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• Integrating satellite data with machine learning reveals resilience dynamics. • Resilience increased from arid to humid regions, peaking where aridity index >0.65. • Vegetation greening coexists with ecosystem resilience loss since 2005. • Warming and water variability drove resilience loss in humid and arid regions, respectively. • Theoretical validation of ecological indicators for ecosystem resilience assessment. Greening is asynchronous with ecosystem resilience in the context of vegetation restoration, thus highlighting the uncertainty in predicting the future sustainability of ecosystems. However, global evidence, to validate this inconsistency, remains limited. Here, we integrated Global Inventory Monitoring and Modeling Studies (GIMMS), Moderate Resolution Imaging Spectroradiometer (MODIS), and global Orbiting Carbon Observatory-2 Solar-induced chlorophyll fluorescence (GOSIF) multisource vegetation indices with a random forest model to demonstrate how resilience in Eurasia quantified using critical slowing down indicators has changed during 1984–2020. Resilience estimates derived from the Normalized Difference Vegetation Index (NDVI), kernel NDVI (kNDVI), Leaf Area Index (LAI), Gross Primary Production (GPP), and GOSIF exhibited similar spatial patterns and trends. Specifically, resilience was lower in water-limited regions and increased with higher aridity index values; it peaked in humid regions (AI > 0.65), with average values (quantified by λ A C 1 ) ranging from −2.20 to −2.00. While vegetation cover showed a general increasing trend, resilience simultaneously declined, particularly in semi-humid areas. Significant shifts in resilience trends occurred around 2005. Warming and variability in water conditions were identified as the main reasons for the decline in resilience in humid and arid regions, respectively. After the transition point, mean temperature contributed 28.8 %, 41.7 %, and 21.6 % to resilience in the arid, semi-arid, and humid zones, respectively. These findings provide valuable insights for comprehending and assessing the ecological impacts of global and regional climate change mitigation efforts.
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Zhang et al. (2025) studied this question.
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