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Evaluation of vegetation drought resistance and resilience across central Asian drylands under water limitation and heat extremes

Shiran SongZhejiang-Kazakhstan Joint Laboratory on Spatio-Temporal Intelligence and Sustainable Development, ChinaXi ChenZhejiang-Kazakhstan Joint Laboratory on Spatio-Temporal Intelligence and Sustainable Development, ChinaAkylbek KurishbayevKazakh National Agrarian Research University, Abay Avenue 8, Almaty 050010, KazakhstanChanjuan ZanSchool of Geographical Sciences, China West Normal University, Nanchong, Sichuan 637009, ChinaChuan WangXinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, ChinaPhilippe De MaeyerDepartment of Geography, Ghent University, Ghent 9000, BelgiumShukhrat ShokirovDepartment of Geodesy and Geoinformatics, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers - National Research University, Tashkent, UzbekistanImanmadi DumanScientific and Educational Technology Platform, Kazakh National Agrarian Research University, Almaty 050010, KazakhstanLuqmon SamievDepartment of Geodesy and Geoinformatics, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers - National Research University, Tashkent, UzbekistanTie LiuZhejiang-Kazakhstan Joint Laboratory on Spatio-Temporal Intelligence and Sustainable Development, China

2026en

ABI

Annotatsiya

Study region Arid Central Asia is one of the largest dryland systems in Eurasia and has experienced amplified warming, increasing drought, and intensifying heat extremes. Yet ecosystem drought stability and its hydroclimatic controls remain insufficiently resolved. Study focus We quantified vegetation drought resistance and resilience across arid Central Asia during 2000–2021 using the transpiration-to-evapotranspiration ratio (TET), a functional indicator of vegetation-regulated water use. Drought events were identified using SPEI3, and heatwaves were characterized by frequency, duration, and cumulative heat. Event-based resistance and post-drought resilience were derived from TET responses to isolated drought events, and machine-learning models coupled with SHAP were used to assess the relative associations of hydroclimatic, edaphic, vegetative, and heatwave-related factors with spatial variation in drought stability. New hydrological insights for the region Drought resistance and resilience showed a significant but relatively weak negative association (r = -0.21, p < 0.001). Forests demonstrated the highest resistance (mean Rt = 0.379), whereas sparse vegetation exhibited the highest resilience (mean Rs = 0.059). Ecohydrological attributions revealed that surface soil moisture was the top-ranking predictor associated with resistance. Conversely, resilience was most closely associated with heatwave duration, precipitation, and soil organic carbon. Heatwave associations differed by dimension: heatwave frequency was positively associated with resistance, whereas longer, more intense heatwaves were negatively associated; resilience showed opposite patterns.

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Identifikatorlar

DOI: 10.1016/j.ejrh.2026.103726

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