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

Assessing the capacity conditions that support agricultural responses to climate-related risks is important for strengthening agricultural systems and ensuring food security. Using panel data from 31 Chinese provinces during 2011–2024, this study introduces the WSR methodology and constructs a capacity-oriented ACR index comprising resistance, adaptation, and transformative capacities. It examines the spatio-temporal evolution, spatial effects, convergence, and nonlinear driving mechanisms of the capacity-oriented ACR index. The results show that: (1) China’s capacity-oriented ACR index increased from 0.3318 in 2011 to 0.4525 in 2024, with higher levels in eastern and central China and lower levels in western China. Provinces with higher ACR index scores were concentrated in the Major Grain-Producing Areas (MGPA). (2) Spatial differences in ACR index scores were mainly attributable to grain functional areas, with the largest gap between the MGPA and the Balanced Grain Production and Consumption Areas (BGPCA). (3) ACR index scores exhibited significant spatial dependence, convergence, and positive spillover effects nationally and in most grain functional areas, whereas the Major Grain-Consuming Areas (MGCA) had not formed a stable convergence trend. (4) Multiple factors were nonlinearly associated with ACR index scores, with dominant drivers varying across grain functional areas. These findings support differentiated regional governance and optimized resource allocation. The findings reflect China’s specific institutional context, and the ACR index captures broad capacity conditions supporting agricultural responses to climate-related risks, which may limit generalizability.