Global results of the historical validation experiment (1961–2006)
Figure 2. Global results of the historical validation experiment (1961–2006). The bars show the per cent changes in (from left to right) global crop production, yield, land use and price computed from actual data (dark blue bar) and from the simulation results (light green bar). The historical experiment is conducted using the SIMPLE model given exogenous historical growth in population, per capita income and total factor productivity growth in agriculture after calibrating the model over the 2001–2006 period.
Global agricultural models are becoming indispensable in the debate over climate change impacts and mitigation policies. Therefore, it is becoming increasingly important to validate these models and identify critical areas for improvement. In this letter, we illustrate both the opportunities and the challenges in undertaking such model validation, using the SIMPLE model of global agriculture. We look back at the long run historical period 1961–2006 and, using a few key historical drivers—population, incomes and total factor productivity—we find that SIMPLE is able to accurately reproduce historical changes in cropland use, crop price, crop production and average crop yields at the global scale. Equally important is our investigation into how the specific assumptions embedded in many agricultural models will likely influence these results. We find that those global models which are largely biophysical—thereby ignoring the price responsiveness of demand and supply—are likely to understate changes in crop production, while failing to capture the changes in cropland use and crop price. Likewise, global models which incorporate economic responses, but do so based on limited time series estimates of these responses, are likely to understate land use change and overstate price changes.