Study on the Crop Suitability and Planting Structure Optimization in Typical Grain Production Areas under the Influence of Human Activities and Climate Change: A Case Study of the Naoli River Basin in Northeast China

Abstract

Optimizing crop planting structures under the influence of climate change and human activities is crucial for sustainable food production and global food security. Taking the Naoli River Basin in Northeast China as a case area, a machine learning model based on maximum entropy was used to explore the suitability distribution of crops under the influence of both environmental factors and human activities. The optimized planting structure strategies were tested in combination with future climate change. The results show that considering human activities can more accurately simulate crop suitability than considering only natural environmental factors. The suitable planting areas for maize, rice, and soybeans are 18,553.54 km2, 10,335.98 km2, and 5844.80 km2, respectively. Highly adapted areas for major crops are concentrated in the plain areas of the middle reaches of the river basin, rather than in populated areas, and there are overlaps among the suitable planting areas for each crop. The optimal crop distribution for the planting structure is to plant rice in the hydrophilic areas of the plain hinterland, soybeans in the plain hinterland farther from the water source, and corn in the peripheral plains and gently sloping mountainous areas. Human activities exerted a strong influence on the potential scatter of soybeans, while climate change had the most significant implications for maize. Future climate change may reduce the area of suitable crop zones, posing challenges to regional food production. It is necessary to reflect on how to rationally balance soil and water resources, as well as how to cope with climate change in the future.