Spatial pattern and attribution of ecosystem drought recovery in China

生态系统 中国 归属 环境科学 环境资源管理 地理 自然地理学 生态学 心理学 生物 社会心理学 考古
作者
Tingtao Wu,Lei Xu,Nengcheng Chen
出处
期刊:Journal of Hydrology [Elsevier BV]
卷期号:638: 131578-131578 被引量:1
标识
DOI:10.1016/j.jhydrol.2024.131578
摘要

Under the backdrop of global climate change, frequent drought events pose a severe and persistent threat to the normal functioning of ecosystems. Drought recovery time, the time it takes for an ecosystem to return to its pre-drought state, is a crucial metric for drought impact and ecosystem stability. However, most previous studies have focused on the drought recovery time of the region as a whole or a specific type of ecosystem. The differences in drought recovery time among different ecosystems and their driving factors are largely unknown. Therefore, this study utilizes multi-source fused Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) data and Gross primary productivity (GPP) data to construct drought and ecosystem indicators. Subsequently, the drought recovery time under different climates and ecosystem types in China from 2002 to 2017 is analyzed. Finally, the factors influencing the differences in drought recovery time among ecosystems are discussed in detail. The results indicate that there is significant spatial heterogeneity in drought recovery time among ecosystems in China, with the forest ecosystems in the Northeast and Southwest regions having the longest recovery time. The recovery time of forest ecosystems (4.32 months) is longer than that of cropland (4.07 months) and grassland (3.79 months) ecosystems, but there are also significant differences in the recovery time for the same ecosystems under different climate types. The differences in drought recovery time among different ecosystem types are primarily influenced by temperature and precipitation during drought recovery, and the response of ecosystems to drought. These results provide scientific support for adopting differentiated management strategies for different ecosystem types to cope with future climate change.
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