate change impacts will increase most global prices relative to early 21st century levels, with varying effects on the cost of food imports ( ''high confidence'' ) ( [[#Nelson--2014|Nelson et al., 2014]] ; [[#Wiebe--2015|Wiebe et al., 2015]] ; [[#Fujimori--2018|Fujimori et al., 2018]] ; [[#Lee--2018|Lee et al., 2018]] ). For example, analysis using results from one study (using CMIP5 data for RCP8.5 and SSP2) found that net food importing countries in the early 21st century would see expenditures on food imports decrease by USD 36 billion in mid-century in real terms with climate change over a no climate change scenario. (Table 5.13).

'''Table 5.13 |''' Net exports of agricultural products, by net exporting and net importing countries, 2010 and 2050 (billion constant parity US dollars), based on analysis in [[#Beach--2019|Beach et al. (2019)]] .

{| class="wikitable"
|-
!
! 2010

! 2050

|-
| Net importers in 2010

|
|-
| No climate change

| –301

| −838

|-
| Climate change

| −301

| −802

|}

Global economic models with a focus on agriculture provide a perspective on the range of potential changes in market outcomes because of climate change. In one study comparing several SSPs to a future with no climate change to one with impacts from RCP8.5, 2050 yields with climate changes impacts are 17% smaller on average than those without climate change. Adaptation by farmers reduce that to an 11% decline. The change in 2050 prices of all crops and regions after climate change impacts and farm-level adaptation is a mean 20% increase ( [[#Nelson--2014|Nelson et al., 2014]] ). Substantial differences arise from both the heterogeneous impacts of climate change over crops and geography and the diversity of modelling approaches in the GCM and crop models. A later study with more socioeconomic scenarios and fewer models got roughly similar results ( [[#Wiebe--2015|Wiebe et al., 2015]] ), as did a modelling study focused on food security in South Asian countries ( [[#Cai--2016|Cai et al., 2016]] ).

Most climate scenario modelling to date does not incorporate increasing variability nor the use of storage, a critical tool to manage variability. Two recent studies are exceptions. In one, climate change generally reduces mean yields and increases their variability in the Midwestern USA and causes modest increases in price volatility ( [[#Thompson--2018|Thompson et al., 2018]] ). A second study ( [[#Chen--2019|Chen and Villoria, 2019]] ) focuses on maize net importers across Africa, Asia and Latin America during 2000–2015. A 1% increase in the ratio of imports to total consumption reduces domestic price variability by 0.29%. A 1% increase in stocks at the beginning of the season is correlated with a 0.22% reduction in the coefficient of variation.

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<span id="adaptation-in-the-post-harvest-supply-chain"></span>
=== 5.11.4 Adaptation in the Post-harvest Supply Chain ===

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The SRCCL ( [[#Mbow--2019|Mbow et al., 2019]] ) findings on adaptation support targeting food value chains and intervention types to the needs of specific locations. Furthermore, adaptation choices will need to be dynamic as climate change impacts are expected to worsen over time.

As discussed above and in [[IPCC:Wg2:Chapter:Chapter-6#6.2.5|Section 6.2.5]] , climate change is expected to cause increasingly severe effects on infrastructure needed for food security: roads and harbours for transport, water storage facilities for irrigation and storage facilities able to withstand climate-related damage. Three categories of adaptation could be considered: adoption of technologies already in use elsewhere, including Indigenous and local knowledge, or available or near ready that become profitable as impacts become more severe; development of new technologies; and taking advantage of changing comparative advantage across regions. Specific examples of post-harvest technical adaptation options that are already available but could be more widely adopted include solar driers, cold storage facilities and transport and use of ultrasonic humidification of selected fruits and vegetables, a technology that has been shown in Europe to reduce losses in each post-harvest stage by 20% or more ( [[#Fabbri--2018|Fabbri et al., 2018]] ). Hermetic storage containers using community-based farmer research networks to scale out ( [[#Singano--2020|Singano et al., 2020]] ; Wenndt et al., 2021) also show promise. Another innovation is to introduce ''Aspergillus'' fungi that do not produce aflatoxins in biocontrol formulations, as is being undertaken in the Aflasafe project in Kenya ( [[#Bandyopadhyay--2016|Bandyopadhyay et al., 2016]] ).

International trade changes are a potentially important adaptation mechanism for both the short-term effects of climate variability and long-term changes in comparative advantage with globally substantial benefits but that are distributed unevenly ( [[#Mosnier--2014|Mosnier et al., 2014]] ; [[#Baldos--2015|Baldos and Hertel, 2015]] ; [[#Fuss--2015|Fuss et al., 2015]] ; [[#Costinot--2016|Costinot et al., 2016]] ; [[#Hertel--2016|Hertel and Baldos, 2016]] ; [[#Gouel--2021|Gouel and Laborde, 2021]] ). One estimate is that, with a reduction in tariffs as well as institutional and infrastructural barriers, the negative impacts of climate change globally would be reduced by 64%, with hunger-affected import-dependent regions seeing the greatest benefit. However, in hunger-affected export-oriented regions, partial trade integration might lead to increased exports at the expense of domestic food availability ( [[#Janssens--2020|Janssens et al., 2020]] ). It is possible for policy changes that result in increased trade flows to also increase the potential for maladaptation, for example by encouraging conversion of environmentally sensitive areas to agriculture ( [[#Fuchs--2020|Fuchs et al., 2020]] ; 5.13.3).

As discussed in [[#5.4|Section 5.4]] , climate change is expected to increase variability in yields. As long as the variability is not correlated across regions, trade flows within a year can partially compensate, with in-period exports from countries less affected to those that are. Alterations in trade flow patterns to accommodate these impacts will reduce the negative effects so long as this variability is not correlated across regions ( [[#UK--2015|UK, 2015]] ; [[#Janetos--2017|Janetos et al., 2017]] ).

In terms of food safety impacts, [[#Lake--2018|Lake and Barker (2018)]] highlight a range of approaches to enhance preparedness for more serious foodborne disease effects from climate change: adoption of novel surveillance methods to speed up detection and improve intervention in foodborne outbreaks; genotype-based approaches to surveillance of food pathogens to enhance spatiotemporal resolution in tracing and tracking of illness; improving integration of plant, animal and human surveillance systems under the rubric of One Health, increased commitment to cross-border and global information initiatives; and improved clarity regarding the governance of complex societal issues such as the conflict between food safety and food waste and strong user-centric (social) communications strategies to engage diverse stakeholder groups.

The range of potential adaptation approaches from production to transportation to reduce food loss and waste is captured in Figure 5.17 ( [[#Galford--2020|Galford et al., 2020]] ).

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[[File:e8a55e05dd07b01d08795772fb30145c IPCC_AR6_WGII_Figure_5_017.png]]

'''Figure 5.17 |''' '''Examples of food loss and waste (FLW) interventions at five stages in the food value change (Galford et al.''' ''', 2020).'''

The importance of reducing food loss and waste due to climate change is widely recognised, but literature on cost-effective reductions is sparse, particularly in low-income countries ( [[#Parfitt--2010|Parfitt et al., 2010]] ). A list of farm and post-harvest methods to reduce food loss ( [[#Sheahan--2017|Sheahan and Barrett, 2017]] ) includes potential farm interventions such as varietal choice, education in harvest and post-harvest handling, hermetic storage technologies (see above), chemical sprays and integrated pest management techniques in storage. The evidence on their effectiveness, especially in the face of increased climate change impacts, is limited.

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