Editing IPCC:AR6/WGII/Chapter-2 (section)

==== 2.5.2.6 Risk to Tropical Forests ====

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Key factors affecting the future distribution of tropical humid and dry forests are amounts and seasonalities of precipitation, increased temperatures, prolonged droughts and droughted-moderated fires ( ''robust evidence'' , ''high agreement'' ) ( [[#Bonai--2016|Bonai et al., 2016]] ; [[#Corlett--2016|Corlett, 2016]] ; [[#Lyra--2017|Lyra et al., 2017]] ; [[#Anderson--2018|Anderson et al., 2018]] ; [[#da%20Silva--2018|da]] [[#Silva--2018|Silva et al., 2018]] ; [[#Fontes--2018|Fontes et al., 2018]] ; [[#O’Connell--2018|O’Connell et al., 2018]] ; [[#Aguirre-Gutiérrez--2019|Aguirre-Gutiérrez et al., 2019]] ; [[#Bartlett--2019|Bartlett et al., 2019]] ; [[#Brando--2019|Brando et al., 2019]] ; [[#Stan--2019|Stan and Sanchez-Azofeifa, 2019]] ). The probability of severe drought is projected to quadruple in natural areas in Brazil with &gt;2°C warming ( [[#Barbosa--2016|Barbosa and Lakshmi Kumar, 2016]] ; [[#Marengo--2020|Marengo et al., 2020]] ). Most multi-model studies assuming rapid economic growth/business-as-usual scenarios (A2, A1B and RCP8.5) show an increase in future woody biomass and areas of woody cover towards the end of the 21st century in temperate regions ( [[#Boit--2016|Boit et al., 2016]] ; [[#Nabuurs--2017|Nabuurs et al., 2017]] ) and tropical forests in East Africa ( [[#Ross--2021|Ross et al., 2021]] ) but a decrease in the remaining tropical regions ( [[#Anadón--2014a|Anadón et al., 2014a]] ; [[#Boit--2016|Boit et al., 2016]] ; [[#Lyra--2017|Lyra et al., 2017]] ; [[#Nabuurs--2017|Nabuurs et al., 2017]] ; [[#Maia--2020|Maia et al., 2020]] ). Terrestrial species are predicted to shift to cooler temperatures and higher elevations ( [[#Pecl--2017|Pecl et al., 2017]] ). Tropical species are more susceptible to climate warming than temperate species ( [[#Rehm--2016|Rehm and Feeley, 2016]] ; [[#Sentinella--2020|Sentinella et al., 2020]] ). This susceptibility will be exacerbated by road-building increasing the ease of access into forests ( [[#Brinck--2017|Brinck et al., 2017]] ; [[#Taubert--2018|Taubert et al., 2018]] ; [[#Bovendorp--2019|Bovendorp et al., 2019]] ; [[#Senior--2019|Senior et al., 2019]] ). Furthermore, most tropical cloud forest species are unable to invade grasslands and this will increase the risk of extinctions in tropical cloud forests ( [[#Rehm--2015|Rehm and Feeley, 2015]] ).

SLR as the result of climate change is likely to influence mangroves in all regions, with greater impact on North and Central America, Asia, Australia and East Africa than on West Africa and South America ( ''robust evidence'' , ''high agreement'' ) ( [[#Alongi--2015|Alongi, 2015]] ; [[#Ward--2016|Ward et al., 2016]] ). On a small scale, mangroves are potentially moving landward ( [[#Di%20Nitto--2014|Di Nitto et al., 2014]] ), while on a large scale they will continue to expand poleward ( [[#Alongi--2015|Alongi, 2015]] ).

