Ecological risk networks: A network structure model for simulating negative ecological linkages among ecologically sensitive areas

Research on structural modeling of negative ecological flow networks across ecologically sensitive regions can reveal potential ecological risks in the region. We define this network structure model that simulates the interconnections of structural functions between discrete and isolated ecologically sensitive areas, and the negative ecological flows between them, as an ecological risk network. We chose an inland province, Shaanxi Province, at the junction of north and south China, as a research case. This article adopts the method of physical quality assessment to assess the ecological sensitivity of the research case. It identifies the risk source sites based on the evaluation results. Subsequently, potential risk corridors are determined based on circuit theory and the Minimum Cumulative Resistance (MCR) model. Finally, we constructed an ecological restoration pattern in Shaanxi Province and made targeted recommendations. 34 ecological risk sources, 50 nodes, and 77 corridors were identified. The research results indicate that there are more ecological risk networks in the northern part of the province, followed by the central part, and very few in the southern part. By analyzing the resistance surface of the ecological risk network, we found that the spatial distribution was formed because the Huanglongshan-Ziwuling mountain range hindered the connection between the dense ecological risk network area in the northern region of Shaanxi and the sparse area in the central region of Shaanxi. And the Qinling mountain range impeded the flow and diffusion of negative ecological flows in the northern part of Shaanxi and the central part of Shaanxi to the southern part of Shaanxi. The results of constructing the ecological restoration pattern show that cropland and grasslands are the most dominant ecological restoration patches. Some ecological restoration corridors and ecological restoration nodes overlap with the water and transportation networks. Targeted prevention and restoration strategies can be proposed in response to the above findings. This study is a practice and exploration of ecological risk network research. The results of this research can provide a theoretical reference for ecological restoration.