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

==== 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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