Most simulations predict a significant geographical shift of transition areas between tropical forests and savanna in the tropical and subtropical Americas and Himalayas ( [[#Anadón--2014a|Anadón et al., 2014a]] ; [[#Rashid--2015|Rashid et al., 2015]] ). Forest dieback, as postulated for the Amazon region, does not occur in the majority of simulations ( [[#Malhi--2009|Malhi et al., 2009]] ; [[#Poulter--2010|Poulter et al., 2010]] ; [[#Rammig--2010|Rammig et al., 2010]] ; [[#Higgins--2012|Higgins and Scheiter, 2012]] ; [[#Huntingford--2013|Huntingford et al., 2013]] ; [[#Davies-Barnard--2015|Davies-Barnard et al., 2015]] ; [[#Sakschewski--2016|Sakschewski et al., 2016]] ; [[#Wu--2016a|Wu et al., 2016a]] ). Model projections of future biodiversity in tropical forests are rare. Arguably, species are most vulnerable to climate change effects at higher altitudes or at the dry end of tropical forest occurrence ( ''medium evidence'' , ''medium agreement'' ) ( [[#Krupnick--2013|Krupnick, 2013]] ; [[#Nobre--2016|Nobre et al., 2016]] ; [[#Trisurat--2018|Trisurat, 2018]] ). Tropical lowlands are expected to lose plant species as temperatures rise above species’ heat tolerance, but could also generate novel communities of heat-tolerant species ( ''robust evidence'' , ''high agreement'' ) ( [[#Colwell--2008|Colwell et al., 2008]] ; [[#Trisurat--2009|Trisurat et al., 2009]] ; [[#Trisurat--2011|Trisurat et al., 2011]] ; [[#Krupnick--2013|Krupnick, 2013]] ; [[#Zomer--2014a|Zomer et al., 2014a]] ; [[#Zomer--2014b|Zomer et al., 2014b]] ; [[#Sullivan--2020|Sullivan et al., 2020]] ; [[#Pomoim--2021|Pomoim et al., 2021]] ).

Statistical models that correlate data on species abundance with information on human pressures, such as LUCs ( [[#Srichaichana--2019|Srichaichana et al., 2019]] ), population density ( [[#Leclère--2020|Leclère et al., 2020]] ) and hunting ( [[#Mockrin--2011|Mockrin et al., 2011]] ), found in tropical and subtropical forests that birds, invertebrates, mammals and reptiles show a decline in their probability of presence with declining forest cover, particularly pronounced in forest specialists or species with narrow ranges ( [[#Newbold--2014|Newbold et al., 2014]] ). Different soil fauna groups showed different responses in abundance and diversity to climate change conditions ( [[#Coyle--2017|Coyle et al., 2017]] ; [[#Facey--2017|Facey et al., 2017]] ) but these responses can impact decomposition rates and biogeochemical cycles ( ''medium evidence'' , ''low agreement'' ).

Invasive plant species are predicted to expand upward by 500–1,500 m in the western Himalayas ( [[#Thapa--2018|Thapa et al., 2018]] ), and by 6–35% yr -1 from the current extent in South America ( ''robust evidence'' , ''high agreement'' ) ( [[#Bhattarai--2014|Bhattarai and Cronin, 2014]] ). Global assessment ( [[#Wang--2017|Wang et al., 2017]] ) also revealed that ecoregions of high-elevation tropical forests and subtropical coniferous forests have a high risk of invasive plant expansion in low-CO 2- emission scenarios, with negative impacts on ecosystem functioning and local livelihoods ( [[#Shrestha--2019|Shrestha et al., 2019]] ).

The impact of unsustainable land use on tropical forests continues in all regions (see Cross-Chapter Paper 7). Projected climate changes will not only impact biodiversity but also the livelihoods of affected people ( ''robust evidence'' , ''high agreement'' ). Increased drought drives crop failures that cause local communities to expand their agricultural area by further clearing native forests ( [[#Desbureaux--2018|Desbureaux and Damania, 2018]] ). Climate change is projected to enlarge the area of suitability for booming tree crops such as oil palm, acacia, Eucalyptus and rubber ( [[#Koninck--2011|Koninck et al., 2011]] ; [[#Cramb--2015|Cramb et al., 2015]] ; [[#Nath--2016|Nath, 2016]] ; [[#Hurni--2017|Hurni et al., 2017]] ; [[#Li--2017|Li et al., 2017]] ; [[#Varkkey--2018|Varkkey et al., 2018]] ). An increase of 8% in the area of rubber plantations in Yunnan Province, China, between 2002–2010 to higher altitudes due to decreased environmental limits, has potentially increased pressure on the remaining biodiversity both within and outside of protected areas ( [[#Zomer--2014a|Zomer et al., 2014a]] ). As a consequence, the suitable area for mammals is projected to be reduced by 47.7% (RCP2.6) and 67.7% (RCP8.5) by 2070, with large variability depending on the different species (Cross-Chapter Paper 7) ( [[#Brodie--2016|Brodie, 2016]] ). To minimize these potential threats, the Yunnan provincial government has identified suitable areas for the establishment of national parks, including the Asian Elephant National Park since 2006. And the government of China developed a national park system in 2013 across the country.

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