Spatiotemporal Variation of Vegetation Greenness and Its Climate Response in the Da Hinggan Mountains

Understanding vegetation greenness dynamics and their climatic drivers in cold-temperate forest ecosystems is essential for regional ecological assessment and sustainable forest management. This study investigated the spatiotemporal characteristics of vegetation greenness and its response to climate variability in the Da Hinggan Mountains, a critical cold-temperate forest region in northeastern China. Using the Google Earth Engine platform, we acquired Landsat-derived growing-season maximum normalized difference vegetation index (NDVI) composites, ERA5-Land temperature and precipitation datasets, and SRTM digital elevation model data spanning 13 biennial growing-season snapshots from 2000 to 2024. The Theil-Sen median slope estimator and Mann-Kendall trend test were employed to detect spatial trends in NDVI, temperature, and precipitation, while partial correlation analysis was applied to quantify the independent linear relationships between climatic variables and NDVI change. Results indicated that the regional mean growing-season maximum NDVI increased from 0.376 in 2000 to 0.404 in 2024, reflecting a gradual overall greening trend. At the pixel scale, significantly greening pixels constituted 22.26% of valid pixels, significantly degrading pixels accounted for 0.97%, and pixels exhibiting non-significant change comprised 76.78%. Meteorological trend analysis revealed predominantly negative temperature slopes without statistically significant warming areas, alongside a widespread but weakly significant increasing precipitation tendency. Partial correlation analysis demonstrated that areas with significant correlations between NDVI and temperature or precipitation were limited to 2.57% and 3.92%, respectively, while 94.12% of the region lacked significant climate response. These findings suggest that vegetation greenness changes in the Da Hinggan Mountains result from the combined influence of forest natural succession, ecological conservation policies, topographic factors, and nonlinear climate interactions, rather than linear climatic forcing alone.