Editing IPCC:AR6/WGII/Chapter-10 (section)

=== 10.4.5 Agriculture and Food ===

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Asia accounts for 67% of global agricultural production ( [[#Mendelsohn--2014|Mendelsohn, 2014]] ) and employs a large portion of the population in many developing countries and regions ( [[#Briones--2013|Briones and Felipe, 2013]] ; [[#ADB--2017b|ADB, 2017b]] ; [[#ILO--2017a|ILO, 2017a]] ). Since the release of IPCC AR5, more studies have reinforced the earlier findings on the spatio-temporal diversity of climate-change impacts on food production in Asia depending on the geographic location, agroecology and crops grown ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ; [[#Ahmad--2019|Ahmad et al., 2019]] ), recognising that there are winners and losers associated with the changing climate across scales ( [[#Dasgupta--2013a|Dasgupta et al., 2013a]] ; [[#Yong-Jian--2013|Yong-Jian et al., 2013]] ; [[#Bobojonov--2014|Bobojonov and Aw-Hassan, 2014]] ; [[#Hijioka--2014|Hijioka et al., 2014]] ; [[#Li--2014a|Li et al., 2014a]] ; [[#Prabnakorn--2018|Prabnakorn et al., 2018]] ; [[#Trisurat--2018|Trisurat et al., 2018]] ; [[#Matsumoto--2019|Matsumoto, 2019]] ). Despite the observed increase in total food production in terms of crops and food yields from 1990 to 2014 in Asia ( [[#FAO--2015|FAO, 2015]] ), there is ''high confidence'' that overall, at the regional level, the projected total negative impacts will far outweigh the expected benefits, with India emerging as the most vulnerable nation in terms of crop production (Figure 10.6). Recent evidence also indicates that climate-related risks to agriculture and food security in Asia will progressively escalate as global warming reaches 1.5°C and higher above pre-industrial levels ( [[#IPCC--2018b|IPCC, 2018b]] ) with differentiated impacts across the Asian continent.

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[[File:21ea5ce9b67eb804507e3dbedebe590e IPCC_AR6_WGII_Figure_10_006.png]]

'''Figure 10.6 |''' '''Projected impacts of climate change to agriculture and food systems in sub-regions of Asia based on post-IPCC-AR5 studies.''' The figure illustrates the spatio-temporal diversity of projected future impacts on food production highlighting that there are winners and losers associated with the changing climate at different scales. AGRI: agriculture; E: east; N: north; NRCP: no RCP analysis; Pre: precipitation; PY: production yield; RCP: representative concentration pathway; S: south; Temp: temperature; W: west. (Refer to Table SM10.2 for details and supporting references.)

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==== 10.4.5.1 Observed Impacts ====

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There remains a paucity of data for observed climate-change impacts on Asian agriculture and food systems since the release of IPCC AR5. Most of these impacts have been associated with drought, monsoon rain and oceanic oscillations, the frequency and severity of which have been linked with the changing climate ( [[#Heino--2018|Heino et al., 2018]] ; [[#Heino--2020|Heino et al., 2020]] ). In general, major impacts to agricultural production, such as those observed by the farmers in the Philippines and Indonesia, include among others delays in crop harvesting, declining crop yields and quality of produce, increasing incidence of pests and diseases, stunted growth, livestock mortality and low farm income ( [[#Stevenson--2013|Stevenson et al., 2013]] ). In South Asia, the series of monsoon floods from 2005 to 2015 contributed to a high level of loss in agricultural production with peaks in 2008 and 2015 ( [[#FAO--2018a|FAO, 2018a]] ). Similarly, in Pakistan, farmers are experiencing a decline in crop yields and increasing incidence of crop diseases as a result of climate extremes, particularly floods, droughts and heatwaves ( [[#Fahad--2018|Fahad and Wang, 2018]] ; [[#Ahmad--2019|Ahmad et al., 2019]] ).

Limited studies have quantified the actual impacts of climate change on agricultural productivity and the economy. In a study in the Mun River basin, northeast Thailand, yield losses of rice due to past climate trends covering the period 1984–2013 was determined to be in the range of &lt; 50 kg ha –1 per decade or 3% of actual average yields with a high possibility of more serious yield losses in the future ( [[#Prabnakorn--2018|Prabnakorn et al., 2018]] ). Likewise, in China, an economic loss of 595–858 million USD for the corn and soybean sectors was computed from 2000 to 2009 ( [[#Chen--2016b|Chen et al., 2016b]] ). On the other hand, the intensive wheat–maize system in China seems to have benefited from climate change with the northward expansion of the northern limits of maize and multi-cropping systems brought about by the rising temperatures ( [[#Li--2014|Li and Li, 2014]] ).

