Abstract
A foodshed is a geographic area from which a population derives its food supply, but a method to determine boundaries of foodsheds has not been formalized. Drawing on the food-water energy nexus, we propose a formal network science definition of foodsheds by using data from virtual water flows, i.e. water that is virtually embedded in food. In particular we use spectral graph partitioning for directed graphs. If foodsheds turn out to be geographically compact, it suggests the food system is local and therefore reduces energy and externality costs of food transport. Using our proposed method we compute foodshed boundaries at the global-scale, and at the national-scale in the case of two of the largest agricultural countries: India and the United States. Based on our determination of foodshed boundaries, we are able to better understand commodity flows and whether foodsheds are contiguous and compact, and other factors that impact environmental sustainability. The formal method we propose may be used more broadly to study commodity flows and their impact on environmental sustainability.
Highlights
Economic and environmental historians have traditionally considered the flow of natural resources from hinterland to metropolis (Cronon, 1991), but there is growing specialization, interconnection, and flow among all regions within nations and further among nations of the world
Commensurating food flow data into virtual water flows requires combining a variety of datasets from several different sources, and is an interesting challenge in and of itself, as we describe in the paragraphs
We have put forth a formal data-driven definition of foodsheds from network science and computed foodsheds for India, the United States, and the world
Summary
Economic and environmental historians have traditionally considered the flow of natural resources from hinterland to metropolis (Cronon, 1991), but there is growing specialization, interconnection, and flow among all regions within nations and further among nations of the world. We use spectral graph partitioning for directed networks (Gleich, 2006; Malliaros and Vazirgiannis, 2013) constructed from agricultural trade data as the basis for defining foodsheds. This spectral approach to graph partitioning is chosen since it is natural, in the sense of capturing the costs of physical flows due to intimate connections with metric embedding. On the other hand, using 2007 Commodity Flow Survey data from the U.S Census and virtual water commensuration that follows (Mekonnen and Hoekstra, 2011; Mubako, 2011; Dang et al, 2015), we find foodsheds that are not geographically contiguous.
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