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1. The FEWSION for Community Resilience (F4R) Process: Building Local Technical and Social Capacity for Critical Supply Chain Resilience

   https://doi.org/10.3389/fenvs.2021.601220  

   Ryan, Sean M. ; Roberts, Elisabeth ; Hibbett, Emma ; Bloom, Nena ; Haden, Carol ; Rushforth, Richard R. ; Pfeiffer, Kyle ; Ruddell, Benjamin L. ( March 2021 , Frontiers in Environmental Science)

   null (Ed.)

   Local business leaders, policy makers, elected officials, city planners, emergency managers, and private citizens are responsible for, and deeply affected by, the performance of critical supply chains and related infrastructures. At the center of critical supply chains is the food-energy-water nexus (FEW); a nexus that is key to a community’s wellbeing, resilience, and sustainability. In the 21st century, managing a local FEW nexus requires accurate data describing the function and structure of a community’s supply chains. However, data is not enough; we need data-informed conversation and technical and social capacity building among local stakeholders to utilize the data effectively. There are some resources available at the mesoscale and for food, energy, or water, but many communities lack the data and tools needed to understand connections and bridge the gaps between these scales and systems. As a result, we currently lack the capacity to manage these systems in small and medium sized communities where the vast majority of people, decisions, and problems reside. This study develops and validates a participatory citizen science process for FEW nexus capacity building and data-driven problem solving in small communities at the grassroots level. The FEWSION for Community Resilience (F4R) process applies a Public Participation in Scientific Research (PPSR) framework to map supply chain data for a community’s FEW nexus, to identify the social network that manages the nexus, and then to generate a data-informed conversation among stakeholders. F4R was piloted and co-developed with participants over a 2-year study, using a design-based research process to make evidence-based adjustments as needed. Results show that the F4R model was successful at improving volunteers’ awareness about nexus and supply chain issues, at creating a network of connections and communication with stakeholders across state, regional, and local organizations, and in facilitating data-informed discussion about improvements to the system. In this paper we describe the design and implementation of F4R and discuss four recommendations for the successful application of the F4R model in other communities: 1) embed opportunities for co-created PPSR, 2) build social capital, 3) integrate active learning strategies with user-friendly digital tools, and 4) adopt existing materials and structure. 

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2. A balancing act: the interplay of food supply chain resilience and environmental sustainability in American cities

   https://doi.org/10.1088/1748-9326/ad0608  

   Gomez, Michael ; Grady, Caitlin ( November 2023 , Environmental Research Letters)

   Global food systems must be a part of strategies for greenhouse gas (GHG) mitigation, optimal water use, and nitrogen pollution reduction. Insights from research in these areas can inform policies to build sustainable food systems yet limited work has been done to build understanding around whether or not sustainability efforts compete with supply chain resilience. This study explores the interplay between food supply resilience and environmental impacts in US cities, within the context of global food systems’ contributions to GHG emissions, water use, and nitrogen pollution. Utilizing county-level agricultural data, we assess the water use, GHG emissions, and nitrogen losses of urban food systems across the US, and juxtapose these against food supply resilience, represented by supply chain diversity. Our results highlight that supply chain resilience and sustainability can simultaneously exist and are not necessarily in competition with each other. We also found a significant per capita footprint in the environmental domains across Southern cities, specifically those along the Gulf Coast and southern Great Plains. Food supply chain resilience scores ranged from 0.18 to 0.69, with lower scores in the southwest and Great Plains, while northeastern and Midwestern regions demonstrated higher resilience. We found several cities with high supply chain resilience and moderate or low environmental impacts as well as areas with high impacts and low resilience. This study provides insights into potential trade-offs and opportunities for creating sustainable urban food systems in the US, underscoring the need for strategies that consider both resilience and environmental implications.

    

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3. Applying the framework to study climate-induced extremes on food, energy, and water systems (C-FEWS): The role of engineered and natural infrastructures, technology, and environmental management in the United States Northeast and Midwest

   https://doi.org/10.3389/fenvs.2023.1070144  

   Vörösmarty, Charles J. ; Melillo, Jerry M. ; Wuebbles, Donald J. ; Jain, Atul K. ; Ando, Amy W. ; Chen, Mengye ; Tuler, Seth ; Smith, Richard ; Kicklighter, David ; Corsi, Fabio ; et al ( March 2023 , Frontiers in Environmental Science)

