Editing IPCC:AR6/WGII/Cross-Chapter-Paper-3 (section)

==== CCP3.3.1.4 Dryland Extent ====

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Global dryland area (based on the AI) is projected to expand by ~10% by 2100 compared to 1961–1990 under a high emission scenario ( [[#Feng--2013|Feng and Fu, 2013]] ). However, there are significant regional differences in the drivers of dryland expansion and subsequent estimates of change in dryland extent. Subtropical drylands are projected to expand as the climate in these regions shifts from temperate to subtropical and aridity increases in currently sub-humid subtropical regions, resulting in the loss of temperature-controlled seasonal cycles (Schlaepfer et al., 2017). Observed and projected warming and drying trends are most severe in transitional climate regions between dry and wet climates, with some exceptions ( [[#Nkrumah--2019|Nkrumah et al., 2019]] ), which are often highly populated agricultural regions with fragile ecosystems ( [[#Cheng--2016|Cheng and Huang, 2016]] ). In contrast, P – E predicts decreasing drought stress across temperate Asia and central Africa ( [[#Swann--2016|Swann et al., 2016]] ). Expansion of arid regions is anticipated in southwest North America, the northern fringe of Africa, southern Africa and Australia. The main areas of semiarid expansion are expected to occur in the north side of the Mediterranean, southern Africa, and North and South America. In contrast, India, eastern equatorial Africa and other areas of the southern Saharan regions are projected to have shrinking drylands ( [[#Biasutti--2006|Biasutti and Giannini, 2006]] ; [[#Biasutti--2013|Biasutti, 2013]] ; [[#Rowell--2016|Rowell et al., 2016]] ). Future projections may underestimate dryland expansion, since the Coupled Model Intercomparison Project 5 (CMIP5) models underestimate historical warming ( [[#Huang--2016|Huang et al., 2016]] ) and overestimate precipitation over drylands, particularly in the semiarid and dry sub-humid regions ( [[#Ji--2015|Ji et al., 2015]] ). However, estimates vary depending on the metric used ( [[#Swann--2016|Swann et al., 2016]] ; [[#Berg--2017b|Berg et al., 2017b]] ). Studies based on off-line aridity and drought metrics (calculated from model output of precipitation, evapotranspiration or temperature) project strong surface drying trends ( [[#Cook--2014|Cook et al., 2014]] ; [[#Scheff--2015|Scheff and Frierson, 2015]] ; [[#Zhao--2015|Zhao and Dai, 2015]] ), while projections based on total soil water availability from CMIP5 models show weaker and less extensive drying ( [[#Berg--2017a|Berg et al., 2017a]] ). In contrast, projections in southern Africa may overestimate future drying, with systematic rainfall biases being found in the present-day climatology in models that simulate extreme future drying ( [[#Munday--2019|Munday and Washington, 2019]] ). Improvements in projections of future changes in aridity require better understanding of seasonality, land hydrology and the feedbacks between projected soil moisture decrease on land surface temperature, relative humidity and precipitation ( [[#Huang--2016|Huang et al., 2016]] ).

