Abstract
Coal mining activities, while promoting urban development, also lead to significant ecological and environmental issues that directly impact regional habitat quality and perception levels. The effective assessment of habitat services and zoning optimization can facilitate ecological restoration in coal mining subsidence areas and enhance public awareness of the ecological service value of habitats. Taking the Longdai River Basin in Huaibei City as a case study, this research constructs a “habitat quality–habitat perception” assessment framework from a social–ecological coupling perspective, integrating the InVEST and SolVES models for a comprehensive evaluation. The coupling coordination degree model is used to analyze the relationship between habitat quality and perception, allowing for the zoning of habitat services. The results indicate that the average habitat quality in the study area is 0.373, reflecting an overall low level. Its spatial distribution exhibits a trend of “higher in the central–southern and northwestern regions and lower in the southwestern and northeastern regions”. Habitat perception mainly presents a “multi-patch” spatial pattern. The coupling degree C between habitat quality and habitat perception is 0.676, while the coupling coordination degree D is only 0.377, indicating a state of mild imbalance in the coupling coordination development. Moreover, disordered units account for as much as 69.22%. Based on the matching and coupling coordination between habitat quality and perception, the study area can be classified into four main categories and eight smaller habitat service zones. Considering the differences in urban–rural gradient spaces, optimization strategies for habitat services based on social–ecological coupling are proposed.
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Hu, B., Zhou, S., Luo, P., & Chen, H. (2025). Assessment of Habitat Services and Gradient Zoning Optimization in Coal Mining Subsidence Areas from a Social–Ecological Coupling Perspective. Sustainability (Switzerland), 17(1). https://doi.org/10.3390/su17010017
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