Global-scale modelling of future changes in sown areas of major crops

Abstract

Land use and its dynamics have attracted much attention from researchers due to their ecological and socio-economic implications. Many studies have used a modelling approach to evaluate land use changes and their effects. Most of these models were designed for the analysis of past, present and future cropland changes at different scales and few have been designed for the study of dynamic changes in sown areas of crops within croplands. This paper presents an integrated modelling approach to simulate dynamically the changes in sown areas for the world's major crops at a global scale. This approach was based on three core models. A crop choice decision model, the Multinomial Logit model, was used to track and simulate the crop choice decisions made by individual farmers. A crop yield model, the GIS-based Environmental Policy Integrated Climate (EPIC) model, was utilized to estimate yields of different crop types under a given biophysical and management environment, while a crop price model, the International Food Policy and Agricultural Simulation (IFPSIM) model, was employed to assess the price of crops on the international market. Through data exchange, the crop choice decision model was linked with the crop yield and crop price models to allow the study of the dynamic feedback loop between changes in agricultural land use and biophysical and socio-economic driving factors. Sensitivity analysis and empirical validation for the model were conducted after the construction of the model. The model validation indicated the reliability of the model for addressing the complexity of current agricultural land use changes and its capacity for investigating long-term scenarios in the future. Finally, the model was used to simulate future scenarios over a time frame of 30 years with five-year increments, beginning from the year 2000. The simulation results provided insights into potential global cropping patterns, variation in rates and trajectory of changes in sown areas for major crops over the test period. These results can improve understanding of projected land use changes and explain their causes, locations and consequences, and provide support for land use planning and policy making.