There is ''high agreement'' in more recent studies that linked the frequency and extent of the El Niño phenomenon with global warming ( [[#Thirumalai--2017|Thirumalai et al., 2017]] ; [[#Wang--2017a|Wang et al., 2017a]] ; [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ) that can trigger substantial loss in crop and fishery production. The 2004 El Niño caused the Philippines an 18% production loss during the dry season and a 32% production loss during the wet season ( [[#Cruz--2017|Cruz et al., 2017]] ). In the 2015 El Niño event, the Indian oil sardine fishery declined by more than 50% of previous years ( [[#Kripa--2018|Kripa et al., 2018]] ) severely impacting coastal livelihoods and economies ( [[#Shyam--2017|Shyam et al., 2017]] ). The 2015–2016 El Niño also inflicted adverse impacts on agricultural productivity and food security, especially affecting the rural poor in middle- and lower-income countries in Southeast and South Asia ( [[#UNDP%20ESCAP%20OCHA%20RIMES%20APCC--2017|UNDP ESCAP OCHA RIMES APCC, 2017]] ).

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==== 10.4.5.2 Projected Impacts ====

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===== 10.4.5.2.1 Fisheries and aquaculture =====

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The fisheries and aquaculture production from Asia in 2019 was estimated at 159.67 mmt contributing to 74.7% of the global production ( [[#FAO--2020|FAO, 2020]] ). This sector provides employment to an estimated 50.46 million people where fishing and aquaculture are important socioeconomic activities and fish products are a substantial source of animal protein ( [[#Bogard--2015|Bogard et al., 2015]] ; [[#Azad--2017|Azad, 2017]] ; [[#FAO--2018c|FAO, 2018c]] ). The economic contribution could be as high as 44% of the coastal communities’ GDP as in the case of Sri Lanka ( [[#Sarathchandra--2018|Sarathchandra et al., 2018]] ). Five Asian countries (i.e., China, Indonesia, India, Vietnam and Japan) are in the top ten of global fish producers, representing a cumulative share of 36% in 2018 ( [[#FAO--2020|FAO, 2020]] ). As a top producer with 15% global share, China also remains a top exporter of fish and fish products with 14% global market share.

There is ''high agreement'' in the literature that Asian fisheries and aquaculture, including the local communities depending on them for livelihoods, are highly vulnerable to the impacts of climate change. Asia has been impacted by SLR ( [[#Panpeng--2017|Panpeng and Ahmad, 2017]] ), a decrease in precipitation in some parts ( [[#Salik--2015|Salik et al., 2015]] ) and an increase in temperature ( [[#Vivekanandan--2016|Vivekanandan et al., 2016]] ), all of which have drastic effects on fisheries and aquaculture ( [[#FAO--2018c|FAO, 2018c]] ). Its coastal fishing communities is exposed to disasters, which are predicted to increase ( [[#Esham--2018|Esham et al., 2018]] ). Fisheries in most of South Asia and Southeast Asia involve small-scale fishers who are more vulnerable to climate-change impacts compared with commercial fishers (Sönke [[#Kreft--2016|Kreft et al., 2016]] ; [[#Blasiak--2017|Blasiak et al., 2017]] ), although there is a general decreasing trend in the number of small units ( [[#Fernandez-Llamazares--2015|Fernandez-Llamazares et al., 2015]] ; [[#ILO--2015|ILO, 2015]] ). A regional study of South Asia forecast large decreases in potential catch of two key commercial fish species (hilsa shad and Bombay duck) in the Bay of Bengal ( [[#Fernandes--2016|Fernandes et al., 2016]] ), which forms a major fishery and food source for coastal communities. About 69% of the commercially important species of the Indian marine fisheries were found to be impacted by climate change and other anthropogenic factors ( [[#Dineshbabu--2020|Dineshbabu et al., 2020]] ). Likewise, water salinisation brought about by SLR is expected to impact the availability of freshwater fish in southwest coastal Bangladesh with adverse implications to poor communities ( [[#Dasgupta--2017a|Dasgupta et al., 2017a]] ). Analysis of fishery has indicated that there will be a continued decrease in catch impacting the seafood sector in the Philippines, Thailand, Malaysia and Indonesia ( [[#Nong--2019|Nong, 2019]] ). Climate change is predicted to decrease total productive fisheries potential in South and Southeast Asia, driven by a temperature increase of approximately 2°C by 2050 ( [[#Barange--2014|Barange et al., 2014]] ).

