Vegetation responsiveness to precipitation is a vital indicator for evaluating vegetation reactions to water cycle variations and forecasting forthcoming ecological shifts. However,the sensitivity and associated trends across diverse arid and humid ecosystems,as well as varying vegetation types,are still poorly understood. This study employs a linear regression model,integrating two vegetation indices,to estimate the sensitivity of vegetation in China to precipitation from 2001 to 2020,and analyzes its spatial distribution and temporal progression. The findings show that the aggregate precipitation sensitivity of Chinese vegetation is affirmative and displays an upward trajectory. Spatially,there is a positive correlation between vegetation sensitivity to rainfall and regional aridity levels,with the order: arid regions > semi-arid regions > semi-humid regions > humid regions. Notable disparities in precipitation sensitivity are observed among different vegetation types,with the highest sensitivity found in temperate desert and grassland ecosystems,where water availability is significantly constrained,while the lowest sensitivity is noted in regions with ample precipitation or temperature-limited ecosystems,such as tropical rainforests and boreal coniferous forests. Temporally,the precipitation sensitivity of vegetation in arid,semi-arid,and semi-humid regions exhibits an upward trend,whereas a decline is observed in humid regions. This phenomenon can be attributed to increased water demand driven by vegetation growth and enhanced surface evapotranspiration resulting from climate warming. Additionally,this study quantifies the contributions of changes in precipitation sensitivity across different arid and humid zones to the overall increase in sensitivity,indicating that arid regions contribute the most to this trend,with both vegetation indices showing contributions exceeding 50%,followed by semi-arid regions. Consequently,amidst ongoing global warming,it is anticipated that vegetation's sensitivity to precipitation variability will intensify,requiring strategic approaches to bolster water resource management in light of climate change.