Location: Nutrient Data Laboratory
Project Number: 8040-52000-064-63-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 1, 2018
End Date: Aug 31, 2021
Rapid changes in population, income, urbanization, technology, and natural resources are driving significant changes in production and consumption of agricultural commodities. There is increasing recognition of the links between changing diets and impacts on natural resources and human well-being, but most analyses maintain a narrow focus on singular topics and simplified representations of the future, which limit the broad applicability of these studies. Embedding the analysis of the future of food systems and its interaction with the natural environment and human wellbeing in a dynamic and integrated forward-looking analysis enables a more nuanced and thorough assessment of where policy efforts need to be focused. The objective will be to explore alternative scenarios of dietary change over the coming decades at national, regional, and global levels, analyzing (1) how diets are affected by changes in the key drivers noted above, (2) what implications these changes have for natural resources and human health and wellbeing, and (3) how policy measures may help shape those outcomes in desired directions.
International Food Policy Research Institute (IFPRI) International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT), which brings together climate, water, crop, and economic modeling tools in an integrated modeling framework (Robinson et al. (2015) as the basis for analysis. The IMPACT economic model simulates national and global markets of agricultural production, demand, and trade associated with more than 60 agricultural commodities across 158 countries and regions around the globe. This cooperative research agreement will target specific extensions to recent developments achieved with IMPACT in tracking nutrient availability, agricultural investments, environmental impacts, and human wellbeing (Beach et al. (in preparation), Hasegawa et al. (2018), Nelson et al. (in preparation), Rosegrant et al. (2017), Springmann et al. (2016)).