Interprovincial disparities and driving mechanisms of wheat cultivation carbon footprint in China from a spatial correlation perspective

As one of the world’s most important staple crops, wheat plays a critical role in global food security, while the carbon emissions associated with its cultivation cannot be overlooked. However, existing studies have paid insufficient attention to the long-term and provincially consistent accounting of wheat cultivation carbon footprints, interprovincial spatial correlation, and the nonlinear responses and potential threshold effects of their driving factors. To address these limitations, this study estimated the provincial carbon footprint of wheat cultivation from 2000 to 2023 using a life cycle assessment (LCA) approach. Kernel density estimation, spatial correlation networks, Moran’s I, and the XGBoost-SHAP model were then employed for further analysis. The results show that: (1) the provincial carbon footprint of wheat cultivation exhibited significant spatial heterogeneity and stage-specific evolutionary characteristics during the study period. High-value areas were persistently concentrated in traditional major wheat-producing regions, such as North China and the Huang-Huai-Hai region, while the number of provinces with low carbon footprints generally increased; however, several major producing provinces continued to maintain relatively high levels. (2) The provincial carbon footprint showed significant positive spatial autocorrelation and formed a spatial correlation network centered on the Beijing-Tianjin-Hebei region, the Huang-Huai-Hai region, and the middle and lower reaches of the Yangtze River, exhibiting a stable and connected “core–periphery” structure. (3) Agricultural mechanization level and Planting structure were the dominant driving factors, with relative contributions of 35.7% and 31.2%, respectively, and both showed pronounced nonlinear and threshold effects. These findings suggest that carbon mitigation in China’s wheat cultivation should balance food security with low-carbon transformation. In particular, efforts should focus on optimizing planting structures and agricultural input patterns in high-footprint major producing areas, while strengthening cross-regional collaborative emission reduction through core provinces in the spatial correlation network, thereby improving resource-use efficiency and promoting low-carbon development in wheat production.