Like fisheries, Asian aquaculture is highly vulnerable to climate change. Shrimp farmers and fry catchers of Bangladesh are frequently affected by extreme climatic disruptions like cyclones and storm surges that severely damage the entire coastal aquaculture ( [[#Islam--2016a|Islam et al., 2016a]] ; [[#Kais--2018|Kais and Islam, 2018]] ). The majority of shrimp farmers also observed that weather has changed abruptly during the past 5 years and that high temperature is most detrimental because it lowers growth rate, increases susceptibility to diseases, including deformation, and affects production ( [[#Islam--2016a|Islam et al., 2016a]] ). Low production in shrimp farming is also attributed to variation and intensity of rainfall perceived by the majority of farmers as part of climate-change impacts ( [[#Ahmed--2015|Ahmed and Diana, 2015]] ; [[#Islam--2016a|Islam et al., 2016a]] ; [[#Henriksson--2019|Henriksson et al., 2019]] ). In Vietnam, small-scale shrimp farmers are likewise vulnerable to climate change, although those who practise an extensive type of farming with low inputs are more vulnerable compared with those who practise a more intensive type with more capital investment ( [[#Quach--2015|Quach et al., 2015]] ; [[#Quach--2017|Quach et al., 2017]] ). Seaweed farming in Asia is very popular, and the significance of seaweed aquaculture beds in capturing carbon is recognised, but most of the farmed seaweeds are susceptible to climate change ( [[#Chung--2017a|Chung et al., 2017a]] ; [[#Duarte--2017|Duarte et al., 2017]] ).

Marine heatwaves are a new threat to fisheries and aquaculture ( [[#Froehlich--2018|Froehlich et al., 2018]] ; [[#Frölicher--2018|Frölicher and Laufkötter, 2018]] ) including disease spread ( [[#Oliver--2017|Oliver et al., 2017]] ), live feed culture (copepods) ( [[#Doan--2018|Doan et al., 2018]] ) and farming of finfishes like Cobia ( [[#Le--2020|Le et al., 2020]] ). Predicting MHWs is considered a prerequisite for increasing the preparedness of farmers ( [[#Frölicher--2018|Frölicher and Laufkötter, 2018]] ). In Southeast Asian countries more than 30% of aquaculture areas are predicted to become unsuitable for production by 2050–2070 and aquaculture production is predicted to decrease 10–20% by 2050–2070 due to climate change ( [[#Froehlich--2018|Froehlich et al., 2018]] ).

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===== 10.4.5.2.2 Crop production =====

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Since IPCC AR5, more studies have been done on different scales from local to global that focus on the differentiated projected impacts of climate change on the production and economics of various crops with rice, maize and wheat among the major crops receiving more attention. New research findings affirm that climate-change impacts, and will continue to significantly affect, crop production in diverse ways in particular areas all over Asia (Figure 10.6). An increasing number of sub-regional and regional studies using various modelling tools provide significant evidence on the overall projected impacts of climate change on crop production at the sub-regional and regional scales with clear indications of winners and losers among and within nations (see, for instance, [[#Mendelsohn--2014|Mendelsohn, 2014]] ; [[#Cai--2016|Cai et al., 2016]] ; [[#Chen--2016b|Chen et al., 2016b]] ; [[#Schleussner--2016|Schleussner et al., 2016]] ).

Beyond the usual research interest in crop yields which has dominated the current literature, recent studies, such as those in Japan, focus on the impacts of climate change on the ''quality'' of crops (see, for instance, [[#Sugiura--2013|Sugiura et al., 2013]] , for apple; as well as [[#Morita--2016|Morita et al., 2016]] , and [[#Masutomi--2019|Masutomi et al., 2019]] , for rice). A large-scale evaluation by [[#Ishigooka--2017|Ishigooka et al. (2017)]] shows that the increased risk in rice production brought about by temperature increase may be avoided by selecting an optimum transplanting date considering both yield and quality. More studies of this nature have to be conducted for other crops in different locations to better understand and adapt to the negative impacts of the changing climate on the quality of crops ( [[#Ahmed--2016|Ahmed and Stepp, 2016]] ).

New studies have projected the ''likely'' negative impact of pests in Asian agriculture. The golden apple snail ( ''Pomacea canaliculate'' ), which is among the world’s 100 most notorious invasive alien species, threatens the top Asian rice-producing countries, including China, India, Indonesia, Bangladesh, Vietnam, Thailand, Myanmar, the Philippines and Japan, with the predicted increase in climatically suitable habitats in 2080 ( [[#Lei--2017|Lei et al., 2017]] ). Similarly, a study by ( [[#Shabani--2018|Shabani et al., 2018]] ) in Oman projected that the pest of date palm trees, Dubas bug ( ''Ommatissus lybicus'' Bergevin), could reduce the crop yield by 50% under future climate scenarios.

