Simulation of global crop production with the ecosystem model DayCent
Modelling plant growth has a tradition starting long before today's computer models. Classical works such as by Sprengel (1828), Liebig (1840) or Mitscherlich (1909) are still influential. Their core questions – what is limiting crop growth and what is the optimal management? – are still being addressed by modern crop models. However, the scope of crop modelling has expanded. An important new motivation for crop modelling are questions regarding the impact of climate change and increasing human population on future food security. Crop modelling has thus been applied to assess the availability of additional land for agriculture, to investigate the impact of climate change on future land use or on future economic welfare.
Agriculture has become a key element within the earth system as it changes global biogeochemical and water cycles, while global environmental change affects land productivity and thus future land-use decisions. To address these issues and their complex interdependency in a consistent modelling approach we adapted the agro-ecosystem model DayCent for the simulation of major crops at the global scale. Based on a global compilation of environmental and management data and an algorithm to calculate global planting dates, DayCent was parameterised and calibrated to simulate global yield levels for wheat, maize, rice and soybeans. Simulation results show that the DayCent model is able to reproduce the major effects of climate, soil and management on crop production. Average simulated crop yield per country agree well with agricultural statistics (Modelling efficiency is about 0.66 for wheat, rice and maize, and 0.32 for soybean) and spatial patterns of yields generally correspond to observed crop distributions and sub-national census data.
|Author(s)||Stehfest E ; Heistermann M ; Priess JA ; Ojima DS ; Alcamo J|
|Publication||Ecol Model 2007; 209(2-4):203-19|