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

==== 10.4.2.2 Projected Impacts ====

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===== 10.4.2.2.1 Biomes and mountain treeline =====

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Across Asia, under a range of representative concentration pathways (RCPs) and other scenarios, rising temperatures are expected to contribute to a northward shift of biome boundaries and an upwards shift of mountain treeline ( ''medium confidence'' ). Northward shift and area change of bioclimatic zones in Siberia ( [[#Anisimov--2017|Anisimov et al., 2017]] ; [[#Torzhkov--2019|Torzhkov et al., 2019]] ) and northeast Asia ( [[#Choi--2019|Choi et al., 2019]] ) are projected. Projected changes in vegetation in China at the end of the 21st century reveal that the area covered by cold–dry potential vegetation decreases as the area covered by warm–humid potential vegetation increases ( [[#Zhao--2017a|Zhao et al., 2017a]] ). Forest expansion into mountain tundra of the northern Urals is expected ( [[#Sannikov--2018|Sannikov et al., 2018]] ). In Republic of Korea, projected under RCP4.5 and RCP8.5 in the 2070s, suitable area loss of six subalpine tree species, namely, Korean fir, Khingan fir, Sargent juniper, Yeddo spruce, Korean yew and Korean arborvitae, range from 17.7 ± 20.1% to 65.2 ± 34.7%, respectively ( [[#Lee--2021b|Lee et al., 2021b]] ). Korean fir forests would be replaced by temperate forests at lower elevations, while they would continuously persist at the highest elevations on Mt. Halla, Jeju Island and Republic of Korea ( [[#Lim--2018|Lim et al., 2018]] ). Himalayan birch at its upper distribution boundary either is projected to move upwards ( [[#Schickhoff--2015|Schickhoff et al., 2015]] ; [[#Bobrowski--2018|Bobrowski et al., 2018]] ) or considered to downslope as a response to global-change-type droughts ( [[#Liang--2014|Liang et al., 2014]] ). Upwards shift in elevation of bioclimatic zones, decreases in area of the highest elevation zones and large expansion of the lower tropical and sub-tropical zones can be expected by the year 2050 throughout the transboundary Kailash Sacred Landscape of China, India and Nepal, and ''likely'' within the Himalayan region more generally ( [[#Zomer--2014|Zomer et al., 2014]] ).

In North Asia, a shift is projected in the dominant biomes from conifers to deciduous species across Russia after 20 years of altered climate conditions ( [[#Shuman--2015|Shuman et al., 2015]] ). In South Siberia, [[#Brazhnik--2015|Brazhnik and Shugart (2015)]] projected a shift from the boreal forest to the steppe biome. [[#Rumiantsev--2013|Rumiantsev et al. (2013)]] also project a positive northward shift of vegetation boundaries for the greater part of West Siberia in line with warming; however, no shift for the north of West Siberia and negative shift for the southern Urals and northwest Kazakhstan are projected for 2046–2065. The replacement of forest–steppe with steppe at the lower treeline in South Siberia is projected ( [[#Brazhnik--2015|Brazhnik and Shugart, 2015]] ), and retreat of larch forests from the southernmost strongholds of boreal forest in eastern Kazakhstan is expected as part of a global process of forest dieback in semiarid regions ( [[#Dulamsuren--2013|Dulamsuren et al., 2013]] ). In North Asia, tree growth is intertwined with permafrost, snowpack, insect outbreaks, wildfires, seed dispersal and climate (e.g., [[#Klinge--2018|Klinge et al., 2018]] ). It is challenging to isolate the affects of individual factors, particularly since they can interact on one another in unanticipated ways because the underlying mechanisms are not well understood ( [[#Berner--2013|Berner et al., 2013]] ; [[#Brazhnik--2015|Brazhnik and Shugart, 2015]] ). The accuracy of treeline-shift projections is limited because projections are based on vegetation models which do not consider all the factors ( [[#Tishkov--2020|Tishkov et al., 2020]] ). The regional vegetation model structure and parameterisation can affect model performance, and the corresponding projections can differ significantly ( [[#Shuman--2015|Shuman et al., 2015]] ).