Higher dust emissions are consistent with climate change projections indicating an expansion in the global area of drylands ( [[#Feng--2013|Feng and Fu, 2013]] ; [[#Huang--2016|Huang et al., 2016]] ) and increased drought risk ( [[#Cook--2014|Cook et al., 2014]] ; [[#Xu--2019|Xu et al., 2019]] ), but future trends in dust event frequency and intensity as a result of climate change are uncertain and will vary geographically (Jia, 2019). Combined effects of climate change and anthropogenic activities are projected to increase sand encroachment and extreme dust storms (Omar [[#Asem--2010|Asem and Roy, 2010]] ; [[#Sharratt--2015|Sharratt et al., 2015]] ; [[#Pu--2017|Pu and Ginoux, 2017]] ) as a result of increased aridity, accelerating soil erosion ( [[IPCC:Wg2:Chapter:Chapter-4#4.4.8|Section 4.4.8]] ; [[#Sharratt--2015|Sharratt et al., 2015]] ) and loss of biomass ( [[#Sharratt--2015|Sharratt et al., 2015]] ; [[#Middleton--2017|Middleton and Kang, 2017]] ). Shifts in dust storm timings are also projected in some regions (Hand et al., 2016). Dustiness is projected to increase in the southern US Great Plains in the late 21st century under the RCP8.5 climate change scenario but decrease over the northern Great Plains ( [[#Pu--2017|Pu and Ginoux, 2017]] ). A declining trend in dust emission and transport from the Sahara under RCP8.5 was detected by Evan et al. (2016), but regional climate model experiments conducted by [[#Ji--2018|Ji et al. (2018)]] under the same scenario indicated that overall dust loadings would increase by the end of the 21st century over West Africa. New dust sources may emerge with changing climate conditions, as [[#Bhattachan--2012|Bhattachan et al. (2012)]] indicate for the Kalahari Desert in southern Africa, due to vegetation loss and dune remobilisation. There is overall ''low confidence'' on future atmospheric dust loads at the global and regional scale. Models of future dust emissions are limited by the low accuracy of models of present anthropogenic dust emissions, which range from 10% to 60% of the total atmospheric dust load ( [[#Webb--2018|Webb and Pierre, 2018]] ). A global compilation of data from sedimentary archives (ice cores), remote sensing, airborne sediment sampling and meteorological station data estimated that anthropogenic dust emissions have at least doubled over the past 250 years ( [[#Hooper--2018|Hooper and Marx, 2018]] ). While future emissions of natural dust sources are projected to decrease (Mahowald et al., 2006) or remain stable ( [[#Ashkenazy--2012|Ashkenazy et al., 2012]] ), when sources of human emissions are included, projections of future atmospheric dust loads suggest that emissions may increase ( [[#Stanelle--2014|Stanelle et al., 2014]] ).

The relative contribution of albedo and evapotranspiration to regional trends in surface temperature ( [[#Charney--1975|Charney, 1975]] ) remains unresolved, and may be determined by different mechanisms in different systems, depending on site-specific conditions such as snow coverage, vegetation and soil moisture ( [[#Yu--2017|Yu et al., 2017]] ). For example, the vegetation–albedo feedback mechanism may dominate in the Arctic ( [[#Blok--2011|Blok et al., 2011]] ; [[#te%20Beest--2016|te Beest et al., 2016]] ), while the vegetation–evaporation feedback may drive change in other regions. Actions that increase forest cover across Africa could thus, theoretically, moderate projected future temperature increases ( [[#Wu--2016|Wu et al., 2016]] ; [[#Diba--2018|Diba et al., 2018]] ), but with potentially negative effects on biodiversity (Chapter 2). Soil drying exacerbates atmospheric aridity, which causes more soil drying in a self-reinforcing land–atmosphere feedback that could intensify under RCP8.5 ( [[#Zhou--2019|Zhou et al., 2019]] ).

Changes to the composition, structure and functioning of natural communities in deserts and dryland ecosystems are key risks resulting from water stress, drought intensity and continued habitat degradation, greater frequency of wildfire, biodiversity loss and the spread of invasive species ( [[#Hurlbert--2019|Hurlbert et al., 2019]] ). Not all these stresses occur at the same time in a particular environment, with some areas more exposed to, for example, wildfire than others, especially in areas with high amounts of dry herbaceous biomass. Grassland composition may shift as C3 plants are replaced by C4 species, which have higher optimal temperatures and higher water use efficiency (although seasonality of precipitation also plays a role) (Knapp et al., 2020). Many desert species have morphological, physiological and/or behavioural adaptations to cope with climatic extremes, including rapid regeneration following droughts ( [[#Boudet--1977|Boudet, 1977]] ; [[#Hiernaux--2006|Hiernaux and Le Houérou, 2006]] ), leaf dropping during the dry season to reduce water loss ( [[#Santos--2014|Santos et al., 2014]] ), alongside long histories of adaptation to climate change ( [[#Brooks--2005|Brooks et al., 2005]] ; [[#Ballouche--2007|Ballouche and Rasse, 2007]] ), while many animals live near their physiological limits ( [[#Vale--2015|Vale and Brito, 2015]] ). Substantial ecological effects may occur when extreme events such as heatwaves or droughts are superimposed on the warming trend, pushing species beyond their physiological and mortality thresholds ( [[#Hoover--2015|Hoover et al., 2015]] ; [[#Harris--2018|Harris et al., 2018]] ).

