Qinling region, as the main habitat of the Giant panda with abundant species resources, was considered as one of the most important biodiversity hotspots in China. Recent years, because of the habitat fragmentation, and the conflict between economic development and biodiversity conservation, the question how to protect the biodiversity in the maximum extent with minimum cost in this critical region attracted more and more attention of scientists and policymakers in China. In this study, we explored a way to maximize protection efficiency by identifying Priority Area for Biodiversity Conservation (PABC), and building/optimizing biodiversity conservation network. The PABC was identified by using a SCP (System Conservation Planning) model, C-plan, with combining the results from biodiversity assessments in three levels, species, habitat and ecosystems. We statistically measured the biodiversity in species level by using Important Value Index from richness of all the higher plants and terrestrial vertebrates, and also the threatened and endemic species analysis, respectively. The habitat suitability was projected by potential habitat for flagship species and target-species for protection in this region. For the ecosystem level, we assessed the ecosystem pattern, services and vulnerability. Then, we use GAP analyses to build and optimize the biodiversity conservation spatial explicit network.
Results/Conclusions
The SCP model results showed that, the habitat for biodiversity in this region is fragmented. Six separated patches were identified as PABC (15.68% of the total study area): Guanshan forest region, Huashan-Dafu valley, Taibai-Zhongnan Mountain, Hanzhong Basin, Micang Mountain and Hualong Mountain. The protection priority of the area were represented by irreplaceability value. The results showed that, over 71% of the existing nature reserves were of high-irreplaceability value (0.6-1.0), with the area of medium-irreplaceability value (0.4-0.6) and low-irreplaceability value (<0.4) accounted for only 14.01% and 14.12% of the existing nature reserves, respectively, indicating that the location of the existing nature reserves were relatively reasonable, and only one patch as protection gaps were identified. However, the existing nature reserves covered only 11.19% of the entire area of high-irreplaceability value, which means, 88.81% of the area with high protection priority were still inadequately protected. Besides, we also identified some area as potential connections and corridors between different patches. By integrating these results, we built and optimized the spatial explicit network for biodiversity conservation.