Vegetation Changes in the Three-River Source Region: Responses to Extreme Climate Events and Time-Lag Effects During 2000–2024

The Three-River Source Region (TRSR) is an environmentally fragile area in China and on the Qinghai–Tibet Plateau that is extremely vulnerable to climate change. The time lag between climate change and vegetation responses in high-altitude regions is a critical component of ecosystem–climate coupling that has not yet been fully quantified. The purpose of this project is to look into the influence of extreme climatic change in the TRSR on vegetation development, as well as to give data support for vegetation restoration and ecological security on the Qinghai–Tibet Plateau. This study used normalized difference vegetation index (NDVI) data from the TRSR from 2000 to 2024 to investigate the pixel-level lag effects of 12 ETCCDI (Expert Team on Climate Change Detection and Indices) extreme climatic indices. Pixel-level maximum Pearson correlation analysis was used to determine the ideal lag period and correlation direction within an 0–6-month lag window, and the lag ratios for seven vegetation kinds were quantified in stratified order. The results show that precipitation, and not temperature, is the primary climatic limiting factor for changes in NDVI in the TRSR. Furthermore, there is a clear distinction between the temperature- and the precipitation-driven lag responses: temperature extreme indices have shorter average response times and highly polarized correlation directions (positive correlation proportions range from 1.0% to 95.9%), whereas precipitation extreme indices have longer average lags and are predominantly positively correlated. Vegetation types have a significant impact on lag sensitivity: grassland and desert respond faster, reflecting shallower root depths and limited soil moisture buffering capacity, whereas meadows and shrubland have the longest lags, consistent with the water-holding capacity promoted by deeper root systems and higher soil organic matter. These findings contribute to our understanding of time-structured vegetation–climate coupling and provide a solid scientific foundation for proactive vegetation management in the TRSR to meet future extreme climate events.