Integrating the Socio-economic and Physical Drivers of Land-use Change at Climate-relevant Scales: an Example with Biofuels

Understanding the factors that drive land-use change, and developing better methods for projecting future changes, have become very important in the context of climate change, since land use is both affected by climate and itself is a significant contributor to greenhouse gas emissions. While much work has been done to include global forecasts of natural land cover types such as forests and deserts at high spatial resolutions, much less has been done to incorporate into these forecasts the socioeconomic drivers of land-use change, such as agriculture, forestry, and urbanization on a global scale. We describe here a computational framework that allows for efficiently incorporating feedback between economic activity and anthropogenic land use changes for the purpose of improved global land-use forecasts. The Partial-Equilibrium Economic Landuse (PEEL) model is a versatile high-resolution companion to the CIM-EARTH computable general equilibrium (CGE) global economics framework that generates consistent forecasts of the land-use changes (LUC) that result from changing growing conditions, technology, resource availability, and demands. The high resolution (≈ 10 km) of model elements allows for direct integration of climate and socioeconomic factors at the scale of relevant climate variation without the need for aggregation (and the associated information loss). We illustrate this approach by using it to investigate the implications of an aggressive 1st generation biofuels policy on LUC. We discuss the development of PEEL, its limitations, and future directions, focusing especially on data needs and potential new data sources.