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===== 10.4.2.2.2 Species ranges and biodiversity =====

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Considerable changes in plant and animal species distribution under warming stress are expected in Asia until 2100 ( ''high confidence'' ). In East Asia, ''Cunninghamia lanceolate'' , a fast-growing and widely distributed coniferous timber species in China, is projected to increase distribution, to decrease the establishment probability and to reduce total NPP by the 2050s ( [[#Liu--2014c|Liu et al., 2014c]] ). In the monsoon regions of Asia, by the end of the 21st century, NPP is projected to increase by 9–45% ( [[#Ito--2016|Ito et al., 2016]] ). Under climate change on the Korean Peninsula (KP), the potential habitat for ''Abies nephrolepis'' is the northern part of KP, and ''A. koreana'' will disappear from Jeju Island and shrink significantly in the KP ( [[#Yun--2018|Yun et al., 2018]] ), while evergreen forests will expand to the northern part of KP ( [[#Koo--2018|Koo et al., 2018]] ; [[#Lim--2018|Lim et al., 2018]] ). It is expected that under projected warming, fig species in China will expand to higher latitudes and altitudes ( [[#Chen--2018c|Chen et al., 2018c]] ). In Japan, under the A1B scenario, 89% of the area currently covered by the ''Fagus crenata'' -dominant forest type will be replaced by ''Quercus'' spp.-dominant forest types ( [[#Matsui--2018|Matsui et al., 2018]] ). Current trends of climate change will reduce distribution of tall (2–2.5 m high) herb communities in Japan, and will increase suitably for them in the Russian Far East ( [[#Korznikov--2019|Korznikov et al., 2019]] ). A range expansion of ''Lobaria pindarensis'' , an endemic epiphytic lichen in the HKH region, is projected to move to the northeast and to higher altitudes in response to climate change, although the species’ low dispersal abilities and the local availability of trees as a substratum will considerably limit latitudinal and altitudinal shifts ( [[#Devkota--2019|Devkota et al., 2019]] ).

The climatic range of Italian locust ( ''Calliptamus italicus'' L.) under RCP4.5 will expand north- and east-ward to Siberia, the Russian Far East and Central Asia ( [[#Popova--2016|Popova et al., 2016]] ). In Krasnoyarsk Krai, Siberia, it is projected that the needle cast disease caused by fungi from the genus ''Lophodermium'' Chevall. in the Scots pine nurseries would shift northward up to 2080 under A2 and B1 scenarios ( [[#Tchebakova--2016|Tchebakova et al., 2016]] ). All four RCP scenarios showed north-ward expansion of vulnerable regions to pine wilt disease in China, Republic of Korea, the Russian Far East and Japan under climate conditions in 2070 ( [[#Hirata--2017|Hirata et al., 2017]] ), and during 2026–2050 in Japan ( [[#Matsuhashi--2020|Matsuhashi et al., 2020]] ). It is noteworthy that disease expansion depends not only on climatic factors but also on the dispersal capacity of insect vectors, the transportation of infected logs to non-infected regions and the susceptibility of host trees (e.g., [[#Gruffudd--2016|Gruffudd et al., 2016]] ). The suitable habitat area of the snow leopard ''Panthera uncia'' is projected to increase by 20% under the IPCC Scenario A1B by 2080: for the seven northernmost snow leopard range states (Afghanistan, Tajikistan, Uzbekistan, Kyrgyzstan, Kazakhstan, Russia and Mongolia) the suitable habitat area will increase, while habitat loss is expected on the southern slope of the Himalaya and the southeast Tibetan Plateau ( [[#Farrington--2016|Farrington and Li, 2016]] ). Climate change projected under four RCP scenarios will not affect the distribution patterns of Turkestan Rock Agama ''Paralaudakia lehmanni'' (Nikolsky 1896; [[#Sancholi--2018|Sancholi, 2018]] ). In Iran, among 37 studied species of plants and animals, the ranges of 30 species are expected to shrink and ranges of 7 species are expected to increase between 2030 and 2099 under climate-change stress ( [[#Yousefi--2019|Yousefi et al., 2019]] ).

