4.7 Article

Trend analysis of vegetation dynamics in Qinghai-Tibet Plateau using Hurst Exponent

Journal

ECOLOGICAL INDICATORS
Volume 14, Issue 1, Pages 28-39

Publisher

ELSEVIER
DOI: 10.1016/j.ecolind.2011.08.011

Keywords

Vegetation dynamic trend; NDVI; Hurst Exponent; R/S analysis; Consistency analysis; Qinghai-Tibet Plateau

Funding

  1. State Key Laboratory of Earth Surface Processes and Resource Ecology of China [2008-KF-04]
  2. National Key Research Development Plan of China [2010CB951704]
  3. National Natural Science Foundation of China [40801066, 41130534]

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As one of the most sensitive areas responding to global environmental change, especially global climate change, Qinghai-Tibet Plateau has been recognized as a hotspot for coupled studies on global terrestrial ecosystem change and global climate change. As an important component of terrestrial ecosystems, vegetation dynamic has become one of the key issues in global environmental change, and numerous case studies have been conducted on vegetation dynamic trend in different study periods. However, few are focused on the quantitative analysis of the consistency of vegetation dynamic trends after the study periods. In the study, taking Qinghai-Tibet Plateau as a case, vegetation dynamic trend during 1982-2003 were analyzed, with the application of the method of linear regression analysis. The results showed that, vegetation dynamics in Qinghai-Tibet Plateau experienced a significant increasing as a whole, with nearly 50% forest degradation in the study period. And among the 7 kinds of vegetation types, the change of forest was the most fluctuant with desert the least one. Furthermore, the consistency of vegetation dynamic trends after the study period, was quantified using Hurst Exponent and the method of R/S analysis. The results showed high consistency of future vegetation dynamic trends for the whole plateau, and inconsistent areas were mainly meadow and steppe distributed in the middle or east of the plateau. It was also convinced that, vegetation dynamic trends in the study area were significantly influenced by topography, especially the elevation. (C) 2011 Elsevier Ltd. All rights reserved.

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