环境科学
植被(病理学)
干旱
含水量
降水
生态系统
气候变化
叶面积指数
水分
干旱指数
水文学(农业)
大气科学
土壤科学
生态学
地理
地质学
气象学
病理
生物
岩土工程
医学
作者
Wantong Li,Mirco Migliavacca,Matthias Forkel,Jasper M. C. Denissen,Markus Reichstein,Hui Yang,Grégory Duveiller,Ulrich Weber,René Orth
标识
DOI:10.1038/s41467-022-31667-9
摘要
Abstract Global vegetation and associated ecosystem services critically depend on soil moisture availability which has decreased in many regions during the last three decades. While spatial patterns of vegetation sensitivity to global soil water have been recently investigated, long-term changes in vegetation sensitivity to soil water availability are still unclear. Here we assess global vegetation sensitivity to soil moisture during 1982-2017 by applying explainable machine learning with observation-based leaf area index (LAI) and hydro-climate anomaly data. We show that LAI sensitivity to soil moisture significantly increases in many semi-arid and arid regions. LAI sensitivity trends are associated with multiple hydro-climate and ecological variables, and strongest increasing trends occur in the most water-sensitive regions which additionally experience declining precipitation. State-of-the-art land surface models do not reproduce this increasing sensitivity as they misrepresent water-sensitive regions and sensitivity strength. Our sensitivity results imply an increasing ecosystem vulnerability to water availability which can lead to exacerbated reductions in vegetation carbon uptake under future intensified drought, consequently amplifying climate change.
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