Future climate change would cause biodiversity and habitat loss in many parts of Asia using modelling approaches ( ''high confidence'' ). [[#Warren--2018|Warren et al. (2018)]] projected that extirpation risks to terrestrial taxa (plants, amphibians, reptiles, birds and mammals) from 2°C to 4.5°C global warming in 12 ‘priority places’ in Asia, under the assumption of no adaptation (i.e., dispersal) by the 2080s, is from 12.2–26.4% to 29–56% (Table 10.1; Figure 10.4). Under different scenarios, future climate change could reduce the extent of a suitable habitat for giant pandas ( [[#Fan--2014|Fan et al., 2014]] ), moose ( ''Alces alces'' ) ( [[#Huang--2016|Huang et al., 2016]] ), black muntjac ( ''Muntiacus crinifrons'' ) ( [[#Lei--2016|Lei et al., 2016]] ) and the Sichuan snub-nosed monkey ( ''Rhinopithecus roxellana'' ) ( [[#Zhang--2019d|Zhang et al., 2019d]] ) in China; the Persian leopard ( ''Panthera pardus saxicolor'' ) in Iran ( [[#Ashrafzadeh--2019a|Ashrafzadeh et al., 2019a]] ); the Bengal tiger ( [[#Mukul--2019|Mukul et al., 2019]] ) in India; and four tree-snail species ( ''Amphidromus'' ) in Thailand ( [[#Klorvuttimontara--2017|Klorvuttimontara et al., 2017]] ). However, climate change would have little impact on the habitats of the Asian elephant, but would cause extinction of the Hoolock gibbon in Bangladesh by 2070 ( [[#Alamgir--2015|Alamgir et al., 2015]] ). Climate change would increase the distribution of the Mesopotamian spiny-tailed lizard ( ''Saara loricate'' ) in Iran ( [[#Kafash--2016|Kafash et al., 2016]] ). Future climate change would reduce the suitable habitat of certain protected plants ( [[#Zhang--2014|Zhang et al., 2014]] ) including ''Polygala tenuifolia'' Wild ( [[#Lei--2016|Lei et al., 2016]] ); relict species in East Asia ( [[#Tang--2018|Tang et al., 2018]] ); tree ''Abies'' ( [[#Ran--2018|Ran et al., 2018]] ) in China; two threatened medicinal plants ( ''Fritillaria cirrhosa'' and ''Lilium nepalense'' ) in Nepal ( [[#Rana--2017|Rana et al., 2017]] ); a medicinal and vulnerable plant species ''Daphne mucronata'' ( [[#Abolmaali--2018|Abolmaali et al., 2018]] ) and ''Bromus tomentellus'' in Iran ( [[#Sangoony--2016|Sangoony et al., 2016]] ); a valuable threatened tree species, ''Dysoxylum binectariferum'' , in Bangladesh ( [[#Sohel--2016|Sohel et al., 2016]] ); and plant diversity in Republic of Korea ( [[#Lim--2018|Lim et al., 2018]] ).

'''Table 10.1 |''' Projected extirpation risks: percentage of taxa (plants, amphibians, reptiles, birds and mammals) for 2°C and 4.5°C global warming in ‘priority places’ in Asia, without adaptation by the 2080s. (From [[#Warren--2018|Warren et al., 2018]] ).

{| class="wikitable"
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! Priority places

! At 2°C (%)

! At 4.5°C (%)

|-
| Mekong

| 26.4

| 55.2

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| Baikal

| 22.8

| 49.5

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| Yangtze

| 20

| 42.6

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| Coral Triangle

| 19.2

| 41.8

|-
| Western Ghats

| 18.8

| 41.67

|-
| New Guinea

| 19.8

| 41.2

|-
| Atlai-Syan

| 18.6

| 37

|-
| Sumatra

| 16.8

| 37

|-
| Borneo

| 17.6

| 36.8

|-
| Amur

| 14.2

| 35.6

|-
| Eastern Himalayas

| 12.2

| 29

|-
| Black sea

| 26.2

| 56

|}

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[[File:a091579abc41f0455382430f112766ce IPCC_AR6_WGII_Figure_10_004.png]]

'''Figure 10.4 |''' '''Location of ‘priority places’ in Asia.''' (Modified from [[#Warren--2018|Warren et al., 2018]] ).