   Change to global climate, including both its progressive character and episodic extremes, constitutes a critical societal challenge. We apply here a framework to analyze Climate-induced Extremes on the Food, Energy, Water System Nexus (C-FEWS), with particular emphasis on the roles and sensitivities of traditionally-engineered (TEI) and nature-based (NBI) infrastructures. The rationale and technical specifications for the overall C-FEWS framework, its component models and supporting datasets are detailed in an accompanying paper (Vörösmarty et al., this issue). We report here on initial results produced by applying this framework in two important macro-regions of the United States (Northeast, NE; Midwest, MW), where major decisions affecting global food production, biofuels, energy security and pollution abatement require critical scientific support. We present the essential FEWS-related hypotheses that organize our work with an overview of the methodologies and experimental designs applied. We report on initial C-FEWS framework results using five emblematic studies that highlight how various combinations of climate sensitivities, TEI-NBI deployments, technology, and environmental management have determined regional FEWS performance over a historical time period (1980–2019). Despite their relative simplicity, these initial scenario experiments yielded important insights. We found that FEWS performance was impacted by climate stress, but the sensitivity was strongly modified by technology choices applied to both ecosystems (e.g., cropland production using new cultivars) and engineered systems (e.g., thermoelectricity from different fuels and cooling types). We tabulated strong legacy effects stemming from decisions on managing NBI (e.g., multi-decade land conversions that limit long-term carbon sequestration). The framework also enabled us to reveal how broad-scale policies aimed at a particular net benefit can result in unintended and potentially negative consequences. For example, tradeoff modeling experiments identified the regional importance of TEI in the form wastewater treatment and NBI via aquatic self-purification. This finding, in turn, could be used to guide potential investments in point and/or non-point source water pollution control. Another example used a reduced complexity model to demonstrate a FEWS tradeoff in the context of water supply, electricity production, and thermal pollution. Such results demonstrated the importance of TEI and NBI in jointly determining historical FEWS performance, their vulnerabilities, and their resilience to extreme climate events. These infrastructures, plus technology and environmental management, constitute the “policy levers” which can actively be engaged to mitigate the challenge of contemporary and future climate change. 

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4. Spatially detailed agricultural and food trade between China and the United States

   https://doi.org/10.1088/1748-9326/ace72c  

   Pandit, Akshay ; Karakoc, Deniz Berfin ; Konar, Megan ( August 2023 , Environmental Research Letters)

   The United States and China are key nations in global agricultural and food trade. They share a complex bilateral agri-food trade network in which disruptions could have a global ripple effect. Yet, we do not understand the spatially resolved connections in the bilateral US–China agri-food trade. In this study, we estimate the bilateral agri-food trade between Chinese provinces and U.S. states and counties. First, we estimate bilateral imports and exports of agri-food commodities for provinces and states. Second, we model link-level connections between provinces and states/counties. To do this, we develop a novel algorithm that integrates a variety of national and international databases for the year 2017, including trade data from the US Census Bureau, the US Freight Analysis Framework database, and Multi-Regional Input-Output tables for China. We then adapt the food flow model for inter-county agri-food movements within the US to estimate bilateral trade through port counties. We estimate 2,954 and 162,922 link-level connections at the state-province and county-province resolution, respectively, and identify core nodes in the bilateral agri-food trade network. Our results provide a spatially detailed mapping of the US–China bilateral agri-food trade, which may enable future research and inform decision-makers.

    

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5. A stochastic programming approach to enhance the resilience of infrastructure under weather‐related risk

   https://doi.org/10.1111/mice.12843  

   Zhang, Ning ; Alipour, Alice ( May 2022 , Computer-Aided Civil and Infrastructure Engineering)

   The presented methodology results in an optimal portfolio of resilience‐oriented resource allocation under weather‐related risks. The pre‐event mitigations improve the capacity of the transportation system to absorb shocks from future natural hazards, contributing to risk reduction. The post‐event recovery planning results in enhancing the system's ability to bounce back rapidly, promoting network resilience. Considering the complex nature of the problem due to uncertainty of hazards, and the impact of the pre‐event decisions on post‐event planning, this study formulates a nonlinear two‐stage stochastic programming (NTSSP) model, with the objective of minimizing the direct construction investment and indirect costs in both pre‐event mitigation and post‐event recovery stages. In the model, the first stage prioritizes a bridge group that will be retrofitted or repaired to improve the system's robustness and redundancy. The second stage elaborates the uncertain occurrence of a type of natural hazard with any potential intensity at any possible network location. The damaged state of the network is dependent on decisions made on first‐stage mitigation efforts. While there has been research addressing the optimization of pre‐event or post‐event efforts, the number of studies addressing two stages in the same framework is limited. Even such studies are limited in their application due to the consideration of small networks with a limited number of assets. The NTSSP model addresses this gap and builds a large‐scale data‐driven simulation environment. To effectively solve the NTSSP model, a hybrid heuristic method of evolution strategy with high‐performance parallel computing is applied, through which the evolutionary process is accelerated, and the computing time is reduced as a result. The NTSSP model is implemented in a test‐bed transportation network in Iowa under flood hazards. The results show that the NTSSP model balances the economy and efficiency on risk mitigation within the budgetary investment while constantly providing a resilient system during the full two‐stage course.

    

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