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<p>Karst regions in southwest China face acute ecological risks due to fragile geological structures, rocky desertification, and sensitivity to human disturbance. Rapid urbanization and tourism growth have further intensified pressures on ecological security, making it essential to evaluate risk patterns and their drivers. This study constructed an ecological risk index (ERI) using multi-source geospatial datasets from 2000 to 2020 and integrated spatial autocorrelation analysis with the XGBoost-SHAP machine learning framework to assess spatiotemporal dynamics in Zunyi, a representative karst region. Results revealed significant spatial clustering: high-risk zones (ERI ≥ 0.079) were concentrated in areas of urban expansion, dense population, and tourism infrastructure, while low-risk zones (ERI &lt; 0.049) were mainly restricted to protected areas (PAs) with strict land-use regulations. Although high-risk areas declined by 18.7% over two decades, medium-high and high-risk categories still covered 43.3% of the region in 2020, indicating persistent vulnerability. Driver analysis showed precipitation (24%), vulnerability degree (20%), and fragmentation (18%) as key natural contributors, while anthropogenic factors collectively explained 67% of ecological risk, highlighting their dominant role. Landscape ecological risk (LER) exhibits a U-shaped response pattern with its drivers, sharing striking similarities to the Environmental Kuznets Curve (EKC) in ecological risk management. This demonstrates that the core logic of this study aligns with that of the EKC—namely, the non-monotonic relationship between human socioeconomic development and environmental change. It further proves that this response pattern is equally applicable to the management of karst landscape ecological risk. Overall, these findings suggest human-driven changes significantly shape karst ecological risks and highlight the value of integrated assessments for targeted zoning and conservation.</p>

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Unraveling karst vulnerabilities: spatiotemporal shifts and anthropogenic drivers shaping Zunyi’s landscape ecological risk

  • 期刊论文

  • 发表日期：

    2026年3月28日

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  • Yi Wei,
  • Yi Liu,
  • Bo Xie,
  • Zhaozhao Ao,
  • Mingming Zhang

摘要

Karst regions in southwest China face acute ecological risks due to fragile geological structures, rocky desertification, and sensitivity to human disturbance. Rapid urbanization and tourism growth have further intensified pressures on ecological security, making it essential to evaluate risk patterns and their drivers. This study constructed an ecological risk index (ERI) using multi-source geospatial datasets from 2000 to 2020 and integrated spatial autocorrelation analysis with the XGBoost-SHAP machine learning framework to assess spatiotemporal dynamics in Zunyi, a representative karst region. Results revealed significant spatial clustering: high-risk zones (ERI ≥ 0.079) were concentrated in areas of urban expansion, dense population, and tourism infrastructure, while low-risk zones (ERI < 0.049) were mainly restricted to protected areas (PAs) with strict land-use regulations. Although high-risk areas declined by 18.7% over two decades, medium-high and high-risk categories still covered 43.3% of the region in 2020, indicating persistent vulnerability. Driver analysis showed precipitation (24%), vulnerability degree (20%), and fragmentation (18%) as key natural contributors, while anthropogenic factors collectively explained 67% of ecological risk, highlighting their dominant role. Landscape ecological risk (LER) exhibits a U-shaped response pattern with its drivers, sharing striking similarities to the Environmental Kuznets Curve (EKC) in ecological risk management. This demonstrates that the core logic of this study aligns with that of the EKC—namely, the non-monotonic relationship between human socioeconomic development and environmental change. It further proves that this response pattern is equally applicable to the management of karst landscape ecological risk. Overall, these findings suggest human-driven changes significantly shape karst ecological risks and highlight the value of integrated assessments for targeted zoning and conservation.