IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v180y2020ics0308521x19301969.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X19301969
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2019.102718?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huber, Robert & Bakker, Martha & Balmann, Alfons & Berger, Thomas & Bithell, Mike & Brown, Calum & Grêt-Regamey, Adrienne & Xiong, Hang & Le, Quang Bao & Mack, Gabriele & Meyfroidt, Patrick & Millingt, 2018. "Representation of decision-making in European agricultural agent-based models," Agricultural Systems, Elsevier, vol. 167(C), pages 143-160.
    2. Karl-Heinz Erb & Christian Lauk & Thomas Kastner & Andreas Mayer & Michaela C. Theurl & Helmut Haberl, 2016. "Exploring the biophysical option space for feeding the world without deforestation," Nature Communications, Nature, vol. 7(1), pages 1-9, September.
    3. Thomas Berger & Christian Troost, 2014. "Agent-based Modelling of Climate Adaptation and Mitigation Options in Agriculture," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 323-348, June.
    4. Nicholas R Magliocca & Daniel G Brown & Erle C Ellis, 2013. "Exploring Agricultural Livelihood Transitions with an Agent-Based Virtual Laboratory: Global Forces to Local Decision-Making," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-11, September.
    5. Pöschl, Martina & Ward, Shane & Owende, Philip, 2010. "Evaluation of energy efficiency of various biogas production and utilization pathways," Applied Energy, Elsevier, vol. 87(11), pages 3305-3321, November.
    6. Grillot, Myriam & Vayssières, Jonathan & Masse, Dominique, 2018. "Agent-based modelling as a time machine to assess nutrient cycling reorganization during past agrarian transitions in West Africa," Agricultural Systems, Elsevier, vol. 164(C), pages 133-151.
    7. Jonathan A. Foley & Navin Ramankutty & Kate A. Brauman & Emily S. Cassidy & James S. Gerber & Matt Johnston & Nathaniel D. Mueller & Christine O’Connell & Deepak K. Ray & Paul C. West & Christian Balz, 2011. "Solutions for a cultivated planet," Nature, Nature, vol. 478(7369), pages 337-342, October.
    8. Benjamin Leon Bodirsky & Alexander Popp & Hermann Lotze-Campen & Jan Philipp Dietrich & Susanne Rolinski & Isabelle Weindl & Christoph Schmitz & Christoph Müller & Markus Bonsch & Florian Humpenöder &, 2014. "Reactive nitrogen requirements to feed the world in 2050 and potential to mitigate nitrogen pollution," Nature Communications, Nature, vol. 5(1), pages 1-7, September.
    9. Xu, Wanying & Zhou, Chuanbin & Cao, Aixin & Luo, Min, 2016. "Understanding the mechanism of food waste management by using stakeholder analysis and social network model: An industrial ecology perspective," Ecological Modelling, Elsevier, vol. 337(C), pages 63-72.
    10. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
    11. Julie Smith & Tim Lang & Bill Vorley & David Barling, 2016. "Addressing Policy Challenges for More Sustainable Local–Global Food Chains: Policy Frameworks and Possible Food “Futures”," Sustainability, MDPI, vol. 8(4), pages 1-17, March.
    12. Adrienne Grêt-Regamey & Sibyl H. Huber & Robert Huber, 2019. "Actors’ diversity and the resilience of social-ecological systems to global change," Nature Sustainability, Nature, vol. 2(4), pages 290-297, April.
    13. Rémy Courdier & François Guerrin & Fenintsoa Andriamasinoro & Jean-Marie Paillat, 2002. "Agent-Based Simulation of Complex Systems: Application to Collective Management of Animal Wastes," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-4.
    14. François Rebaudo & Verónica Crespo-Pérez & Jean-François Silvain & Olivier Dangles, 2011. "Agent-Based Modeling of Human-Induced Spread of Invasive Species in Agricultural Landscapes: Insights from the Potato Moth in Ecuador," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(3), pages 1-7.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Joris Baars & Mohammad Ali Rajaeifar & Oliver Heidrich, 2022. "Quo vadis MFA? Integrated material flow analysis to support material efficiency," Journal of Industrial Ecology, Yale University, vol. 26(4), pages 1487-1503, August.
    2. Rizzati, Massimiliano & Landoni, Matteo, 2024. "A systematic review of agent-based modelling in the circular economy: Insights towards a general model," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 617-631.
    3. 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).
    4. 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.
    5. 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.
    6. 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).
    7. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).
    2. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.
    3. Matteo Coronese & Martina Occelli & Francesco Lamperti & Andrea Roventini, 2024. "Towards sustainable agriculture: behaviors, spatial dynamics and policy in an evolutionary agent-based model," LEM Papers Series 2024/05, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    4. Brinkmann, Katja & Kübler, Daniel & Liehr, Stefan & Buerkert, Andreas, 2021. "Agent-based modelling of the social-ecological nature of poverty traps in southwestern Madagascar," Agricultural Systems, Elsevier, vol. 190(C).