While there is general agreement that CO 2 promotes growth and productivity of plants through enhanced photosynthesis, there remains uncertainty on the extent to which carbon fertilisation will influence agricultural production in Asia as it interacts with increasing temperatures, changing water availability and the different adaptation measures employed ( [[#Ju--2013|Ju et al., 2013]] ; [[#Jat--2016|Jat et al., 2016]] ; [[#ADB--2017b|ADB, 2017b]] ). As global warming compounds beyond 1.5°C, however, the likelihood of adverse impacts on agricultural and food security in many parts of developing Asia increases ( [[#Mendelsohn--2014|Mendelsohn, 2014]] ; [[#IPCC--2018b|IPCC, 2018b]] ). There is a growing trend towards more integrated studies and modelling that combines biophysical and socioeconomic variables (including management practices) in the context of changing climate to reduce uncertainty associated with future impacts of climate change on the agriculture sector (see, for instance, [[#Mason-D’Croz--2016|Mason-D’Croz et al., 2016]] ; [[#Smeets%20Kristkova--2016|Smeets Kristkova et al., 2016]] ; [[#Gaydon--2017|Gaydon et al., 2017]] ).

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===== 10.4.5.2.3 Livestock production =====

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There is hardly any mention about the impacts of climate change on livestock production in the Asia chapter of AR5 due to limited studies on this area. This scarcity of information persists to the current assessment with very scant information on the projected impacts and adaptation aspects of livestock production ( [[#Escarcha--2018a|Escarcha et al., 2018a]] ). The use of scenarios and models to determine alternative futures with participatory engagement processes has been recommended for informed policy and decision making with potential application in the livestock sector ( [[#Mason-D’Croz--2016|Mason-D’Croz et al., 2016]] ). Of the limited assessment available, a study on the smallholders’ risk perceptions of climate change impacts on water-buffalo production systems in Nueva Ecija, the Philippines, identified feed availability and animal health as the production aspects most severely affected by multiple weather extremes ( [[#Escarcha--2018b|Escarcha et al., 2018b]] ). In the Mongolian Altai Mountains, early snowmelt and an extended growing season have resulted in reduced herder mobility and prolonged pasture use, which has in turn initiated grassland degradation ( [[#Lkhagvadorj--2013a|Lkhagvadorj et al., 2013a]] ). Furthermore, reduced herder mobility has increased the pressure on forests resulting in increased logging for fuel and construction wood and reduced regeneration due to browsing damage by increasing goat populations ( [[#Khishigjargal--2013|Khishigjargal et al., 2013]] ; [[#Dulamsuren--2014|Dulamsuren et al., 2014]] ).

In terms of direct impacts, climate-change-induced heat stress and reduced water availability are ''likely'' to generally have negative effects on livestock ( [[#ADB--2017b|ADB, 2017b]] ). In the HKH region, climate change has induced severe impacts on livestock through degradation of rangelands, pastures and forests ( [[#Hussain--2019|Hussain et al., 2019]] ). However, indirect effects may be positive such as in Uzbekistan and South Asia where alfalfa and grassland productivity is expected to improve under warming conditions, which have beneficial effects on livestock production ( [[#Sutton--2013|Sutton et al., 2013]] ; [[#Weindl--2015|Weindl et al., 2015]] ).

At the global level, analysis involving 148 countries in terms of the potential vulnerability of their livestock sector to climate and population change shows that some Asian nations, particularly Mongolia, are ''likely'' to be the most vulnerable while South Asia is the most vulnerable region ( [[#Godber--2014|Godber and Wall, 2014]] ).

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===== 10.4.5.2.4 Farming systems and crop areas =====

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There is new evidence since AR5 that farming systems and crop areas will change in many parts of Asia in response to climate change. In South Asia, a study in Nepal showed that farmers are inclined to change practices in cropland use to reduce climate-change risk ( [[#Chalise--2016|Chalise and Naranpanawa, 2016]] ). In India, climate change is also predicted to lead to boundary changes in areas suitable for growing certain crops (Srinivasa [[#Rao--2016|Rao et al., 2016]] ). A study in Bangladesh revealed a shift in crop choices among farmers, implying changes in the future rice-cropping pattern. Specifically, a temperature increase will compel farmers to choose irrigation-based Boro, Aus and other crops in favour of the rain-fed Aman rice crop ( [[#Moniruzzaman--2015|Moniruzzaman, 2015]] ).

In the coastal area of Odisha in India, adverse impact on the agriculture sector is anticipated considering the increasing temperature trends over the past 30 years for all the seasons ( [[#Mishra--2014|Mishra and Sahu, 2014]] ). In a national study that groups Bangladesh into 16 sub-regions with similar farming areas, simulations of a 62 cm rise in mean sea level project damages to production because of area loss in excess of 31% in sub-region 15 and nearly 40% in sub-region 16 ( [[#Ruane--2013|Ruane et al., 2013]] ). Also in Bangladesh, a study on predicting the design of water requirements for winter paddy rice under climate change conditions shows that agricultural water resource management will help minimise drought risk and implement future agricultural water resource policies (Islam et al., 2018) that may have important implications for crop areas and production.

