| Autor: |
Liu JJ; College of Tourism and Landscape Architecture, Guilin University of Technology, Guilin 541004, Guangxi, China., Chen JR; College of Tourism and Landscape Architecture, Guilin University of Technology, Guilin 541004, Guangxi, China., Lai YN; College of Tourism and Landscape Architecture, Guilin University of Technology, Guilin 541004, Guangxi, China., Luo BY; School of Geographic Sciences, East China Normal University, Shanghai 200241, China., Zhao F; College of Tourism and Landscape Architecture, Guilin University of Technology, Guilin 541004, Guangxi, China., DU Q; College of Tourism and Landscape Architecture, Guilin University of Technology, Guilin 541004, Guangxi, China. |
| Abstrakt: |
In landscape ecology, the target species ecological network is often constructed by the least-cost path model (hereafter LCPM) to improve landscape connectivity among discrete habitats and to mitigate the negative impacts of habitat fragmentation. Nevertheless, the traditional ecological network method based on LCRM has insufficient understanding of landscape structure changes and ecological processes of research site. We used landscape pattern index and connectivity probability index to quantitatively evaluate the landscape structure and connectivity characteristics of the research area before and after the construction of the ecological network. The ecological network of the habitat of Presbytis leucocephalus, located in Chongzuo, Guangxi Province, was used as an example to describe the optimization and application of this method in detail. We identified the habitat and stepping stone patches of the target species, classified land use types of the study area, set up different resistant values, and obtained 20 corridors of ecological network using LCPM. The results showed that LCRM could effectively improve habitat integrity and continuity, reduce overall fragmentation level, and improve habitat quality based on the structural and functional connectivity evaluation by landscape pattern index and connectivity probability index. Meanwhile, its construction could improve the structural connectivity and functional connectivity of the habitat landscape, with significant consistency of the connection degree changes in both aspects (R 2 =98.3%, P<0.01). However, the relationship between landscape structure changes and functional connectivity caused by the network was not strong, and their relationship was not as significant as the inherent relationship between the structure and function. |
