Spatiotemporal Evolution Characteristics and Nonlinear Driving Mechanisms of Agricultural Climate Resilience in China

Summary

This panel study of 31 Chinese provinces (2011–2024) introduces a capacity-oriented agricultural climate resilience index integrating resistance, adaptation, and transformative dimensions using WSR methodology. The index increased significantly over the decade, with pronounced east–west gradients and concentration in Major Grain-Producing Areas. Spatial analysis revealed significant spillover effects and convergence trends nationally, though grain functional area classifications emerged as dominant heterogeneous drivers, suggesting that effective climate resilience governance requires regionally differentiated strategies aligned with China's institutional context.

Regional applicability

The study is specific to China's grain production system, spatial governance structure, and institutional context, limiting direct transferability to United Kingdom farming. However, the methodological framework for assessing multi-dimensional climate resilience capacity (resistance, adaptation, transformation) and the spatial econometric approach to identify regional heterogeneity could inform UK agricultural resilience assessment, particularly in devolved agricultural policy frameworks.

Key measures

Agricultural climate resilience (ACR) index comprising resistance, adaptation, and transformative capacities; spatial autocorrelation; convergence analysis; nonlinear relationships with driving factors

Outcomes reported

The study constructed and evaluated a capacity-oriented agricultural climate resilience (ACR) index across 31 Chinese provinces from 2011–2024, measuring spatio-temporal evolution, spatial effects, convergence patterns, and nonlinear driving mechanisms. Key findings showed ACR index increase from 0.3318 to 0.4525 over the period, with marked regional disparities and differential convergence patterns across grain functional areas.

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