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MayaSim: An Agent-Based Model of the Ancient Maya Social-Ecological System

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  • Scott Heckbert

Abstract

This paper presents results from the MayaSim model, an integrated agent-based, cellular automata, and network model representing the ancient Maya social-ecological system. The model represents the relationship between population growth, agricultural production, soil degradation, climate variability, primary productivity, hydrology, ecosystem services, forest succession, and the stability of trade networks. Agents representing settlements develop and expand within a spatial landscape that changes under climate variation and responds to anthropogenic impacts. The model is able to reproduce spatial patterns and timelines somewhat analogous to that of the ancient Maya, although this proof-of-concept model requires refinement and further archaeological data for calibration. This paper aims to identify candidate features of a resilient versus vulnerable social-ecological system, and employs computer simulation to explore this topic, using the ancient Maya as an example. Complex systems modelling identifies how interconnected variables behave, considering fast-moving variables such as land cover change and trade connections, meso-speed variables such as demographics and climate variability, as well as slow-moving variables such as soil degradation.

Suggested Citation

  • Scott Heckbert, 2013. "MayaSim: An Agent-Based Model of the Ancient Maya Social-Ecological System," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 16(4), pages 1-11.
    • Handle: RePEc:jas:jasssj:2012-93-3
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    File URL: https://www.jasss.org/16/4/11/11.pdf
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    Citations

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    Cited by:

    1. Davide Secchi & Raffaello Seri, 2017. "Controlling for false negatives in agent-based models: a review of power analysis in organizational research," Computational and Mathematical Organization Theory, Springer, vol. 23(1), pages 94-121, March.
    2. Costanza, Robert & Chichakly, Karim & Dale, Virginia & Farber, Steve & Finnigan, David & Grigg, Kat & Heckbert, Scott & Kubiszewski, Ida & Lee, Harry & Liu, Shuang & Magnuszewski, Piotr & Maynard, Sim, 2014. "Simulation games that integrate research, entertainment, and learning around ecosystem services," Ecosystem Services, Elsevier, vol. 10(C), pages 195-201.
    3. Белоусов Ф.А., 2018. "Модель "Кочевников" И "Землепашцев" С Ограниченным Ресурсом Пространственного Перемещения," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 54(4), pages 124-131, октябрь.
    4. Sikk, Kaarel & Caruso, Geoffrey, 2024. "Framing settlement systems as spatial adaptive systems," Ecological Modelling, Elsevier, vol. 490(C).
    5. Roman, Sabin & Palmer, Erika & Brede, Markus, 2018. "The Dynamics of Human–Environment Interactions in the Collapse of the Classic Maya," Ecological Economics, Elsevier, vol. 146(C), pages 312-324.
    6. Michael Yearworth & Sarah E. Cornell, 2016. "Contested Modelling: a Critical Examination of Expert Modelling in Sustainability," Systems Research and Behavioral Science, Wiley Blackwell, vol. 33(1), pages 45-63, January.
    7. Roman, Sabin & Bullock, Seth & Brede, Markus, 2017. "Coupled Societies are More Robust Against Collapse: A Hypothetical Look at Easter Island," Ecological Economics, Elsevier, vol. 132(C), pages 264-278.

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