Declining coupling between vegetation and drought over the past three decades

蒸散量 植被(病理学) 增强植被指数 气候变化 降水 环境科学 归一化差异植被指数 自然地理学 气候学 地理 生态学 地质学 植被指数 生物 气象学 病理 医学
作者
Delong Li,Li An,Shuai Zhong,Lei Shen,Shuyao Wu
出处
期刊:Global Change Biology [Wiley]
卷期号:30 (1) 被引量:19
标识
DOI:10.1111/gcb.17141
摘要

Abstract Droughts have been implicated as the main driver behind recent vegetation die‐off and are projected to drive greater mortality under future climate change. Understanding the coupling relationship between vegetation and drought has been of great global interest. Currently, the coupling relationship between vegetation and drought is mainly evaluated by correlation coefficients or regression slopes. However, the optimal drought timescale of vegetation response to drought, as a key indicator reflecting vegetation sensitivity to drought, has largely been ignored. Here, we apply the optimal drought timescale identification method to examine the change in coupling between vegetation and drought over the past three decades (1982–2015) with long‐term satellite‐derived Normalized Difference Vegetation Index and Standardized Precipitation‐Evapotranspiration Index data. We find substantial increasing response of vegetation to drought timescales globally, and the correlation coefficient between vegetation and drought under optimal drought timescale overall declines between 1982 and 2015. This decrease in vegetation–drought coupling is mainly observed in regions with water deficit, although its initial correlation is relatively high. However, vegetation in water‐surplus regions, with low coupling in earlier stages, is prone to show an increasing trend. The observed changes may be driven by the increasing trend of atmospheric CO 2 . Our findings highlight more pressing drought risk in water‐surplus regions than in water‐deficit regions, which advances our understanding of the long‐term vegetation–drought relationship and provides essential insights for mapping future vegetation sensitivity to drought under changing climate conditions.
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