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Marine ecosystem models of realistic complexity rarely exhibits significant endogenous non-stationary dynamics

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  • Occhipinti, Guido
  • Solidoro, Cosimo
  • Grimaudo, Roberto
  • Valenti, Davide
  • Lazzari, Paolo

Abstract

Despite the observation of cyclic and chaotic dynamics in nature, it is still not clear whether this behaviour is inherent to ecological systems or caused by external forcings. Here we explored a set of approximately 210,000 simulations to assess how often a model of realistic complexity exhibits non-stationary dynamics when external perturbations are excluded. Remarkably, less than one third of the population shown non-stationary dynamics and, even when present, fluctuations were rather small. The inherent stability of plankton communities showed to be related to the presence of multiple feedbacks in the food web structure, omnivory, low centre of gravity, and supports the conclusion that food webs of realistic complexity rarely exhibit significant endogenous non-stationary dynamics. Finally, we computed Lyapunov exponents for the non-stationary trajectories, in order to assess in which proportion they were periodic or chaotic, and we concluded that less than 10% of the non-stationary trajectories (3% of the total) showed sensitivities to initial conditions. This further supports the conclusion that complex topology mainly damps endogenous fluctuations in the food web.

Suggested Citation

  • Occhipinti, Guido & Solidoro, Cosimo & Grimaudo, Roberto & Valenti, Davide & Lazzari, Paolo, 2023. "Marine ecosystem models of realistic complexity rarely exhibits significant endogenous non-stationary dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s0960077923008627
    DOI: 10.1016/j.chaos.2023.113961
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    1. Lutz Becks & Frank M. Hilker & Horst Malchow & Klaus Jürgens & Hartmut Arndt, 2005. "Experimental demonstration of chaos in a microbial food web," Nature, Nature, vol. 435(7046), pages 1226-1229, June.
    2. Elisa Benincà & Jef Huisman & Reinhard Heerkloss & Klaus D. Jöhnk & Pedro Branco & Egbert H. Van Nes & Marten Scheffer & Stephen P. Ellner, 2008. "Chaos in a long-term experiment with a plankton community," Nature, Nature, vol. 451(7180), pages 822-825, February.
    3. Stephanie A. Henson & B. B. Cael & Stephanie R. Allen & Stephanie Dutkiewicz, 2021. "Future phytoplankton diversity in a changing climate," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    4. Sankar, S. & Polimene, L. & Marin, L. & Menon, N.N. & Samuelsen, A. & Pastres, R. & Ciavatta, S., 2018. "Sensitivity of the simulated Oxygen Minimum Zone to biogeochemical processes at an oligotrophic site in the Arabian Sea," Ecological Modelling, Elsevier, vol. 372(C), pages 12-23.
    5. Tedesco, Letizia & Vichi, Marcello & Thomas, David N., 2012. "Process studies on the ecological coupling between sea ice algae and phytoplankton," Ecological Modelling, Elsevier, vol. 226(C), pages 120-138.
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