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Global food trade is crucial for food security and availability. Trade is typically optimized to promote efficiency, whereas resilience is increasingly being recognized as another important objective. However, it is not clear if prioritizing resilience comes at the expense of efficiency or if the two objectives can be promoted simultaneously. We develop a complex network framework to assess the relationship between efficiency and resilience of food trade for the last half century. There is a competitive relationship between efficiency and resilience when only network topology is considered. However, a cooperative relationship between efficiency and resilience exists when the intensity of trade connections is accounted for. Policy makers can use this framework to evaluate the relationship between efficiency and resilience in critical supply chains.

Food supply chains are essential for distributing goods from production to consumption points. These complex supply chains are important for food security and availability. Recent research has developed novel methods to estimate food flows with high spatial resolution, but we do not currently understand how fine-grained food supply chains vary in time. In this study, we develop a time-series analysis of food flows between the counties in the United States. We use the Food Flow Model to estimate food flows [kg] for all county pairs across all food commodity groups (70 million links) for the years 2007, 2012, and 2017. We then determine the core nodes to the US food flow network by a multi-criteria decision analysis technique. Our estimates of county-to-county food flows are freely available with this paper and could be useful for future research, policy, and decision-making.

The food system is an important contributor to carbon dioxide emissions. The refrigerated food supply chain is an energy-intensive, nutritious, and high-value part of the food system, making it particularly important to consider. In this study, we develop a novel model of cold chain food flows between counties in the United States. Specifically, we estimate the truck transport via roadways of `meat' and `prepared foodstuffs' for the year 2017. We use the roadway travel distance in our model framework rather than the great-circle distance between two locations to improve the estimate of the long-haul freight with temperature controlled system. This enables us to more accurately calculate the truck fuel consumption and CO2 emissions related to cold chain food transport. We find that the cold chain transport of `meat' emitted 8.4x10^6 T CO2 yr-1 and `prepared foodstuffs' emitted 14.5x10^6 T CO2 yr-1, which is in line with other studies. `Meat' has a longer average refrigerated transport distance, resulting in higher transport CO2 emissions per kg than processed foodstuffs. We also find that CO2 emissions from cold chain food transport are not projected to significantly increase under the temperatures projected to occur with climate change in 2045. These county-level cold chain food flows could be used to inform infrastructure investment, supply chain decision making, and environmental footprint studies.