Ecological Indicators (Oct 2023)

Assessment of multiple factors and interactions affecting grassland degradation on the Tibetan Plateau

  • Shanshan Wang,
  • Erfu Dai,
  • Lizhi Jia,
  • Yijia Wang,
  • Anqi Huang,
  • Lei Liao,
  • Liping Cai,
  • Donglin Fan

Journal volume & issue
Vol. 154
p. 110509

Abstract

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The Tibetan Plateau (TP), a vital region for terrestrial ecosystem services and biodiversity, is facing severe grassland degradation influenced by multiple factors. However, it remains unclear how several influential factors interactively influence grassland degradation. Here, we used five land cover products and six vegetation indexes to quantify grassland degradation on the TP. We then applied structural equation modeling (SEM) to quantitatively assess multiple factors and interactions affecting grassland degradation. We found that grassland degradation on the TP was mainly concentrated in the central and southern regions which were under high pressure from human activities, with the area of 325,430 km2, accounting for about 12.63% of the total grassland area on the TP during 2000–2020. The factors such as overgrazing, climate change, and human activities have contributed to the grassland degradation on the TP. Moreover, we found that there is a complex and interrelated relationship between these factors and that addressing one factor alone is unlikely to solve the problem of grassland degradation. Human activities significantly (p < 0.05) influenced grassland degradation on the TP, while climate factors had a greater direct effect (0.384) compared to soil factors (0.298) and human activities (0.263). Soil factors, on the other hand, had a greater total effect (0.388) than human activities (0.263) and climate factors (0.161). The topography of the TP played an indirect role (−0.4) in slowing down the degradation of grasslands by significantly (P < 0.05) affecting human activities and climate. In order to fully understand the truth about grassland degradation and to avoid further grassland degradation, it is necessary to consider multiple influencing factors and their interactions.

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