Spatiotemporal Evolution and Nonlinear Drivers of Eco-Environmental Quality Under Production–Living–Ecological Space Transition in Northern Xinjiang: An XGBoost–SHAP Analysis

The development of arid-oasis agriculture and territorial spatial restructuring strongly influence regional eco-environmental quality. Clarifying production–living–ecological space (PLES) transitions and the nonlinear mechanisms driving eco-environmental quality is important for sustainable agricultural land use and ecological governance. Northern Xinjiang combines economic agglomeration with ecological sensitivity, making it a representative region for examining changes in eco-environmental quality and their underlying drivers. Land-use data for 1990, 2000, 2010, and 2020 were analyzed using land-use transition matrices, the eco-environmental quality index (EEQI), spatial autocorrelation, and hotspot analysis to characterize spatiotemporal changes under PLES transitions. XGBoost–SHAP was applied to identify the dominant factors, nonlinear responses, and interactions. The results showed that: (1) ecological space remained dominant from 1990 to 2020, but its share declined from 91.72% to 87.36%. Production and living spaces increased from 7.78% and 0.50% to 11.72% and 0.92%, respectively. Agricultural production space expanded most markedly, and spatial restructuring was most intense during 2000–2010. (2) EEQI decreased from 0.3100 to 0.2922 and showed an overall fluctuating decline. Significant spatial clustering was observed, with Moran’s I values consistently above 0.81 (p < 0.001). High-value areas were mainly distributed in the Ili River Valley and along the northern slope of the Tianshan Mountains, whereas low-value areas were concentrated in the Junggar Basin interior and the arid areas along its eastern margin. (3) During 2000–2020, LAI and NPP in agricultural production space increased by 45.7% and 48.2%, respectively. These increases indicated overall improvements in canopy condition and productivity. After 2010, NPP growth slowed markedly while LAI remained relatively stable, indicating a stage-specific divergence. (4) XGBoost–SHAP showed good robustness and spatial generalizability, with R2 values of 0.868–0.918 and RMSE values of 0.059–0.075. NDVI remained the primary driver, while Elev contributed consistently. The dominant interaction shifted from NDVI ∩ PopDen in 1990 and 2000 to NDVI ∩ Elev in 2010 and NDVI ∩ GDP in 2020. This shift indicated fundamental natural constraints and stronger joint effects of population and economic activities during the later stages. These findings provide a scientific basis for optimizing PLES, regulating arid-oasis agriculture, and safeguarding regional ecological security.