摘要
Background In resource-based cities,long-term irrational exploitation of resources has caused severe damage to ecosystem functions,mainly manifested in the signifcant decline of biodiversity,land degradation,water pollution,and the deterioration of air quality.This has led to a signifcant decline in the cities’sustainable development capabilities.Establishing and optimizing an ecological spatial network(ESN)can promote the efective transmission of material energy and enhance the ecosystem functions,which holds fundamental importance in ensuring the ecological integrity of the region and promoting sustainable urban development.In this study,by combining the ecological environment with the landscape to determine the ecological sources,we constructed the ESN of Shenmu City,a mining city,based on the minimum cumulative resistance(MCR)model,and conducted a correlation analysis between the topological structure of the ESN and the signifcance of ecosystem functions.Then,the optimization strategy scheme based on ecosystem functions was proposed.Finally,robustness was used to determine the efect before and after optimization.Results The results showed that the high-value ecosystem service areas in Shenmu City were predominantly located in the central and western parts,with the highest value in the southeast.There was a strong correlation between the importance of ecosystem functions and the degree and feature vector of ecological nodes.Conclusions The ESN can be optimized efectively by adding stepping stone nodes and new corridors.Through the robustness of the optimized ESN,we found that the optimized network has more robust connectivity and stability and can show better recovery ability after ecological function damage.This research presents an efective method for the construction and optimization of the ESN in the mining area and provides a theoretical basis for realizing the sustainability of the mining economy,regional development,and ecological protection in Shenmu City.
基金
supported by the National Key Research and Development Program of China(2022YFE0127700)
the 5·5 Engineering Research&Innovation Team Project of Beijing Forestry University(No.BLRC2023B06).
