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  1. The demand for ‘local food’ by U.S. consumers has grown markedly over the last several decades, accompanied by confusion over how to define local food. Is ‘local’ food defined by the location of the farm, food processing factory, distribution warehouse, or all three? Is ‘local’ food defined by geographic, political, or biophysical boundaries? Is ‘local’ solely farm-to-table or can it include factories? This study evaluates food commodity flow ‘localness’ using jurisdictional boundaries and physical distance to investigate the potential for food system transformation and the tradeoffs inherent to ‘localizing’ food production. We take a supply chain approach by making data-driven distinctions between farm-based flows of food and industrial, energy and nonfood (IENF) crops, and manufacturing/distribution flows of food and agriculturally-derived industrial inputs. We analyze the diversity, distance (a proxy for environmental impact), political boundaries, population, weight, and price (net selling value) of food commodity flows. The diversity of a community's food supply has an optimal range of zero to four-hundred miles. We find tradeoffs between food system diversity and local food sourcing, sustainability, and self-sufficiency. As communities look to improve food system resilience, they will need to balance food-miles and the other values associated with local food. 
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  2. Abstract

    Virtual water flows are used to map the indirect water consumption connections implied by the supply chain of a city, region, or country. This information can be used to manage supply chains to achieve environmental policy objectives and mitigate environmental risks to critical supply chains. A limitation of prior work is that these flows are typically analyzed using monolayer networks, which ignores crucial intersectoral or interlayer couplings. Here, we use a multilayer network to account for such couplings when analyzing blue virtual water flows in the United States. Our multilayer network consists of 115 different regions (nodes), covering the entire conterminous United States; 41 coupled economic sectors (layers); and ∼2 × 107possible links. To analyze the multilayer network, we focus on three fundamental network properties: topological connectivity, mesoscale structure, and node centrality. The network has a high connectivity, with each node being on average connected to roughly 2/3 of the network's nodes. Interlayer flows are a major driver of connectivity, representing ∼54% of all the network's connections. Five different groups of tightly connected nodes (communities) characterize the network. Each community represents a preferred spatial mode of long‐range virtual water interaction within the United States. We find that large (populous) cities have a stronger influence than small ones on network functioning because they attract and recirculate more virtual water through their supply chains. Our results also highlight differences between the multilayer and monolayer virtual water network, which overall show that the former provides a more realistic representation of virtual water flows.

     
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  3. Abstract

    Many research and monitoring networks in recent decades have provided publicly available data documenting environmental and ecological change, but little is known about the status of efforts to synthesize this information across networks. We convened a working group to assess ongoing and potential cross‐network synthesis research and outline opportunities and challenges for the future, focusing on the US‐based research network (the US Long‐Term Ecological Research network, LTER) and monitoring network (the National Ecological Observatory Network, NEON). LTER‐NEON cross‐network research synergies arise from the potentials for LTER measurements, experiments, models, and observational studies to provide context and mechanisms for interpreting NEON data, and for NEON measurements to provide standardization and broad scale coverage that complement LTER studies. Initial cross‐network syntheses at co‐located sites in the LTER and NEON networks are addressing six broad topics: how long‐term vegetation change influences C fluxes; how detailed remotely sensed data reveal vegetation structure and function; aquatic‐terrestrial connections of nutrient cycling; ecosystem response to soil biogeochemistry and microbial processes; population and species responses to environmental change; and disturbance, stability and resilience. This initial study offers exciting potentials for expanded cross‐network syntheses involving multiple long‐term ecosystem processes at regional or continental scales. These potential syntheses could provide a pathway for the broader scientific community, beyond LTER and NEON, to engage in cross‐network science. These examples also apply to many other research and monitoring networks in the US and globally, and can guide scientists and research administrators in promoting broad‐scale research that supports resource management and environmental policy.

     
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