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Mapping biodiversity conservation priorities for protected areas: A case study in Xishuangbanna Tropical Area, China 

 
论文编号:
作者: Huang ZD
刊物名称: Biological Conservation
所属学科:
论文题目英文: Mapping biodiversity conservation priorities for protected areas: A case study in Xishuangbanna Tropical Area, China
年: Sep 2020
卷: 249
期:
页: 108741
联系作者: Bai Y
收录类别:
影响因子: 4.711
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摘要:

Global biodiversity is declining rapidly, posing a severe threat to ecosystem functions and services. Protected Areas (PAs) can be extremely effective in protecting biodiversity, but conservation gaps arise as a result of poor consideration of land-use change and its impacts, and of integrated planning based on representative ecological indicators. New approaches are available to identify conservation priorities for new comprehensive PAs and ensure that endangered species are effectively protected, we used the Habitat Quality module in the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and the Maximum Entropy (MaxEnt) model to assess a protected area in Xishuangbanna tropical area, China. The results revealed unprotected biodiversity hotspots occupying a total area of 4669.60 km2, or 24.37% of the total area of Xishuangbanna, including a key conservation gap of 1228.85 km2 (6.08% of total area). The conservation priorities outside PAs were mainly distributed in north-east Xishuangbanna, followed by the south-east (scattered distribution). This indicates that existing PAs do not offer adequate protection for local biodiversity. Our combined modeling (MaxEnt-InVEST) framework proved successful in creating maps of conservation gaps of biodiversity hotspots based on actual species distribution data and can consider current land uses. For well-targeted organized planning in local PAs, obligations and objectives of international agreements need to be met and scientific interventions for protecting key habitats of the endangered species need to be delineated. We also identified a need for incorporating reliable monitoring and management networks into global biodiversity assessment and conservation.

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