Drylands are home to more than 38% of the total global population and are one of the most sensitive areas to climate change and human activities1,2. Projecting the areal change in drylands is essential for taking early action to prevent the aggravation of global desertification3,4. However, dryland expansion has been underestimated in the Fifth Coupled Model Intercomparison Project (CMIP5) simulations5 considering the past 58 years (1948–2005). Here, using historical data to bias-correct CMIP5 projections, we show an increase in dryland expansion rate resulting in the drylands covering half of the global land surface by the end of this century. Dryland area, projected under representative concentration pathways (RCPs) RCP8.5 and RCP4.5, will increase by 23% and 11%, respectively, relative to 1961–1990 baseline, equalling 56% and 50%, respectively, of total land surface. Such an expansion of drylands would lead to reduced carbon sequestration and enhanced regional warming6,7, resulting in warming trends over the present drylands that are double those over humid regions. The increasing aridity, enhanced warming and rapidly growing human population will exacerbate the risk of land degradation and desertification in the near future in the drylands of developing countries, where 78% of dryland expansion and 50% of the population growth will occur under RCP8.5.
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This work was jointly supported by the National Basic Research Program of China (2012CB955301), Special Public Welfare Research Fund of China (GYHY201206009), the National Science Foundation of China (41521004, 41305009 and 41405010) and the China University Research Talents Recruitment Program (111 project, No. B13045). The authors acknowledge the World Climate Research Programme’s (WCRP) Working Group on Coupled Modelling (WGCM), the Global Organization for Earth System Science Portals (GO-ESSP) for producing the CMIP5 model simulations and making them available for analysis and NASA’s Earth-Sun System Division (ESSD) for providing the MODIS Adaptive Processing System (MODAPS) data sets. All of the authors acknowledge S. Feng for providing the precipitation and PET data sets from the observations and the 20 members of CMIP5 and David Covert for his valuable comments and helpful suggestions for this research.
About this article
npj Science of Food (2018)