Description
Monitoring changes in drought-induced vegetation loss risk and ecosystem resilience is crucial for understanding the stability of dryland ecosystems under a warming climate. Using long-term satellite vegetation indices and hydroclimatic drivers, we mapped historical drought-induced vegetation loss risk and vegetation resilience across global drylands and projected their future changes under CMIP6 SSP scenarios. We further applied machine-learning models to quantify the relative importance of key drivers and to support attribution of resilience changes. These analyses advance mechanistic understanding of drought-driven risk and resilience dynamics, supporting dryland ecological restoration and adaptive management.
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Publication Details
DOI
Publisher
figshare
Subfield
Global and Planetary Change
Field
Environmental Science
Domain
Physical Sciences
Confidence Score
65%
Source
Scholar Data Model