The impact of future climate change on invasive species may be species- or region specific ( ''medium confidence'' ). Climate change would promote invasion of a highly invasive aquatic plant ''Eichhornia crassipes'' ( [[#You--2014|You et al., 2014]] ), ''Ambrosia artemisiifolia'' ( [[#Qin--2014|Qin et al., 2014]] ), alligator weed ( ''Alternanthera philoxeroides'' ) ( [[#Wu--2016|Wu et al., 2016]] ), invasive alien plant ''Solidago canadensis'' ( [[#Xu--2014|Xu et al., 2014]] ), three invasive woody oil-plant species ( ''Jatropha curcas, Ricinus communis'' and ''Aleurites moluccana'' ) ( [[#Dai--2018|Dai et al., 2018]] ), and 90 of ~150 poisonous plant species ( [[#Zhang--2017a|Zhang et al., 2017a]] ) in China; six mostly highly invasive species ( ''Ageratum houstonianum'' Mill., ''Chromolaena odorata'' (L.) R.M. King &amp; H. Rob., ''Hyptis suaveolens'' (L.) Poit., ''Lantana camara'' L ''.'' , ''Mikania micrantha'' Kunth and ''Parthenium hysterophorus'' L.) in Nepal (Shrestha et al. 2018); 11 invasive plant species in the western Himalaya ( [[#Thapa--2018|Thapa et al., 2018]] ); alien plants in Georgia ( [[#Slodowicz--2018|Slodowicz et al., 2018]] ); the invasive green anole ( ''Anolis carolinensis'' ) in Japan ( [[#Suzuki-Ohno--2017|Suzuki-Ohno et al., 2017]] ); the Giant African Snail in India ( [[#Sarma--2015|Sarma et al., 2015]] ); and a major insect vector ( ''Monochamus alternatus'' ) of the pine wilt disease ( [[#Kim--2016b|Kim et al., 2016b]] ) and melon thrips ( ''Thrips palmi'' Karny) ( [[#Park--2014|Park et al., 2014]] ) in Republic of Korea. In contrast, a few studies have projected that climate change would inhibit the invasion of one exotic species ( ''Spartina alterniflora'' ) ( [[#Ge--2015|Ge et al., 2015]] ), alien invasive weeds ( [[#Wan--2017|Wan et al., 2017]] ), an invasive plant ( ''Galinsoga parviflora'' ) ( [[#Bi--2019|Bi et al., 2019]] ) and an invasive species ( ''Galinsoga quadriradiata'' ) ( [[#Yang--2018b|Yang et al., 2018b]] ) in China; and two invasive plants ( ''Chromolaena odorata'' and ''Tridax procumben'' s) in India ( [[#Panda--2019|Panda and Behera, 2019]] ).

Five of 15 endemic freshwater fish species in Iran will lose some parts of their current suitable range under climate change by 2070 ( [[#Yousefi--2020|Yousefi et al., 2020]] ). In line with projected large increases in mean water temperature, the strongest increase is projected in exceeded frequency and magnitude of maximum temperature tolerance values for freshwater minnow ( ''Zacco platypus'' ) in East Asia for 2031–2100 ( [[#Van%20Vliet--2013|Van Vliet et al., 2013]] ). Climate change under the A1B scenario is projected to decrease diversity (–0.1%) along with increased local richness (+15%) and range size (+19%) of stream macroinvertebrates in the Changjiang River catchment, southeast China, for the period 2021–2050, while land-use change is predicted to have the strongest negative impact ( [[#Kuemmerlen--2015|Kuemmerlen et al., 2015]] ). The Asian clam ''Corbicula fluminea'' Müller, an invasive species native to southeast China, the Republic of Korea and southeast Russia, is projected to invade Southeast Asia under all four RCP scenarios for the 2041–2060 and 2061–2080 periods ( [[#Gama--2017|Gama et al., 2017]] ). Projected SLR, related aquatic salinisation and alteration in fish species composition may have a negative impact on poor households in southwest coastal Bangladesh ( [[#Dasgupta--2017a|Dasgupta et al., 2017a]] ).

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===== 10.4.2.2.3 Wildfires =====

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Under regional projections for North Asia, warmer climate will increase forest fire severity by the late 21st century ( ''medium confidence'' ). For the southern taiga in Tuva Republic, Central Siberia, in a warmer climate, both the annual area burned and fire intensity will increase by 2100. For the central taiga in the Irkutsk region, the annual area burned as well as crown fire-to-ground fire ratiowill increase by the late 21st century compared with the historical (1960–1990) estimate. This moves forest composition towards greater contribution of hardwoods (e.g., ''Betula'' spp., ''Populus'' spp.) ( [[#Brazhnik--2017|Brazhnik et al., 2017]] ). This shifting was also proved by observations in northern Mongolia, where boreal forest fires ''likely'' promote the relative dominance of ''B. platyphylla'' and threaten the existence of the evergreen conifers, ''Picea obovata'' and ''Pinus sibirica'' ( [[#Otoda--2013|Otoda et al., 2013]] ). For Tuva Republic, warming ambient temperatures increase the potential evapotranspiration demands on vegetation, but if no concurrent increase in precipitation occurs, vegetation becomes stressed and either dies from temperature-based drought stress or more easily succumbs to insects, fire, pathogens or wind throw ( [[#Brazhnik--2017|Brazhnik et al., 2017]] ). Although [[#Torzhkov--2019|Torzhkov et al. (2019)]] also projected fire risk (FR) increase in Tuva Republic, they expect FR decrease in the Irkutsk region and Yakutia under RCP8.5, and FR decrease in major parts of Central and East Siberia under RCP4.5 for 2090–2099. This discrepancy is due to differences in models, climate projections, fire severity metrics and other assumptions. According to global projections, FR will increase in Central Asia, Russia, China and India under a range of scenarios ( [[#Sun--2019|Sun et al., 2019]] ).

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