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Updated: Aug 5, 2026

The Use of High-resolution Infrared Thermography (HRIT) for the Study of Ice Nucleation and Ice Propagation in Plants
Published on: May 8, 2015
Seasonal transition in snow effects on vegetation growth across the Tibetan Plateau
Zekai Meng1,2,3, Xiuchen Wu4, Yongmei Huang1,2
1State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Beijing Normal University, Beijing, China.
Abstract:
Snow exerts intricate influences on alpine ecosystems, and winter snow process is undergoing drastic change with climate warming. Yet the impacts of winter snow on vegetation growth (hereafter, snow effects) and their underlying mechanisms remain uncertain, as snow effects operate through multiple pathways. Based on remote sensing-derived snow and vegetation products, we examine the snow effects on vegetation growth in spring and summer across the Tibetan Plateau through partial correlation analysis. We then quantify the distinct pathways through which snow influences vegetation growth in spring and summer using pixel-wised piecewise-Structural Equation Modeling, and further identify the transitions of dominant ecological processes underlying these effects. We report a marked seasonal transition of snow effects on vegetation growth, with negative-to-positive shifts observed in 25% of the Tibetan Plateau from spring to summer. The negative snow effects in spring are mainly attributable to the snowmelt-date (SMD)-induced phenological pathway, through which earlier snowmelt advances spring phenology and thereby influences vegetation growth. In contrast, snow effects in summer are predominantly positive due to the reversal of snow-induced phenological effects from spring and the carryover of snow-driven soil moisture effects into summer, which promotes vegetation growth. Finally, we found that most of the dynamic global vegetation models (DGVMs) used in this study have limited ability to reproduce this seasonal transition in snow effects. These findings highlight the critical seasonal shifts in ecological processes that underpin snow effects on ecosystems, providing valuable insights into improving ecosystem models.
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