Evaluating the Coupling Adaptability of the Food System in China From an Integrated Food Security Perspective

Against the backdrop of intensifying global challenges—including climate shocks, dietary globalization, and escalating food insecurity affecting hundreds of millions—the sustainable transformation of food system has become a paramount concern for achieving the United Nations Sustainable Development Goals (SDGs). This imperative demands integrated approaches that move beyond siloed analyses to holistically address the complex interactions within food system. The coupling adaptability of the food composite system (FCS)—conceptualized as a complex system integrating population, land, and food subsystems—constitutes the core proposition for achieving synergistic development between SDGs and ecological security. This study aims to systematically diagnose the spatiotemporal evolution and driving mechanisms of China's FCS adaptability from an integrated food security perspective. To solve the spatio‐temporal evolution and driving mechanism of the adaptability of FCS in China, this study combines entropy‐based weighting with multi‐scale spatial statistical models, including spatial variogram, markov chain, and geographic and temporal weighted regression (GTWR), to investigate the spatio‐temporal evolution laws and driving mechanisms of the adaptability of FCS in China from 2010 to 2022. Results are as follows: (1) The adaptability of FCS demonstrates a biphasic “fluctuation‐stabilization to the regional restructuring” trajectory, with overall indices stabilizing. (2) The regional hierarchy shifted from “production and sales balance area > main grain production area > main grain sales area” to “main grain production area > production and sales balance area > main grain sales area”, accompanied by accelerated adaptability degradation in the main grain sales area. (3) Spatial differentiation exhibits “agglomeration intensification‐axial polarization”, with northeast‐southwest axial variation intensity surpassing other orientations by 38.7%. (4) Spatial markov chain analysis revealed a “neighborhood locking” effect, while GTWR modeling identified that adaptability is co‐determined by the rural capital inventory, industrial structure, planting structure, governmental fiscal support, and environmental regulation, with spatiotemporally heterogeneous impacts. This study provides critical insights for formulating spatially differentiated farmland conservation strategies and enhancing food system resilience in functional zones of global grain production.