Spatial Patterns and Regulators of Drought Resistance and Resilience in the Qinling–Daba Mountain Ecosystems

Under global climate change, escalating drought frequency and intensity threaten ecosystem stability, yet the resistance and resilience of ecosystems in climate transition zones remain poorly characterized. This study quantified ecosystem resistance and resilience to drought in the Qinling–Daba Mountains (QDMs)—China’s North–South Transitional Zone using the Standardized Precipitation Evapotranspiration Index (SPEI) and four sets of remote sensing vegetation indices. We further examined heterogeneity, spatiotemporal trade-offs, and dominant drivers using the probability density bin, spatial overlay, an XGBoost-SHAP model, and piecewise regression. First, pronounced spatial heterogeneity emerged: resistance and resilience were highest in the semi-humid/humid and plateau zones (overlapping in the western high mountains) but lowest in humid and mid-subtropical zones, whereas resilience increased with energy availability from warm temperate to mid-subtropical zones. Second, vegetation-type contrasts were also evident: coniferous forests ranked top in both metrics, broadleaf forests showed high resistance but low resilience, grasslands the reverse, and natural forests consistently outperformed planted forests. Third, a spatiotemporal trade-off existed. Spatially, they were significantly negatively correlated, with “high-low” and “low-high” as dominant patterns, enabling the delineation of four management zones via spatial overlay. Temporally, resistance increased while resilience declined, confirming the dynamic nature of this trade-off. Finally, Elevation and vegetation cover co-dominated both components with positive effects, and hydrothermal anomalies imposed nonlinear thresholds. Our findings from this climate-sensitive region provide a valuable framework for understanding and managing ecosystem stability in transitional zones globally.