Measuring the Level and Potential of China's Food Security Resilience in the Context of Climate Change
Abstract
Intensifying global climate change poses a severe threat to agricultural production, and strengthening China's food security resilience is therefore of great practical significance for safeguarding food security in China. This study constructs an evaluation system comprising 17 indicators across four dimensions-supply availability, consumption access, food utilization, and system stability-and applies the entropy-TOPSIS method, the Dagum Gini coefficient, kernel density estimation, Markov chains, an obstacle degree model, and the GM(1,1) grey prediction model to measure the level and potential of food security resilience across 31 provinces in China. The results show that China's food security resilience exhibits a steady upward trend, with the composite score rising from 0.2240 in 2010 to 0.3504 in 2024. Regional disparities are dominated by inter-group differences, whose average contribution rate reaches 70.13%, and the overall Gini coefficient declines gradually. Resilience shows a significant positive spatial autocorrelation throughout, with the global Moran's I remaining significant at the 1% level in all years. Transitions among resilience levels are characterized by "club convergence", with the high-level club being the most stable, and neighborhood states significantly condition local transitions. The grain self-sufficiency rate, rural broadband access per capita, and the soil erosion control rate are the leading obstacle factors; at the dimension level, the obstacle…
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