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Ways to reduce or avoid juvenile-driven cycles in individual-based population models

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  • Kooijman, S.A.L.M.

Abstract

Feeding being linked to surface area and maintenance to volume causes juvenile-driven cycles in individual-based population models (IBM’s). This combination of traits induces self-synchronisation of individuals: at some low food level, small individuals can still grow, but large ones cannot. Since Dynamic Energy Budget (DEB) models have these features, which are well-tested for individuals in the Add_my_Pet collection, DEB-based population models have such juvenile-driven cycles in simple homogeneous reactors. These cycles are, however, not seen in practice. This paper explores ways to reduce or avoid such cycles in a realistic way, keeping the model as simple as possible, and comes with recommendations. Some of the fixes also repair related artefacts of too simple population models, such as competitive exclusion, the paradox of enrichment and merry-go-around. A size-dependent hazard, which is essential for species with many small offspring, and details on nutrition are unavoidable in realistic models for physiologically structured population dynamics.

Suggested Citation

  • Kooijman, S.A.L.M., 2024. "Ways to reduce or avoid juvenile-driven cycles in individual-based population models," Ecological Modelling, Elsevier, vol. 490(C).
    • Handle: RePEc:eee:ecomod:v:490:y:2024:i:c:s0304380024000383
    DOI: 10.1016/j.ecolmodel.2024.110649
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    References listed on IDEAS

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    1. Kooijman, Sebastiaan A.L.M. & Lika, Konstadia & Augustine, Starrlight & Marn, Nina & Kooi, Bob W., 2020. "The energetic basis of population growth in animal kingdom," Ecological Modelling, Elsevier, vol. 428(C).
    2. De Roos, André M. & Schellekens, Tim & Van Kooten, Tobias & Van De Wolfshaar, Karen & Claessen, David & Persson, Lennart, 2008. "Simplifying a physiologically structured population model to a stage-structured biomass model," Theoretical Population Biology, Elsevier, vol. 73(1), pages 47-62.
    3. Jef Huisman & Franz J. Weissing, 1999. "Biodiversity of plankton by species oscillations and chaos," Nature, Nature, vol. 402(6760), pages 407-410, November.
    4. Lika, K. & Kooijman, S.A.L.M., 2024. "The metabolic interpretation of the von Bertalanffy growth rate," Ecological Modelling, Elsevier, vol. 488(C).
    5. Nisbet, Roger M. & Martin, Benjamin T. & de Roos, Andre M., 2016. "Integrating ecological insight derived from individual-based simulations and physiologically structured population models," Ecological Modelling, Elsevier, vol. 326(C), pages 101-112.
    6. Jager, Tjalling, 2020. "Revisiting simplified DEBtox models for analysing ecotoxicity data," Ecological Modelling, Elsevier, vol. 416(C).
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