    5. Bowles, Nicholas & Alexander, Samuel & Hadjikakou, Michalis, 2019. "The livestock sector and planetary boundaries: A ‘limits to growth’ perspective with dietary implications," Ecological Economics, Elsevier, vol. 160(C), pages 128-136.
    6. Tianran Ding & Wouter Achten, 2023. "Coupling agent-based modeling with territorial LCA to support agricultural land-use planning," ULB Institutional Repository 2013/359527, ULB -- Universite Libre de Bruxelles.
    7. Yibo Luan & Wenquan Zhu & Xuefeng Cui & Günther Fischer & Terence P. Dawson & Peijun Shi & Zhenke Zhang, 2019. "Cropland yield divergence over Africa and its implication for mitigating food insecurity," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(5), pages 707-734, June.
    8. Huber, Robert & Bakker, Martha & Balmann, Alfons & Berger, Thomas & Bithell, Mike & Brown, Calum & Grêt-Regamey, Adrienne & Xiong, Hang & Le, Quang Bao & Mack, Gabriele & Meyfroidt, Patrick & Millingt, 2018. "Representation of decision-making in European agricultural agent-based models," Agricultural Systems, Elsevier, vol. 167(C), pages 143-160.
    9. Noeldeke, Beatrice & Winter, Etti & Ntawuhiganayo, Elisée Bahati, 2022. "Representing human decision-making in agent-based simulation models: Agroforestry adoption in rural Rwanda," Ecological Economics, Elsevier, vol. 200(C).
    10. Kremmydas, Dimitris & Athanasiadis, Ioannis N. & Rozakis, Stelios, 2018. "A review of Agent Based Modeling for agricultural policy evaluation," Agricultural Systems, Elsevier, vol. 164(C), pages 95-106.
    11. Egger, Claudine & Plutzar, Christoph & Mayer, Andreas & Dullinger, Iwona & Dullinger, Stefan & Essl, Franz & Gattringer, Andreas & Bohner, Andreas & Haberl, Helmut & Gaube, Veronika, 2022. "Using the SECLAND model to project future land-use until 2050 under climate and socioeconomic change in the LTSER region Eisenwurzen (Austria)," Ecological Economics, Elsevier, vol. 201(C).
    12. Rianne Duinen & Tatiana Filatova & Wander Jager & Anne Veen, 2016. "Going beyond perfect rationality: drought risk, economic choices and the influence of social networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(2), pages 335-369, November.
    13. Carrasco, L. Roman & Cook, David & Baker, Richard & MacLeod, Alan & Knight, Jon D. & Mumford, John D., 2012. "Towards the integration of spread and economic impacts of biological invasions in a landscape of learning and imitating agents," Ecological Economics, Elsevier, vol. 76(C), pages 95-103.
    14. Troost, Christian & Huber, Robert & Bell, Andrew R. & van Delden, Hedwig & Filatova, Tatiana & Le, Quang Bao & Lippe, Melvin & Niamir, Leila & Polhill, J. Gareth & Sun, Zhanli & Berger, Thomas, 2023. "How to keep it adequate: A protocol for ensuring validity in agent-based simulation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 159, pages 1-21.
    15. Ran Sun & James Nolan & Suren Kulshreshtha, 2022. "Agent-based modeling of policy induced agri-environmental technology adoption," SN Business & Economics, Springer, vol. 2(8), pages 1-26, August.
    16. Utomo, Dhanan Sarwo & Onggo, Bhakti Stephan & Eldridge, Stephen, 2018. "Applications of agent-based modelling and simulation in the agri-food supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 794-805.
    17. Mollie Chapman & Susanna Klassen & Maayan Kreitzman & Adrian Semmelink & Kelly Sharp & Gerald Singh & Kai M. A. Chan, 2017. "5 Key Challenges and Solutions for Governing Complex Adaptive (Food) Systems," Sustainability, MDPI, vol. 9(9), pages 1-30, September.
    18. Evgeny Latynskiy & Thomas Berger, 2017. "Assessing the Income Effects of Group Certification for Smallholder Coffee Farmers: Agent-based Simulation in Uganda," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(3), pages 727-748, September.
    19. Berre, D. & Diarisso, T. & Andrieu, N. & Le Page, C. & Corbeels, M., 2021. "Biomass flows in an agro-pastoral village in West-Africa: Who benefits from crop residue mulching?," Agricultural Systems, Elsevier, vol. 187(C).
    20. Beatrice Nöldeke & Etti Winter & Yves Laumonier & Trifosa Simamora, 2021. "Simulating Agroforestry Adoption in Rural Indonesia: The Potential of Trees on Farms for Livelihoods and Environment," Land, MDPI, vol. 10(4), pages 1-31, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agisys:v:180:y:2020:i:c:s0308521x19301969. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.