Large-Scale Modelling of Global Food Security and Adaptation under Crop Yield Uncertainty

Concerns about future food security in the face of volatile and potentially lower yields due to climate change have been at the heart of recent discussions on adaptation strategies in the agricultural sector. While there are a variety of studies trying to quantify the impact of climate change on yields, some of that literature also acknowledges the fact that these estimates are subject to substantial uncertainty. The question arises how such uncertainty will affect decision-making if ensuring food security is an explicit objective. Also, it will be important to establish, which options for adaptation are most promising in the face of volatile yields. The analysis is carried out using a stochastic version of the Global Biosphere Management Model (GLOBIOM) model, which is a global recursive dynamic partial equilibrium bottom-up model integrating the agricultural, bio-energy and forestry sectors with the aim to give policy advice on global issues concerning land use competition between the major land-based production sectors. The source of stochasticity is the interannual crop yield variability, making it more risky to rely on average yields and thus requiring stochastic optimization techniques. The results indicate that food security requires overproduction to meet minimum food supply constraints also in scenarios of negative yield shocks, where the additional land needed is sourced from forests and other natural land. Trade liberalization and enhanced irrigation both appear to be promising food supply stabilization, and hence land saving, mechanisms in the face of missing storage.