降水
环境科学
弹性(材料科学)
干旱
植树造林
生态系统
持续性
气候变化
森林恢复
心理弹性
森林生态学
植被(病理学)
环境资源管理
农林复合经营
地理
生态学
气象学
心理学
物理
热力学
生物
病理
医学
心理治疗师
作者
Wanting Wang,Shiliang Liu,Qiang Zhang,Yifei Zhao,Yuhong Dong,Gang Wu,Yetong Li,Jingyang Fan,Jiayi Lin,Zhijia Tian,Lam‐Son Phan Tran
出处
期刊:Earth’s Future
[American Geophysical Union]
日期:2025-08-01
卷期号:13 (8)
摘要
Abstract Forestation plays a crucial role in the restoration of ecosystem functions and services, while the sustainability of restored forests arouses pervasive concerns, and the resilience dynamics and mechanisms of these forests remain poorly understood. Here, we utilize the lag‐1 temporal autocorrelation of satellite‐based vegetation data to evaluate long‐term resilience trends in stable and restored forests across China from 2001 to 2020, then apply machine‐learning algorithms to explore the key drivers behind these trends. Results show that nearly half (45%) of forest ecosystems have experienced resilience declines, whether they are stable forests (44.4%) or restored forests (44.8%). Increased aridity and interannual precipitation variability have a significant impact on the resilience declines in both types of forest ecosystems. Comparatively, non‐climate variables exert a larger impact on resilience declines in restored forests than in stable forests. Resilience declines are more prevalent in restored forests with low plant species richness (<2,000), short forestation times (<10 years), or high soil moisture (>0.2 m 3 /m 3 ). Structural equation models reveal that fewer critical factors directly influence the resilience of restored forests compared to stable forests. These findings underscore the importance of integrating these determinants into ecological restoration efforts to ensure forestation sustainability.
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