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A unified framework for analysis of individual-based models in ecology and beyond

Author

Listed:
  • Stephen J. Cornell

    (University of Liverpool)

  • Yevhen F. Suprunenko

    (University of Liverpool
    University of Cambridge)

  • Dmitri Finkelshtein

    (Swansea University)

  • Panu Somervuo

    (University of Helsinki)

  • Otso Ovaskainen

    (University of Helsinki
    Norwegian University of Science and Technology)

Abstract

Individual-based models, ‘IBMs’, describe naturally the dynamics of interacting organisms or social or financial agents. They are considered too complex for mathematical analysis, but computer simulations of them cannot give the general insights required. Here, we resolve this problem with a general mathematical framework for IBMs containing interactions of an unlimited level of complexity, and derive equations that reliably approximate the effects of space and stochasticity. We provide software, specified in an accessible and intuitive graphical way, so any researcher can obtain analytical and simulation results for any particular IBM without algebraic manipulation. We illustrate the framework with examples from movement ecology, conservation biology, and evolutionary ecology. This framework will provide unprecedented insights into a hitherto intractable panoply of complex models across many scientific fields.

Suggested Citation

  • Stephen J. Cornell & Yevhen F. Suprunenko & Dmitri Finkelshtein & Panu Somervuo & Otso Ovaskainen, 2019. "A unified framework for analysis of individual-based models in ecology and beyond," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12172-y
    DOI: 10.1038/s41467-019-12172-y
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    Cited by:

    1. Wadkin, Laura E. & Holden, John & Ettelaie, Rammile & Holmes, Melvin J. & Smith, James & Golightly, Andrew & Parker, Nick G. & Baggaley, Andrew W., 2024. "Estimating the reproduction number, R0, from individual-based models of tree disease spread," Ecological Modelling, Elsevier, vol. 489(C).

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