Spatiotemporal Dynamics, Climate Lag Effects, and Environmental Associations of Vegetation Cover Across the Western Sichuan Plateau During 2001–2024

Vegetation dynamics in alpine ecosystems are highly sensitive to climate and environmental changes. However, the spatial heterogeneity of vegetation cover and its lagged associations with climate variability remain insufficiently understood. This study estimated fractional vegetation cover (FVC) based on MOD13Q1 NDVI data. The Sen’s slope and Mann–Kendall tests were employed to describe trends in FVC change, while pixel-based Pearson correlation analysis was used to quantify lagged associations (0–12 months) between temperature and precipitation and FVC. Furthermore, the XGBoost–SHAP framework was used to quantify nonlinear environmental associations with the spatial variation in FVC. The results showed that, from 2001 to 2024, the growing-season FVC on the Western Sichuan Plateau exhibited a significant increasing trend, with an average value of 0.7062 and a rate of 0.0018 yr−1 (R2 = 0.5040, p < 0.001). Areas with high and relatively high FVC values accounted for 75.7873% of the study area, indicating generally favourable vegetation conditions with substantial spatial heterogeneity. Both temperature and precipitation exhibited lagged associations with FVC, with long-term lags (7–12 months) accounting for 45.6600% and 45.0768% of the study area, respectively. After integrating topography and land-cover information, the explanatory power of the XGBoost model was enhanced, with the R2 value increasing from 0.2181 in the climate-only model to 0.6393 in the full ecological model (RMSE = 0.1800, MAE = 0.1263). SHAP analysis indicated that DEM (elevation), LC_10 (grasslands), and TMEAN (Temperature_2m) made the largest contributions to the modelled spatial variation in FVC, accounting for 39.0853%, 17.3644%, and 10.3859%, respectively. These results indicate persistent associations between FVC spatial heterogeneity and topographic, land-cover, and climatic gradients.