Climate change increases risks of continued range retractions of Karoo succulents in South Africa (Young et al., 2016), dry argan woodlands in Morocco ( [[#Alba-Sánchez--2015|Alba-Sánchez et al., 2015]] ), epiphytic cacti in Brazil ( [[#Cavalcante--2019|Cavalcante and Duarte, 2019]] ; [[#Cavalcante--2020|Cavalcante et al., 2020]] ) and other plant species exposed to higher aridity. Projected increases in heat and aridity could increase mortality of trees and shrubs in Sonoran Desert ecosystems in the USA ( [[#Munson--2012|Munson et al., 2012]] ; 2016b), reduce sagebrush in arid ecosystems of the western USA ( [[#Renwick--2018|Renwick et al., 2018]] ), and contribute to the replacement of perennial grasses with xeric shrubs in the southwestern USA ( [[#Bestelmeyer--2018|Bestelmeyer et al., 2018]] ). CO 2 fertilization and warmer conditions, combined with changes in timing and availability of moisture, could increase invasive grasses and wildfire in desert ecosystems of Australia and southwestern USA, where wildfire has historically been absent or infrequent ( [[#Abatzoglou--2011|Abatzoglou and Kolden, 2011]] ; Horn and St. Clair, 2017; [[#Klinger--2017|Klinger and Brooks, 2017]] ; [[#Syphard--2017|Syphard et al., 2017]] ). Trends of woody encroachment may continue in some North American and African drylands or at least not reverse ( [[#Higgins--2012|Higgins and Scheiter, 2012]] ; [[#Caracciolo--2016|Caracciolo et al., 2016]] ). Impacts of woody encroachment on drylands may show a slight increase in carbon, but a decline in water and huge negative impacts on biodiversity, with a tendency for open ecosystem species to be most affected ( [[#Archer--2017|Archer et al., 2017]] ). Expansion of grasses into these arid shrublands has the potential to transform them rapidly, especially through the acceleration of the fire cycle ( [[#Bradley--2016|Bradley et al., 2016]] ). While the impact of increased aridity may be offset by changing water use efficiency by plants under high CO 2 concentrations, limiting the expansion of dryland ecosystems ( [[#Swann--2016|Swann et al., 2016]] ; [[#Mirzabaev--2019|Mirzabaev et al., 2019]] ), increased plant growth in response to elevated CO 2 , which results in increased water consumption, may counteract this. Increased water use efficiency is therefore not expected to counterbalance increased evaporative demand (Chapter 8). There is ''medium confidence'' that succulent species will be particularly vulnerable to increased heat and aridity due to reduced physiological performance, loss of seed banks, lower germination rates and increased mortality (Table CCP3.1; [[#Musil--2005|Musil et al., 2005]] ; [[#Aragón-Gastélum--2014|Aragón-Gastélum et al., 2014]] ; 2017; [[#Shryock--2014|Shryock et al., 2014]] ; [[#Martorell--2015|Martorell et al., 2015]] ; [[#Carrillo-Angeles--2016|Carrillo-Angeles et al., 2016]] ; [[#Koźmińska--2019|Koźmińska et al., 2019]] ).

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