Reducing cropland requirement by optimizing provincial grain trade patterns in China

Optimizing grain trade patterns to conserve cropland is crucial for enhancing the “internal circulation” of grain production. This study characterized the current supply and demand dynamics for China’s three primary staple crops—wheat, maize, and rice—encompassing demand for human consumption, animal feed, and food loss and waste across the entire food supply chain. We developed a linear programming-based grain trade simulation and optimization model to determine the interprovincial trade patterns of these three crops and their virtual cropland trade structure, to assess the potential reduction in cropland requirements achieved by optimizing interprovincial grain trade patterns. We found that in profit-driven trade schemes, grain trade largely follows the principle of proximity, and major grain-producing provinces such as Henan, Shandong, and Anhui alleviate cropland resource imbalances to some extent through interprovincial trade. Optimizing trade patterns could reduce national cropland requirements by nearly 15,000 km2. Attention should also be paid to the synergistic benefits of reducing cropland requirements and reducing transport-related carbon emissions. Optimizing the grain trade structure and leveraging the production advantages of major grain-producing regions contribute to reducing cropland requirement, while simultaneously enhancing the role of land resource management in guaranteeing a stable food supply.