Assessing the Alignment Between Naturally Adaptive Grain Crop Planting Patterns and Staple Food Security in China

Climate change and socio-economic transformation increasingly challenge the stability of China's food supply. This study aims to optimize grain crop layouts by integrating natural suitability and nutritional supply within a unified analytical framework. Using the MaxEnt model incorporating bioclimatic, topographic, and soil variables, we simulated the natural suitability of major grain crops and compared it with actual planting patterns based on the SPAM dataset. Results revealed substantial spatial discrepancies between actual and suitable distributions, with national planting diversity index increasing by 26.42% (from 0.53 to 0.67) under suitable conditions. Wheat and maize are most suited to northern China, rice and tuber crops to southern regions, while soybean performs optimally in the northeast. Nutrient supply potential also improved substantially under the suitable scenario, with energy, protein, fat, and carbohydrate increasing by 56.9 × 10⁸ KJ, 77.2 × 10⁶ g, 23.3 × 10⁶ g, and 48.6 × 10⁶ g per million people, respectively. Among alternative structures, maize-soybean and maize-based planting structures better aligned with both natural adaptability and nutritional balance (e.g., in Inner Mongolia and Heilongjiang), whereas rice-based structure showed weaker correspondence (e.g., in Shanghai). These findings demonstrate that naturally adaptive optimization can enhance both environmental compatibility and nutritional adequacy, providing scientific guidance for developing climate-resilient and nutrition-oriented crop layout strategies in China.