Journal
BIOLOGICAL CONSERVATION
Volume 195, Issue -, Pages 128-135Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.biocon.2015.12.044
Keywords
Forest node; Forest connectivity; Deforestation simulation; Biodiversity conservation priority; Eastern Himalaya; China
Funding
- National Nature Science Foundation of China [31300453, 31272327]
- Ministry of Environmental Protection of China [20120928]
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International biodiversity conservation prioritization efforts often focus on biodiversity hotspots or valuable species. However, for most parts of the world, comprehensive species data with acceptable quality are still scarce to support regional priority evaluations. To model the factors that favor a high/important degree of biodiversity and threats; in this study, we provide an alternative conservation priority approach to use when species data are insufficient. Based on a Landsat-derived forest cover map of 2010 of the Eastern Himalaya of China, we defined forest nodes, measured and delineated their importance with the connectivity metric dPC at regional and sub regional scales. Based on a deforestation map of 2000 to 2010, we simulated deforestation from 2010 to 2030 using the Dinamica EGO software at multiple scales, and calculated the threatened degree of each forest node at an optimal scale. We then ranked the conservation priorities by coupling the measurements of the connectivity importance values and simulated threatened degree of each important forest node. Six forest patches (2.5% of remaining forest in 2010) were ranked as conservation priority patch-I and II. The unprotected parts are recommended to be expanded into or established as new nature reserves. Although species information was not used, the identified forest patches accommodated existing nature reserves (48% overlapped) in this region. As a fast and efficient assessment approach, with outcomes that are valuable for regional conservation planning, this method could be widely used for any forest dominant regions when field data is insufficient to identify conservation priorities at a fine scale. (C) 2016 Elsevier Ltd. All rights reserved.
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