Spatiotemporal Evolution and Driving Mechanisms of Climate Resilience of Grain Production in China: Insights from Super-Efficiency SBM-DEA and XGBoost-SHAP Models

Frequent global extreme climate events exert persistent shocks to grain production systems. Evaluating and improving the climate resilience of grain production (CRFP) has become a critical issue for safeguarding national food security and advancing the sustainable transformation of agricultural systems aligned with Sustainable Development Goals (SDGs), particularly SDG 2 (Zero Hunger). Based on panel data of 30 provincial-level administrative regions in China spanning 2011 to 2024, this study employs a super-efficiency SBM-DEA model that accounts for undesirable outputs to measure CRFP. An XGBoost-SHAP machine-learning model is further applied to unpack the contribution ranking, nonlinear threshold characteristics, and multi-factor interactive effects of various driving factors. The results reveal the following: (1) Nationwide, CRFP shows an overall pattern of “rising first and then declining with stabilizing fluctuations”. Spatially, high-resilience zones gradually agglomerate in eastern coastal areas and the North China Plain from scattered distribution, presenting a differentiation pattern of “rising in the east and stagnating in the west”. Inter-regional differences constitute the principal source of overall national disparities in CRFP, and spatial stratification is becoming increasingly prominent. (2) The climate risk index is the primary driving factor of CRFP. Most driving factors exhibit widespread nonlinear threshold effects, and their impacts display notable regional heterogeneity. (3) Digital inclusive finance and agricultural technology yield the strongest positive synergistic benefits. In contrast, the interactions between climate risk and relief amplitude, as well as the urban–rural income ratio, further amplify the adverse impacts on CRFP. Accordingly, this study proposes adopting region-specific policy measures, improving policy targeting precision, and establishing multi-factor synergistic policy portfolios. These measures aim to strengthen the shock-resistance and recovery capacity of grain production systems to achieve long-term sustainable grain supply, and provide empirical evidence and decision-making support for ensuring national food security amid ongoing climate change.