Abstract
Food security depends on food production exceeding consumption, which are influenced, respectively, by climate change and socio-economic development. We adopted a hybrid approach for predicting features of future food security in China. Specifically, complex interactions in food security were examined using copula-based Markov Chain Monte Carlo simulation. Crop yields per unit area were simulated with a denitrification-decomposition (DNDC) model under four climate-change scenarios. A high shortage risk for soybean and lower shortage risks for maize and wheat were predicted. Compared with the extent of food security in China under other dietary patterns, the performance advantage of the Chinese dietary pattern was identified, which could mitigate crop shortage risks. The shortage risk of core crops would not be influenced greatly under the different dietary patterns. In the planning years 2025 and 2030, the shortage risks for soybean and rice would be pronounced (i.e., more than 50%), whereas those for maize and wheat would not be prominent.