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  • 标题:A Long-Term Ecological Vulnerability Analysis of the Tibetan Region of Natural Conditions and Ecological Protection Programs
  • 本地全文:下载
  • 作者:Yunxiao Jiang ; Yu Shi ; Rong Li
  • 期刊名称:Sustainability
  • 印刷版ISSN:2071-1050
  • 出版年度:2021
  • 卷号:13
  • 期号:19
  • 页码:10598
  • DOI:10.3390/su131910598
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:The combined impacts of drastic natural environment change and increasing human interference are making the uncertainty of the Tibetan Plateau’s ecological vulnerability the world’s largest. In this study, an ecological vulnerability index (<i>EVI</i>) of Tibet in the core area of the Tibetan Plateau was assessed using a selected set of ecological, social, and economic indicators and using a spatial principal component analysis (SPCA) to calculate their weights. The data included Landsat images and socio-economic data from 1990 to 2015 in five-year intervals. The results showed that the total <i>EVI</i> remained at a high vulnerability level, with drastic fluctuation from 1990 to 2000 (a peak in 1995, when there was a sudden increase in light vulnerability, which moved to extreme vulnerability in the next period), and minor fluctuations after 2000, gradually increasing from southeast to northwest. In addition, the spatial analysis showed a distinct positive correlation between the <i>EVI</i> and grassland area (0.33), land use degree (0.15), NDVI (0.14), livestock husbandry output, and a negative correlation in terms of desertification area. The artificial afforestation program (AAP) had a positive significant correlation with NDVI (R<sup>2</sup> = 0.88), preventing the environment from becoming more vulnerable. The results provide practical information and suggestions for planners to improve the land use degree in urban areas and the vegetation coverage in pastoral regions of the Tibetan Plateau based on the spatial–temporal heterogeneity patterns of the <i>EVI</i> of Tibet.
  • 关键词:ecological vulnerability; Tibetan Plateau; spatial principal components analysis; artificial afforestation program; Getis-Ord Gi*; linear regression model
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