Anthropogenically-driven escalating impact of soil-based compound dry-hot extremes on vegetation productivity
Yani Liang, Jun Wang, Zengchao Hao, Huanjiong Wang, Huijuan Cui, Quansheng Ge
Chinese Academy of Sciences Institute of Geographic Sciences and Natural Resources Research University of Chinese Academy of Sciences Beijing Normal University
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Compound dry-hot extremes exert stronger environmental impacts than individual dry or hot extremes. While evidence for increasing meteorological compound dry-hot extremes (defined using surface air temperature and vapor pressure deficit or precipitation) is growing, the impacts and evolving risks of soil-based compound dry-hot extremes remain poorly understood. Using homogenized soil temperature observations and observationally constrained soil moisture dataset for China, we show that the adverse effects of soil-based compound dry-hot extremes on vegetation productivity are more severe than their meteorological counterparts. From 1980 to 2017, the frequency and coverage area of soil-based compound dry-hot extremes in China increased by 3.0 days and 141.9$$\times$$104 km2, respectively, with the most pronounced increases occurring in northern China. These increases are primarily attributed to anthropogenic soil warming. Under a fossil-fueled development scenario, the mean frequency of such extremes is projected to increase by 13.3 days by the end of the twenty-first century relative to the 1981–2010 baseline, potentially reducing China’s terrestrial vegetation gross primary production by approximately 0.025 Pg C a−1. Our findings highlight an anthropogenic escalation of soil-based compound dry-hot extremes and their growing threats to terrestrial carbon sinks and food security. Soil-based compound dry-hot extremes represent a critical yet underappreciated driver of ecosystem stress. This study shows that their frequency and coverage area have increased markedly in China due to anthropogenic soil warming, which may pose growing adverse impacts on vegetation productivity.
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Remote Sensing in Agriculture · Plant Water Relations and Carbon Dynamics
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