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Multi-level agent-based modelling of social-ecological systems: Bridging the gap between the micro and macro levels

Author

Listed:
  • Sun, Zhanli
  • Ringsmuth, Andrew K.
  • Barbrook-Johnson, Pete
  • Van Delden, Hedwig
  • Dou, Yue
  • Gotts, Nick
  • Grant, William E.
  • Hofstede, Gert Jan
  • Jager, Wander
  • Koch, Jennifer
  • LePage, Christophe
  • Little, John C.
  • Meyer, Markus
  • Natalini, Davide
  • Wang, Hsiao-Hsuan
  • Zare, Fateme
  • Lippe, Melvin

Abstract

Social-ecological systems (SESs) are complex adaptive systems that encompass multiple spatial, temporal, and organisational scales and levels. The dynamics of SESs are driven by interactions among processes occurring both within and across different levels. These multi-level interactions generate patterns of system behaviour that emerge at different spatial, temporal, and organisational levels. This has profound implications for managing SESs. Agent-based models (ABMs) are known for their ability to simulate emergent phenomena and are powerful tools for modelling SESs. However, most multi-level ABMs focus merely on individual/micro-level interactions and aggregated/macro-level interactions and rarely capture the true multi-level dynamics of SESs, which often include effects that cascade across multiple levels. We describe a conceptual framework for multi-level ABMs that couple processes occurring at intermediate levels with those occurring at micro and macro levels, and, more importantly, propose a mathematical construct that embodies the generic features of a truly multi-level ABM. We then discuss our proposed model within the context of past and potential future multi-level agent-based modelling efforts.

Suggested Citation

  • Sun, Zhanli & Ringsmuth, Andrew K. & Barbrook-Johnson, Pete & Van Delden, Hedwig & Dou, Yue & Gotts, Nick & Grant, William E. & Hofstede, Gert Jan & Jager, Wander & Koch, Jennifer & LePage, Christophe, 2026. "Multi-level agent-based modelling of social-ecological systems: Bridging the gap between the micro and macro levels," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 8, pages 1-20.
  • Handle: RePEc:zbw:espost:340884
    DOI: 10.18174/sesmo.18914
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    References listed on IDEAS

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    1. Amorocho-Daza, Henry & Sušnik, Janez & van der Zaag, Pieter & Slinger, Jill H., 2025. "A model-based policy analysis framework for social-ecological systems: Integrating uncertainty and participation in system dynamics modelling," Ecological Modelling, Elsevier, vol. 499(C).
    2. White, Easton R. & Wulfing, Sophie, 2024. "Extreme events and coupled socio-ecological systems," Ecological Modelling, Elsevier, vol. 495(C).
    3. Wang, Ming & Wang, Hsiao-Hsuan & Koralewski, Tomasz E. & Grant, William E. & White, Neil & Hanan, Jim & Grimm, Volker, 2024. "From known to unknown unknowns through pattern-oriented modelling: Driving research towards the Medawar zone," Ecological Modelling, Elsevier, vol. 497(C).
    4. Mrosla, Laura & Fabritius, Henna & Kupper, Kristiina & Dembski, Fabian & Fricker, Pia, 2025. "What grows, adapts and lives in the digital sphere? Systematic literature review on the dynamic modelling of flora and fauna in digital twins," Ecological Modelling, Elsevier, vol. 504(C).
    5. Christian Berger & Mari Bieri & Karen Bradshaw & Christian Brümmer & Thomas Clemen & Thomas Hickler & Werner Leo Kutsch & Ulfia A. Lenfers & Carola Martens & Guy F. Midgley & Kanisios Mukwashi & Victo, 2019. "Linking scales and disciplines: an interdisciplinary cross-scale approach to supporting climate-relevant ecosystem management," Climatic Change, Springer, vol. 156(1), pages 139-150, September.
    6. 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.
    7. Jager, W. & Janssen, M. A. & De Vries, H. J. M. & De Greef, J. & Vlek, C. A. J., 2000. "Behaviour in commons dilemmas: Homo economicus and Homo psychologicus in an ecological-economic model," Ecological Economics, Elsevier, vol. 35(3), pages 357-379, December.
    8. Wang, Hsiao-Hsuan & Van Voorn, George & Grant, William E. & Zare, Fateme & Giupponi, Carlo & Steinmann, Patrick & Müller, Birgit & Elsawah, Sondoss & van Delden, Hedwig & Athanasiadis, Ioannis N. & Su, 2023. "Scale decisions and good practices in socio-environmental systems modelling: Guidance and documentation during problem scoping and model formulation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 5, pages 1-1.
    9. Wang, Hsiao-Hsuan & Grant, William E. & Birt, Andrew G. & Wilcox, Bradford P., 2025. "Modeling rangelands as complex adaptive socio-ecological systems: An agent-based model of pyric herbivory," Ecological Modelling, Elsevier, vol. 501(C).
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