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Flows in Agro-food Networks (FAN): An agent-based model to simulate local agricultural material flows

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  • Fernandez-Mena, Hugo
  • Gaudou, Benoit
  • Pellerin, Sylvain
  • MacDonald, Graham K.
  • Nesme, Thomas

Abstract

Agro-food networks are characterized by complex material exchanges among farms, processors, consumers, and waste managers involved in fertilization, food, feed and bioenergy production. Better coordination of material exchanges at the local scale can facilitate more efficient resource use. Here, we present a new agent-based model, “Flows in Agro-food Networks” (FAN), which simulates the processing and exchange of fertilizers, feed, food and wastes among farms and multiple upstream or downstream partners (feed and fertilizer suppliers, food industries, waste processors, and anaerobic digesters) in small farming regions. FAN includes a series of environmental indicators that can be used to assess alternative scenarios in terms of ecosystem services, nutrient cycling, and resource autonomy. We use a French case study to demonstrate FAN’s dynamics and to explore the sensitivity of key parameters. We show a strong influence of spatial distance between agents, their disposition to exchange, and their preference for specific materials on local agro-food network simulations. FAN is powerful theoretical tool to explore and assess opportunities for a circular economy in small farming regions and to unravel interactions between recycling, environmental performance and food production.

Suggested Citation

  • Fernandez-Mena, Hugo & Gaudou, Benoit & Pellerin, Sylvain & MacDonald, Graham K. & Nesme, Thomas, 2020. "Flows in Agro-food Networks (FAN): An agent-based model to simulate local agricultural material flows," Agricultural Systems, Elsevier, vol. 180(C).
    • Handle: RePEc:eee:agisys:v:180:y:2020:i:c:s0308521x19301969
    DOI: 10.1016/j.agsy.2019.102718
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    2. Catarino, Rui & Therond, Olivier & Berthomier, Jérémy & Miara, Maurice & Mérot, Emmanuel & Misslin, Renaud & Vanhove, Paul & Villerd, Jean & Angevin, Frédérique, 2021. "Fostering local crop-livestock integration via legume exchanges using an innovative integrated assessment and modelling approach based on the MAELIA platform," Agricultural Systems, Elsevier, vol. 189(C).
    3. Melissa Parks, 2022. "Exploring the influence of social and informational networks on small farmers’ responses to climate change in Oregon," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 39(4), pages 1407-1419, December.
    4. Nicholas R. Magliocca, 2020. "Agent-Based Modeling for Integrating Human Behavior into the Food–Energy–Water Nexus," Land, MDPI, vol. 9(12), pages 1-25, December.
    5. Pinsard, Corentin & Martin, Sophie & Léger, François & Accatino, Francesco, 2021. "Robustness to import declines of three types of European farming systems assessed with a dynamic nitrogen flow model," Agricultural Systems, Elsevier, vol. 193(C).
    6. Rahman, Md Mamunur & Nguyen, Ruby & Lu, Liang, 2022. "Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach," Agricultural Systems, Elsevier, vol. 201(C).

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