Spatial Patterns and Drivers of China’s Agricultural Ecological Efficiency: A Super-Efficiency EBM–GeoDetector Approach

Agricultural practices significantly impact environmental sustainability, making the enhancement of Agricultural Ecological Efficiency (AEE) crucial for China’s sustainable agricultural development. However, the spatial-temporal evolution patterns and underlying driving forces of AEE remain insufficiently understood in the context of China’s rapid agricultural transformation. To address this research gap, we analyzed AEE across 30 Chinese provinces from 2000 to 2021, identifying spatial patterns and key influencing factors. Employing a Super-Efficiency EBM model with undesirable outputs, we calculated provincial AEE scores. Spatial analysis tools, including Moran’s I, Dagum Gini decomposition, and kernel density estimation, were applied to explore regional differences. We also utilized Geo-detector to quantify driving factors and their interactions. The results demonstrated a clear west-to-east and south-to-north gradient of declining AEE, with western provinces exhibiting higher efficiency levels. Despite narrowing disparities within the eastern and western regions, central regions displayed increasing intra-regional differences. Geo-detector analysis further highlighted significant interactive effects among factors such as urbanization, governmental agricultural support, education levels, and precipitation, enhancing the explanatory power of AEE spatial variations. These findings support region-specific policies for optimizing agricultural structures and resource efficiency, facilitating China’s ecological transition in agriculture.