Author:
Wang Pan,Feng Bin,Zhang Li,Fan Xueyang,Tang Zhuo,Dong Xin,Zhang Jindong,Zhou Caiquan,Bai Wenke
Abstract
Habitat suitability assessment is the basis for wildlife conservation management and habitat restoration. It is a useful tool to understand the quality of wildlife habitat and its potential spatial distribution. In order to reveal the habitat suitability and connectivity of sambar (Rusa unicolor) to promote species and biodiversity conservation, this study collected records of sambar (Rusa unicolor) from over 2,000 camera traps in the forests of Southwest China in the past 5 years to assess the overall situation of their habitat. The results of the species distribution model revealed that the suitable habitat area for sambar in the five major mountain ranges (Minshan, Qionglai, Daxiangling, Xiaoxiangling, and Liangshan) in Southwest China is 18,231 km2, accounting for 17.02% of the total area. The most suitable habitat of sambar is primarily distributed in Qionglai, as well as the intersection areas of Daxiangling, Xiaoxiangling, and Minshan. The temperature annual range, temperature seasonality, elevation, and distance to road were important factors affecting the distribution of suitable habitat for sambar. Analysis of landscape pattern shows that there were 273 habitat patches, with a maximum patch area of 9,983 km2, accounting for 54.8% of the total suitable habitat area. However, the segmentation index and separation index of each habitat patch were 0.99 and 106.58, respectively, indicating a relatively high habitat fragmentation in the study area. The results of habitat connectivity analysis showed that the Qionglai mountains have the largest suitable habitat area and the highest connectivity among habitat patches. However, habitat connectivity between the five mountains is very low, suggesting that gene flow among these mountain ranges is probably limited. We therefore recommend strengthening protection of sambar and their habitat, with special attention to the establishment of corridors between the different mountain populations.
Funder
China Postdoctoral Science Foundation
National Natural Science Foundation of China
Sichuan Province Science and Technology Support Program
Subject
Management of Technology and Innovation