In East Asia, the observed changes in agricultural flooding in different parts of China could influence farming systems and crop areas ( [[#Zhang--2016b|Zhang et al., 2016b]] ) as extreme events intensify in the context of changing climate. Agricultural management practice in China may also change to optimise soil organic carbon sequestration ( [[#Zhang--2016a|Zhang et al., 2016a]] ). A study on projected irrigation requirements under climate change using a soil-moisture model for 29 upland crops in the Republic of Korea showed that water scarcity is a major limiting factor for sustainable agricultural production ( [[#Hong--2016|Hong et al., 2016]] ). In terms of drought, despite increasing future precipitation in most scenarios, crop-specific agricultural drought is expected to be a significant risk due to rainfall variability ( [[#Lim--2019a|Lim et al., 2019a]] ). On the other hand, a projected rise in water availability in the Korean Peninsula using multiple regional climate models and evapotranspiration methods indicates that it will ''likely'' increase agricultural productivity for both rice and corn, but would decrease significantly in rain-fed conditions ( [[#Lim--2017b|Lim et al., 2017b]] ). Thus, irrigation and soil-water management will be a major factor in determining future farming systems and crop areas in the country.

Global studies on climate-change-induced hotspots of heat stress on agricultural crops show that large suitable cropping areas in Central and Eastern Asia, and the northern part of the Indian subcontinent, are under heat stress risk under the A1B emissions scenario ( [[#Teixeira--2013|Teixeira et al., 2013]] ) and hence may reduce cropping areas in these regions. In Japan, the projected decline in rice yield in some areas suggests that the current rice-producing regions would be divided into suitable and unsuitable areas as temperatures increases ( [[#Ishigooka--2017|Ishigooka et al., 2017]] ), with important implications regarding the possible shift in cropping area. Similarly, it has been shown that there will be change in the geographic distribution of the occurrence of poor skin colour of table-grape berries ( [[#Sugiura--2019|Sugiura et al., 2019]] ) and suitable areas for cultivation of subtropical citrus ( [[#Sugiura--2014|Sugiura et al., 2014]] ) in Japan by the middle of the 21st century.

There is emerging evidence from modelling and field experimentation that designing future farming systems and crop areas that will promote sustainable development in Asia in the context of climate change would have to incorporate not only productivity and price considerations but also how to moderate temperature increase, enhance water conservation and optimise GHG mitigation potential ( [[#Sapkota--2015|Sapkota et al., 2015]] ; [[#Zhang--2016a|Zhang et al., 2016a]] ; [[#Ko--2017|Ko et al., 2017]] ; [[#Lim--2017b|Lim et al., 2017b]] ). The effects of agricultural landscape change on ecosystem services also need to be understood and taken into account in designing farming systems and allocating farm areas ( [[#Lee--2015b|Lee et al., 2015b]] ; [[#Zanzanaini--2017|Zanzanaini et al., 2017]] ).

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==== 10.4.5.3 Food Security ====

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[[#FAO--2001|FAO (2001)]] defines food security as ‘a situation that exists when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life’. There is significant evidence that climate change significantly undermines both agricultural production and food security in Asia ( [[#ADB--2017b|ADB, 2017b]] ). Increasing evidence from sub-regions and individual countries suggests that climate-related hazards, such as increasing temperature, changing rainfall, SLR, drought, flooding and the more frequent and intense occurrences of El Niño–Southern Oscillation events, all impact agricultural production with significant effects on food security. All these hazards interact with non-climatic factors, such as competing demand for scarce water resources, rural–urban migration, food prices and increasing food demand in the long term, and poor governance, among other things, that may worsen food insecurity in the region ( [[#Montesclaros--2021|Montesclaros and Teng, 2021]] ).

In West Asia, particularly in Saudi Arabia and Yemen, increasing water scarcity brought about by temperature rise is anticipated to have a severe impact on agriculture and food production that undermines food security ( [[#Al-Zahrani--2019|Al-Zahrani et al., 2019]] ; [[#Baig--2019|Baig et al., 2019]] ). Saudi Arabia, for instance, was forced to phase out its wheat production starting in 2016 and fully rely on importation to conserve its drying fossil water resources ( [[#Al-Zahrani--2019|Al-Zahrani et al., 2019]] ), a situation which is also linked to a water governance issue.

In Central Asia, a study using a bioeconomic farm model shows very large differences in climate change impacts across farming systems at the subnational level. Large-scale commercial farms in the northern regions of Kazakhstan will have positive income gains, while small-scale farms in arid zones of Tajikistan will experience a negative impact with ''likely'' effects on farm income security ( [[#Bobojonov--2014|Bobojonov and Aw-Hassan, 2014]] ). Impacts on farmers’ income in western Uzbekistan will also significantly vary and could fall by as much as 25% depending on the extent of temperature increase and water-use efficiency ( [[#Bobojonov--2016|Bobojonov et al., 2016]] ).

