Xiaowen Lin, Qian Dang, and Megan Konar (2014). “A Network Analysis of Food Flows within the United States of America.” Environmental Science & Technology 48(10), 5439-5447. DOI: 10.1021/es500471d.
Abstract: The world food system is globalized and interconnected, in which trade plays an increasingly important role in facilitating food availability. We present a novel application of network analysis to domestic food flows within the USA, a country with global importance as a major agricultural producer and trade power. We find normal node degree distributions and Weibull node strength and betweenness centrality distributions. An unassortative network structure with high clustering coefficients exists. These network properties indicate that the USA food flow network is highly social and well-mixed. However, a power law relationship between node betweenness centrality and node degree indicates potential network vulnerability to the disturbance of key nodes. We perform an equality analysis which serves as a benchmark for global food trade, where the Gini coefficient = 0.579, Lorenz asymmetry coefficient = 0.966, and Hoover index = 0.442. These findings shed insight into trade network scaling and proxy free trade and equitable network architectures.