Using multiple criteria for redesigning habitat corridor plans for Giant Pandas.
One key factor to long-term success in conservation planning is to allocate limited resources to the most critical locations and ensure the effectiveness of contemporary management plans under future conditions. Here, we proposed an innovative framework to quantitatively prioritize conservation acti...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0326792 |
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| Summary: | One key factor to long-term success in conservation planning is to allocate limited resources to the most critical locations and ensure the effectiveness of contemporary management plans under future conditions. Here, we proposed an innovative framework to quantitatively prioritize conservation actions for a vulnerable species, giant panda (Ailuropoda melanoleuca), and use it to identify Priority Habitat Corridors (PHCs) to address the threat of habitat fragmentation. We focused on the newly established Giant Panda National Park (GPNP), and combined field data with remotely-sensed landscape and anthropogenic metrics to evaluate the feasibility and effectiveness of potential habitat corridors. We first conducted habitat and corridor modeling and identified 72 candidate corridors. We then conducted gap analysis and applied multiple criteria to prioritize candidate habitat corridors. We identified 34,486 km2 of suitable habitat for giant pandas inside the GPNP and six PHCs that merit the highest priority because they were located at optimal elevation range with adequate forest coverage, had the capacity to connect multiple habitat patches, and were relatively feasible based on their conservation and anthropogenic interference status. Using an integrated modeling approach with biophysical, biotic, and anthropogenic criteria, our work provides a generic methodology to prioritize conservation actions which support future management for giant pandas and other wildlife species. |
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| ISSN: | 1932-6203 |