Randomized trial evaluates ecological zoning by linking ecosystem values and risk in a specific basin, indicating management implications.
Ecological zoning is important for understanding spatial heterogeneity and supporting landscape-level management. However, existing approaches rarely integrate ecosystem service supply with ecological risk, and their underlying nonlinear relationships remain insufficiently explored. This study aims to develop an integrated framework linking ecosystem service value (ESV) and landscape ecological risk (LER) based on a two-dimensional quadrant model. This framework integrates ESV and LER from complementary benefit–risk perspectives, advancing ecological zoning beyond single-indicator approaches. Using the Miyun Reservoir Basin as a case study, multi-source data from 2000 to 2020 were used to quantify ESV and LER and to examine their spatiotemporal dynamics. The ESV-LER framework was applied to identify ecological functional zones. In addition, the XGBoost-SHAP model combined with the Geographical Detector was used to explore the nonlinear effects and interactions of natural and anthropogenic drivers. ESV showed a “decline-recovery” trend, whereas LER exhibited an opposite “decrease-increase” pattern. Areas with both high ESV and high LER were mainly distributed around the reservoir and river networks, suggesting a spatial mismatch between ecological value and risk. Ecological improvement and conservation zones accounted for approximately 79% of the basin, while ecological risk prevention zones expanded over time, indicating increasing human disturbance. NDVI was identified as a dominant factor with dual effects, enhancing ESV while reducing LER, whereas population density and NPP exhibited nonlinear threshold effects that increased ecological risk. Overall, this study advances ecological zoning by integrating functional value and risk perspectives while explicitly revealing their nonlinear drivers. The proposed framework provides a transferable and interpretable approach for watershed-scale ecological management and supports more targeted and differentiated governance strategies.
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Li et al. (2026) studied this question.
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