In a regional study among South Asian countries using an integrated assessment modelling framework, changes in rice and wheat productions brought about by climate change are anticipated to engender wild price volatilities in the markets ( [[#Cai--2016|Cai et al., 2016]] ). Price spikes are projected for 2015–2040 in all South Asian regions with India, Pakistan and Sri Lanka predicted to experience increasingly much higher rice and wheat prices than under the baseline scenario, creating major concerns about food affordability and food security. This will ''likely'' severely affect the overall economic growth of these countries since they are mainly agriculture-driven economies.

A study on mapping global patterns of drought risk projected an increase in drought frequency and intensity in the populated areas of South to Central Asia extensively used for crop and livestock production with serious repercussion to food security and potential civil conflict in the medium to long term ( [[#Carrão--2016|Carrão et al., 2016]] ). In Southeast Asia, a Philippine study on the relationship between seasonal rainfall, agricultural production and civil conflict suggests that the projected change towards wetter rainy seasons and drier dry seasons in many parts of the country will lead to more civil conflict ( [[#Crost--2018|Crost et al., 2018]] ) with negative implications for food and human security. Similarly, floods and higher food prices are also associated with higher risks of social unrest in Asia that may undermine food security ( [[#Hendrix--2015|Hendrix and Haggard, 2015]] ; [[#Ide--2021|Ide et al., 2021]] ).

Food insecurity will be localised across Asia where one part of the country or sub-region will be more food secured while the others, more insecure. This will require in-country or sub-regional trade and development cooperation to minimise the adverse impacts of food insecurity associated with the changing climate ( [[#Li--2014a|Li et al., 2014a]] ; [[#Abid--2016|Abid et al., 2016]] ).

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==== 10.4.5.4 Key Drivers to Vulnerability ====

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There is ''high confidence'' that agriculture will continue to be among the most vulnerable sectors in Asia in light of the changing climate ( [[#Mendelsohn--2014|Mendelsohn, 2014]] ; [[#ADB--2017b|ADB, 2017b]] ). Among the more vulnerable areas include mountain agriculture where fluctuation in crop production ( [[#Poudel--2016|Poudel and Shaw, 2016]] ; [[#Hussain--2019|Hussain et al., 2019]] ), and food insufficiency, is more widespread than in lowland areas ( [[#Poudel--2015|Poudel and Shaw, 2015]] ; [[#Kohler--2009|Kohler and Maselli, 2009]] ). Also vulnerable are flood-prone areas like the Vietnam Mekong River Delta where 39% of the total rice area is exposed to sustained flood risks ( [[#Wassmann--2019a|Wassmann et al., 2019a]] ). Increasing temperatures and changing precipitation levels will persist to be important vulnerability drivers that will shape agricultural productivity particularly in South Asia, Southeast Asia and Central Asia as well as in selected areas of the region. With the increasing likelihood of extreme weather events, such as strong typhoons in the Philippines, the agriculture sector in the typhoon-prone areas of Southeast and East Asia, as well as the Indus Delta, will be more vulnerable to crop destruction (Mallari and Ezra, 2016). Projections on increasing SLR and flooding, such as those in Bangladesh and the Mekong Delta, will submerge and decrease crop production areas and severely affect agriculture and fishery sectors, but will also trigger outmigration from these areas ( [[#ADB--2017b|ADB, 2017b]] ).

Vulnerability of aquaculture-related livelihoods to climate change was assessed at the global scale using the MAGICC/SCENGEN climate modelling tools, and Vietnam and Thailand were identified as most vulnerable in brackish-water aquaculture production ( [[#Handisyde--2017|Handisyde et al., 2017]] ). China, Vietnam and the Philippines are also ranked highly vulnerable in marine production. Moreover, a recent vulnerability assessment of Korean aquaculture based on predicted changes in seawater temperature and salinity according to RCP8.5 indicated that vulnerability was highest for seaweed, such as laver and sea mustard, while fish, shrimp and abalone are relatively less vulnerable as they are less sensitive to high water temperature and their farming environments are controllable to a large extent ( [[#Kim--2019a|Kim et al., 2019a]] ). In Indonesia, farming of whiteleg shrimp ( ''Litopenaeus vannamei'' ) has been found to be vulnerable to increased rainfall and temperature decrease ( [[#Puspa--2018|Puspa et al., 2018]] ).

