Sustainability-Oriented Governance of Tourism Corridors: Decoupling Socioeconomic Pressure and Ecological Vulnerability with Explainable AI and Evolutionary Optimization

Linear tourism corridors can stimulate regional economic revitalization, but they may also intensify land conversion, fragment habitats, and challenge the long-term sustainability of ecologically sensitive landscapes. Resolving this tension requires a transition from qualitative zoning to data-driven, threshold-informed spatial governance. This study develops a continuous analytical pipeline to support land-use governance along China National Highway 331 (G331). We integrated principal component analysis (PCA) with a Bayesian-optimized eXtreme Gradient Boosting (XGBoost) model, validated through Spatial Block Cross-Validation to reduce spatial data leakage and provide a more conservative assessment of geographic transferability. Shapley Additive Explanations (SHAP) was used to interpret localized non-linear associations, threshold patterns, and spatially heterogeneous model responses. Empirical results indicate that anthropogenic socioeconomic intensity is the dominant predictive driver associated with spatial variation in ecological quality. The SHAP analysis identified model-derived threshold patterns, including an approximate population-density threshold around 4000 people per square kilometer and a corridor-distance response around 50 km from the G331 highway. To translate these model-derived explanatory insights into spatial governance scenarios, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used to approximate the Pareto trade-off frontier between ecological integrity and socioeconomic expansion. This multi-objective optimization delineated three spatial governance scenarios and identified a Pareto-elbow configuration that supports compatible-use management. This closed-loop framework provides a transferable analytical approach for sustainability-oriented corridor governance by identifying where development may be concentrated, where ecological buffers should be strengthened, and where strict conservation should be prioritized.