Environmental interpretation of spatial heterogeneity in the trade-offs and synergies of land use functions: A study based on the XGBoost-SHAP model

Abstract Accurately revealing the spatial heterogeneity in the trade-offs and synergies of land use functions (LUFs) and their driving factors is imperative for advancing sustainable land utilization and optimizing land use planning. This is especially critical for ecologically vulnerable inland river basins in arid regions. However, existing methods struggle to effectively capture complex nonlinear interactions among environmental factors and their multifaceted relationships with trade-offs and synergies of LUFs, especially for the inland river basins in arid regions. Consequently, this study focused on the middle reaches of the Heihe River Basin (MHRB), an arid inland river basin in northwestern China. Using land use, socioeconomic, meteorological, and hydrological data from 2000 to 2020, we analyzed the spatiotemporal patterns of LUFs and their trade-off and synergy relationships from the perspective of production, living, ecological functions. Additionally, we employed an integrated Extreme Gradient Boosting (XGBoost)- SHapley Additive exPlanations (SHAP) framework to investigate the environmental factors influencing the spatial heterogeneity in the trade-offs and synergies of LUFs. Our findings reveal that from 2000 to 2020, the production, living, and ecological functions of land use within the MHRB exhibited an increasing trend, demonstrating a distinct spatial pattern of “high in the southwest and low in the northeast”. Significant spatial heterogeneity defined the trade-off and synergistic relationships, with trade-offs dominating human activity-intensive oasis areas, while synergies prevailed in other areas. During the study period, synergistic relationships between production and living functions and between production and ecological functions were relatively robust, whereas synergies in living-ecological functions remained weaker. Natural factors (digital elevation model (DEM), annual mean temperature, Normalized Difference Vegetation Index (NDVI), and annual precipitation) emerged as the primary factors driving the trade-offs and synergies of LUFs, followed by socioeconomic factors (population density, Gross Domestic Product (GDP), and land use intensity), while distance factors (distance to water bodies, distance to residential areas, and distance to roads) exerted minimal influence. Notably, the interactions among NDVI, annual mean temperature, DEM, and land use intensity exerted the most substantial impacts on the relationships among LUFs. This study provides novel perspectives and methodologies for unraveling the mechanisms underlying the spatial heterogeneity in the trade-offs and synergies of LUFs, offering scientific insights to inform regional land use planning and sustainable natural resource management in inland river basins in arid regions.