Abstract

Sanjiangyuan region, which located in the north of Qinghai-Tibet Plateau in China, is characterized by an extreme environment and is subject to the impacts of climate change and intense human activities. To protect the eco-environment in Sanjiangyuan, the Sanjiangyuan National Nature Reserve (SNNR) was established in 2000, and an ecological project was initiated in 2005. Comprehensive and quantitative evaluation of the eco-environmental vulnerability (EV) and analysis of the long-term dynamic changes in the region are extremely important for understanding eco-environmental change and assessing protection effectiveness, however rarely found in previous research.The aim of this study is to develop a method to assess EV and analyse the dynamic change in Sanjiangyuan region for years 1990, 2000 and 2010. In the first phase of the study, an integrated evaluation method based on Fuzzy Analytic Hierarchy Process (FAHP) was developed. This phases included:■development of the evaluation hierarchical structure and selection criteria;■data collection and processing;■evaluation criteria normalization;■determination of the related importance of the criteria;■criteria weighting calculation, and;■linear weighted combination.In the second phase of the study, the developed methodology was applied to assess the EV in the Sanjiangyuan region for the years 1990, 2000, and 2010, and to document the dynamic change. In the third phase, a series of integrated regional EV grades were used to analyse the EV change both within and outside of SNNR.The results showed that: 1) EV in the whole Sanjiangyuan region was distributed as a high/low gradient that trends west to east in all three study periods; 2) the dynamic change of EV in Sanjiangyuan region as a whole showed a moderate reduction during 1990–2000, a sizeable and extensive decrease during 2000–2010; and, 3) during the 2000–2010 period, ecological environment change magnitude was significantly better within the Sanjiangyuan National Nature Reserve than for the unprotected areas of the region. The proposed method is relatively easy to implement and could also be applied to other study regions. However, the method could be further improved by reducing some subjective elements.

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