Climate-change-induced vulnerability, however, is complicated by non-climate drivers. In Thailand, for instance, a 38% reduction (from 21,486 to 13,328 million at the present value (1 USD = 33.54 THB) in the export values of rice and products in the last quarter of 2011 has been attributed not only to the impact of tropical cyclone Nock-Ten on Thai rice export but also the economic slowdown in Thailand during 2011–2012 ( [[#Nara--2014|Nara et al., 2014]] ).

Considering the high vulnerability of Asia to climate change as a whole, there is a need to look at the drivers of vulnerability in an integrated and comprehensive manner. The increasing interest on nexus studies that links climate-change impacts on agriculture with the other sectors like water, energy, land-use change, urbanisation, poverty, economic liberalisation and others (see, for example, [[#Takama--2016|Takama et al., 2016]] ; [[#Aich--2017|Aich et al., 2017]] ; [[#Eslamian--2017|Eslamian et al., 2017]] ; [[#Duan--2019b|Duan et al., 2019b]] ) could contribute to a systemwide vulnerability reduction and an important initial step towards a more climate-resilient future.

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==== 10.4.5.5 Adaptation Options ====

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Since AR5, there has been a surge in the volume of literature that documents and assesses the different adaptation practices already employed in Asian agriculture as well as those that provide future adaptation options. There is ''robust evidence'' that a variety of adaptation practices already employed in agriculture and fisheries are valuable in reducing the negative effects of current climate anomalies but may not be sufficient to fully offset the adverse impacts of future climate scenarios. Recent literature, therefore, focuses on how to build on current adaptation initiatives and processes to improve current and future outcomes ( [[#Iizumi--2019|Iizumi, 2019]] ).

Asian farmers and fishers already employ a variety of adaptation practices to minimise the adverse impacts of climate change. In a recent systematic and comprehensive review of farmers’ adaptation practices in Asia, Shaffril et al. (2018) categorised these practices into different forms such as crop management, irrigation and water management, farm management, financial management, physical infrastructure management and social activities. ‘Climate-smart agriculture’–an integrated approach for developing agricultural strategies that address the intertwined challenges of food security and climate change–is increasingly being promoted in many parts of the region, especially in Southeast and South Asia, with potentially promising outcomes ( [[#Chandra--2017|Chandra et al., 2017]] ; [[#Khatri-Chhetri--2017|Khatri-Chhetri et al., 2017]] ; [[#Shirsath--2017|Shirsath et al., 2017]] ; [[#Westermann--2018|Westermann et al., 2018]] ; [[#Wassmann--2019b|Wassmann et al., 2019b]] ). Site-specific adaptations, such as those in Pakistan, include farmers’ utilisation of several adaptation techniques which include changing crop type and variety, and improving seed quality; fertiliser application and use of pesticides, and planting of shade trees; and water storage and farm diversification ( [[#Fahad--2018|Fahad and Wang, 2018]] ), as well as the implementation of comprehensive climate information services for farming communities ( [[#World%20Meteorological%20Organization--2017|World Meteorological Organization, 2017]] ).

Adaptation measures are also beneficial to small-scale fishers and fish farmers ( [[#Miller--2018|Miller et al., 2018]] ), and through fisheries management plans (FMP) and Early warning systems, the Asian region is reducing climate impact ( [[#FAO--2018c|FAO, 2018c]] ). The most common FMPs adopted in different Asian countries are limits to fishing gear, licensing schemes and seasonal closures ( [[#ILO--2015|ILO, 2015]] ), protection of nursery grounds, providing alternative livelihoods ( [[#Azad--2017|Azad, 2017]] ), limiting fish aggregating devices (FADs) and introduction of monitoring and control tools ( [[#Department%20of%20Fisheries%20(Thailand)--2015|Department of Fisheries (Thailand), 2015]] ). Fishers’ strong sense of belonging to their place of residence and the sense of responsibility to protect the vulnerable fish stock has been advantageously used for developing cooperatives and starting community-based fisheries management (FAO, 2012; [[#ILO--2015|ILO, 2015]] ; [[#Shaffril--2017|Shaffril et al., 2017]] ), and these initiatives have yielded positive results.

In aquaculture, most households in shrimp communities rely on process-oriented multiple coping mechanisms such as consumption smoothing, income smoothing and migration that enhance farmers’ resilience to climate anomalies ( [[#Kais--2018|Kais and Islam, 2018]] ). Diversification and integration of varied resources and interventions in feed and husbandry are seen to help the aqua farmers increase their profits and overcome the impacts of climate change ( [[#Henriksson--2019|Henriksson et al., 2019]] ). Strategies like polyculture, integrated multitrophic aquaculture (IMTA) and recirculating aquaculture systems (RAS) have been suggested to increase aquaculture productivity, environmental sustainability and climate change adaptability ( [[#Ahmed--2019c|Ahmed et al., 2019c]] ; [[#Tran--2020|Tran et al., 2020]] ). In Bangladesh, several adaptation measures, such as integrated community-based adaptation strategies ( [[#Akber--2017|Akber et al., 2017]] ) and integrated coastal zone management ( [[#Ahmed--2015|Ahmed and Diana, 2015]] ), have been recommended to increase climate resilience among shrimp farmers.

