生态系统
环境科学
亚热带
归一化差异植被指数
陆地生态系统
气候变化
生态学
降水
植被(病理学)
叶面积指数
蒸散量
大气科学
森林生态学
气候学
全球变暖
碳循环
热带和亚热带湿润阔叶林
结构复杂性
干旱
自然地理学
生长季节
生物多样性
通量网
草原
初级生产
生态系统模型
水循环
作者
Baoni Li,Junguo Liu,Dashan Wang,Xia Liu,Shijing Liang,Shuyu Zhang,Guoqing Gong,Ling Zeng,Zhilin Guo,Jianhuai Ye,Chen Wang,Zhenzhong Zeng
摘要
Abstract As global warming intensifies, humid ecosystems are increasingly exposed to unexpected extreme droughts. However, it remains unclear how ecosystem functions, such as greenness and photosynthesis, and structures, such as leaf area, respond to such events and whether they decouple. We investigated the record‐breaking 2022 growing‐season drought in the humid Yangtze River Basin, where precipitation dropped ∼50% below average. Here we analyzed anomalies of remote sensing normalized difference vegetation index (NDVI) and solar‐induced fluorescence (SIF) to indicate ecosystem functional responses, and leaf area index (LAI) to represent ecosystem structural responses. We applied machine learning models and SHapley Additive exPlanations (SHAP) analysis to attribute these responses to hydroclimatic anomalies and further examine topographic effects. Results indicate a striking divergence of ecosystem functional and structural responses, with NDVI decreasing by 8.4% and SIF declining by 2.2%, while LAI increasing by 1.8% relative to history (2001–2022). Notably, subtropical forest LAI surged by 9.8%, despite a marked decline in NDVI and SIF. Leaf growth was enhanced especially at higher elevations with dense canopies and abundant antecedent soil moisture. Energy conditions, that is, air temperature, vapor pressure deficit, and solar radiation, were found to strongly regulate ecosystem responses to drought. These results imply that humid ecosystems can sustain structural growth despite functional impairment under drought, likely through complex physiological regulation and complementary resource utilization. Our findings underscore the importance of incorporating the function‐structure decoupling under extreme drought in photosynthesis and terrestrial carbon cycle estimations.
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