Spatial Imbalance and Driving Mechanisms of Human–Environment Coupling in the Xiuhe River Basin: Implications for Coordinated Ecosystem Services in Agricultural Landscape

This study examines the spatial imbalance and driving mechanisms of human–environment coupling in the Xiuhe River Basin, an important agricultural–ecological watershed in the middle and lower reaches of the Yangtze River. We integrated the coupling-coordination degree (C–D) model, Coupling Elasticity Index (CEI), spatial autocorrelation analyses (global and local Moran’s I, LISA, and Getis–Ord Gi*), and GeoDetector to assess spatial heterogeneity, classify coupling types, and identify key human–ecosystem. The results reveal marked spatial variation in coordination levels, which are higher in the central–western mountains and lower in the southeastern plains (global Moran’s I = 0.7344, p < 0.01), indicating significant spatial clustering. Using the CEI, the basin was classified into ecology-dominated zones (ecological advancement with human retreat), human-dominated zones (human advancement with ecological retreat), and relatively balanced zones. Upstream areas (CEI < 0.6) exhibit ecological advantages, whereas downstream plains (CEI > 1.5) experience dominant human pressures. GeoDetector analysis identified population density, proportion of built-up land, and water quality indicators (COD and TP) as the primary drivers, with interactions substantially enhancing explanatory power (e.g., PD × COD q = 0.86). These findings underscore nonlinear feedbacks and cross-scale interactions that influence coordinated ecosystem services in agricultural landscapes. We recommend differentiated management strategies: conserving upstream ecological functions, promoting balanced development in midstream areas, and regulating development intensity and pollution downstream to sustain human–environment coordination. This study provides quantitative evidence and methodological insights to improve understanding of ecological complexity and optimize governance of the agricultural landscape.