This project supports the development of an interdisciplinary modeling system that is designed to answer three questions regarding the effects of climate changes on US agriculture: (1) how do changes in the climate affect production; (2) what options are available to mitigate the effects of climate changes; and (3) what are the relative cost-benefit ratios of strategies for adapting to or mitigating the effects of climate change. A new model is needed because existing models, often guided by a single disciplinary perspective, ignore the spatial heterogeneity of forecasts generated by general circulation models, ignore the simultaneous effects of the physical, economic, policy, and demographic environment on yield, and ignore the effects of climate change on planting decisions. This research alleviates these limits by using artificial neural networks to disaggregate spatially the forecasts of climate generated by general circulation models and by estimating new models that integrate the physical, economic, policy, and demographic determinants of yield and planting decisions. In addition to model validation, the research will include scenario analysis to explore climate change implications for uncertainty, planning, and policy. This project is supported under the Methods and Models for Integrated Assessment funding opportunity.
