Modeling the ecological network in mountainous resource-based cities: Morphological spatial pattern analysis approach

Abstract

Landscape fragmentation in mountainous resource-based cities has become increasingly serious, particularly in blue-green spaces. This study aims to establish a quantitative theoretical foundation for constructing an ecological network using the integrated morphological spatial pattern analysis (MSPA)–Conefor–minimum cumulative resistance (MCR) model. It employs multiple data sets, including land use data, remote sensing images, Shuttle Radar Topography Mission (SRTM) digital elevation, vegetation coverage data, etc., to conduct the quantitative analysis. Five groups of spatial resolution datasets (i.e., 30 m, 60 m, 90 m, 150 m, and 300 m) are employed for comparison and selection through MSPA to identify and analyze core landscape types. Connectivity analysis uses Conefor 2.6 software, and ecological sources are selected accordingly. Subsequently, the MCR model is applied to construct ecological corridors. Moreover, 153 ecological corridors are delineated, comprising 78 primary and 58 secondary corridors. The results show that most ecological core patches are fragmented and dispersed, while ecological corridors are vulnerable to disruption by external interference. This study also identifies 470 ecological breakpoints, mainly concentrated in the northeast, central, and southwestern areas characterized by high corridor density and intense anthropogenic activity. Additionally, 39 biological resting points are primarily located in the central urban area, and peripheral areas show few or no such points. This suggests establishing additional biological resting points to facilitate species migration and diffusion and complement the ecological network. This research addresses a significant gap in ecological network modeling within mountainous resource-based cities by developing a blue-green ecological network model. The findings encourage ecological governance bodies and technical professionals to recognize the interdependent relationship between blue and green spaces. This study supports the formulation of targeted planning strategies and helps maintain the potential connectivity essential for ecological balance.