More recently, nature-based solutions (NbS) have gained attention globally to enhance climate adaptation. In the context of agriculture, NbS are seen as cost-effective interventions that can increase resilience in food production while advancing climate mitigation and improving the environment ( [[#Iseman--2021|Iseman and]] [[#Miralles-Wilhelm--2021|Miralles-Wilhelm, 2021]] ). Experiences in implementing NbS in agricultural landscapes have been documented both in agriculture and fisheries sectors that promote production while providing co-benefits such as environmental protection and sustainability ( [[#Miralles-Wilhelm--2021|Miralles-Wilhelm, 2021]] ).

Despite the numerous adaptation measures already employed, there is sufficient evidence that farmers’ current adaptation practices are inadequate to offset the worsening climate change impacts. A more comprehensive approach that integrates economic and social strategies with other measures is seen to reduce climate vulnerability. For instance, agriculture insurance is viewed as a promising adaptation approach to reduce risks and increase the financial resilience of farmers and herders in many Asian countries ( [[#Prabhakar--2018|Prabhakar et al., 2018]] ; [[#Matheswaran--2019|Matheswaran et al., 2019]] ; [[#Nguyen--2019|Nguyen et al., 2019]] ; [[#Stringer--2020|Stringer et al., 2020]] ). Similarly, participation of multiple stakeholders from all relevant sectors at different levels in adaptation planning and decision making is seen as an important factor in improving outcomes ( [[#Arunrat--2017|Arunrat et al., 2017]] ; [[#Hochman--2017|Hochman et al., 2017]] ; [[#Chandra--2018|Chandra and McNamara, 2018]] ). Moreover, while adaptation is local and context specific, the following general adaptation-related strategies are distilled from the current literature, based on the Asian experience, to enhance current and future adaptations (see Figure 10.7 for details or examples of each strategy):

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[[File:e2ea5dbb8d6801ed8dc68e775a652df1 IPCC_AR6_WGII_Figure_10_007.png]]

'''Figure 10.7 |''' '''Adaptation-related strategies in Asian agriculture to enhance current and future adaptations.'''

<ul>
<li>Create enabling policies ( [[#Chen--2018d|Chen et al., 2018d]] ) and enhance institutional capacity ( [[#Wang--2014|Wang et al., 2014]] ; [[#Hirota--2019|Hirota and Kobayashi, 2019]] )</li>
<li>Improve adaptation planning and decision making ( [[#Xu--2014|Xu and Grumbine, 2014]] ; [[#Asmiwyati--2015|Asmiwyati et al., 2015]] ; [[#Dissanayake--2017|Dissanayake et al., 2017]] ; [[#Hochman--2017|Hochman et al., 2017]] ; [[#Qiu--2018|Qiu et al., 2018]] ; [[#Shuaib--2018|Shuaib et al., 2018]] ; [[#Aryal--2020b|Aryal et al., 2020b]] ; [[#Ruzol--2021|]] [[#Ruzol--2021|Ruzol and Pulhin, 2021]] ; [[#Ruzol--2021|Ruzol et al., 2021]] )</li>
<li>Promote science-based adaptation measures ( [[#Alauddin--2014|Alauddin and Sarker, 2014]] ; [[#Sapkota--2015|Sapkota et al., 2015]] ; [[#Lim--2017b|Lim et al., 2017b]] )</li>
<li>Adopt an integrated approach to improve adaptation ( [[#Teixeira--2013|Teixeira et al., 2013]] ; [[#Yamane--2014|Yamane, 2014]] ; [[#Abid--2016|Abid et al., 2016]] ; [[#Sakamoto--2017|Sakamoto et al., 2017]] ; [[#Sawamura--2017|Sawamura et al., 2017]] ; [[#Trinh--2018|Trinh et al., 2018]] )</li>
<li>Invest in critical infrastructure ( [[#Cai--2016|Cai et al., 2016]] ; [[#Rezaei--2018|Rezaei and Lashkari, 2018]] )</li>
<li><p>Address farmers’ adaptation barriers ( [[#Alauddin--2014|Alauddin and Sarker, 2014]] ; [[#Pulhin--2016|Pulhin et al., 2016]] ; [[#Fahad--2018|Fahad and Wang, 2018]] ; [[#Gunathilaka--2018|Gunathilaka et al., 2018]] ; [[#Almaden--2019b|Almaden et al., 2019b]] )</p>
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