Vegetation Dynamics in Response to Climate Change and Human Activities in a Typical Alpine Region in the Tibetan Plateau

Int J Environ Res Public Health. 2022 Sep 28;19(19):12359. doi: 10.3390/ijerph191912359.

Abstract

Understanding past and future vegetation dynamics is important for assessing the effectiveness of ecological engineering, designing policies for adaptive ecological management, and improving the ecological environment. Here, inter-annual changes in vegetation dynamics during 2000-2020, contributions of climate change (CC) and human activities (HA) to vegetation dynamics, and sustainability of vegetation dynamics in the future were determined in Gannan Prefecture (a typical alpine region in the Tibetan Plateau), China. MODIS-based normalized difference vegetation index (NDVI), air temperature, precipitation, and land cover data were used, and trend analysis, multiple regression residuals analysis, and Hurst exponent analysis were employed. NDVI increased at a rate of 2.4 × 10-3∙a-1 during the growing season, and vegetation improved in most parts of the study area and some sporadically degraded areas also existed. The increasing rate was the highest in the Grain to Green Project (GTGP) areas. The vegetation in the southern and northern regions was mainly affected by CC and HA, respectively, with CC and HA contributions to vegetation change being 52.32% and 47.68%, respectively. The GTGP area (59.89%) was most evidently affected by HA. Moreover, a Hurst exponent analysis indicated that, in the future, the vegetation in Gannan Prefecture would continuously improve. The study can assist in formulating ecological protection and restoration projects and ensuring sustainable development.

Keywords: Hurst exponent; ecological projects; human activities; residual analysis; vegetation dynamics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Climate Change*
  • Ecosystem*
  • European Alpine Region
  • Human Activities
  • Humans
  • Temperature
  • Tibet

Grants and funding

This research was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grants No. XDA26010202, XDA19040301), and the Fundamental Research Funds for the Central Universities (CUG2106311).