Duration of vegetation green-up response to snowmelt on the Tibetan Plateau

Abstract

The Tibetan Plateau (TP) is characterized by abundant snow and heightened sensitivity to climate change. Although the impact of snowmelt on vegetation green-up is well recognized, the duration of vegetation response to snowmelt on the TP remains unclear. This study calculates the time differences between the green-up date and the start of snowmelt from 2001-2018 on the TP, denoted as ΔD. Exploratory spatial data analysis and the Mann-Kendall test were then applied to investigate the spatiotemporal distribution feature of ΔD. Subsequently, partial correlation and multiple linear regression analysis were employed to examine the impact of spring mean temperature, spring total rainfall, and daily snowmelt on ΔD. The results reveal that the mean ΔD across the TP was 38.5 d, with a spatially clustered distribution: low ΔD values were concentrated in the Hengduan Mountains, while high ΔD values were observed in the Bayankara and Himalaya mountains. Additionally, ΔD shortened with increasing spring temperature, total rainfall, and daily snowmelt, which accounted for 23.5%, 28.8%, and 35.4% of ΔD variation, respectively. In 67% of arid areas and 64% of regions with low vegetation, daily snowmelt was the dominant factor influencing ΔD. Conversely, spring temperature played a primary role in 48% of humid areas and 37% of regions with high vegetation. Our findings enhance the understanding of vegetation responses to snowmelt and provide a scientific foundation for further research on the stability of alpine ecosystems and the impacts of climate change on the TP.