Evaluation of ecosystem vulnerability and its driving forces on the Qinghai-Tibet Plateau based on EVI dynamics

Abstract

The Qinghai-Tibet Plateau is a critical ecological barrier and an ecologically fragile zone in northern China and highly sensitive to climate change. In recent years, intensified climate warming and industrialization have increased pressures on the region, highlighting the need for an objective and comprehensive ecological vulnerability assessment model. Based on MODIS remote sensing data from 2001 to 2024, this study analyzed the spatiotemporal patterns of ecological vulnerability using the Enhanced vegetation index (EVI) as the core indicator. It quantified the sensitivity, adaptability, and vulnerability of the grassland ecosystem and underlying driving mechanisms. The results showed that: (1) spatially, the EVI-based ecological vulnerability exhibited overall moderate vulnerability, with the degree increasing progressively from non-vulnerable in the southeast to extremely vulnerable in the northwest. The Xinjiang Uygur and the Tibet Autonomous Regions showed particularly high ecological vulnerability; (2) the EVI-based grassland ecosystem vulnerability exhibited two temperature thresholds at − 7.66 ± 0.12 °C and − 4.50 ± 0.12 °C, and two precipitation thresholds at 241.79 ± 3.84 mm and 559.86 ± 5.29 mm. These thresholds define the climatic ranges within which the ecosystem maintains relatively high adaptability and low sensitivity, resulting in minimum ecological vulnerability; (3) the ecological vulnerability was dependent on external driving factors. Single-factor detection demonstrated that temperature is the dominant driving force. The explanatory power of all factor pairs was enhanced after interaction. Ecological vulnerability was dominated by slope and annual mean temperature, indicating that climate and topography jointly and profoundly shape the spatial differentiation of ecological vulnerability.

Keywords

Qinghai-Tibet Plateau / Ecological vulnerability / Enhanced vegetation index / Geodetector model / Spatial distribution

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Funding

the National Key Research and Development Program of China (2024YFF1306101)

The Chief Scientist Program of Qinghai Province (2024-SF-102)

RIGHTS & PERMISSIONS

Northeast Forestry University