Structural Responses of Vegetation Resilience to Background-State and Temperature Asymmetry Across China: An Annual-Scale Causal Analysis

Vegetation resilience plays a key role in ecosystem stability as climate change and human disturbance intensify. We quantified resilience via AR(1) from kNDVI data over mainland China (2000–2024), and assessed its spatiotemporal patterns, long-term causal drivers (Causal Forest), and breakpoint-related mechanism shifts (non-stationary causal networks). Resilience varied strongly across space, with higher AR(1) values concentrated in northern transition belts and inland regions. Breakpoints clustered in 2010–2018 and showed broad synchronicity nationwide. Long-term effects were dominated by environmental background states: mean variables generally outweighed variability (CV) and memory terms, suggesting that persistent climate–environment conditions primarily shaped resilience gradients. Temperature emerged as the strongest national-scale control and acted asymmetrically across metrics—TMX strongly suppressed resilience, whereas TMN tended to enhance it—while precipitation and CO2 gained importance regionally. Driver networks reorganized markedly across breakpoints, exhibiting high edge turnover and heterogeneous lag shifts—pointing to stage-dependent restructuring that goes beyond changes in driver strength. This framework links net effects with mechanism reorganization to help diagnose vegetation resilience under non-stationary conditions.