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Synergetic Approach and modeling of fish population dynamics

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  • Vyacheslav Navrotsky

Abstract

In the last few years it has become increasingly obvious that one of the obstacles in the way of constructing good simulation models of the global ocean ecosystem is a poor understanding of the general principles of marine ecosystems processes. A great number of factors and relationships acting in the marine environment, in combination with the random character of change in many of them, call for the development of new approaches in modeling. In this paper a synergetic approach is proposed. A new paradigm for this approach is discussed. As an example a population with logistic natural growth under different conditions of exploitation is considered. It is shown that the simplest mechanism, that principally changes the behavior of a population in a fluctuating environment, includes fishing and migration. This mechanism explains catastrophic changes in population abundance in cases when no one factor may be seen as exclusive. It is shown that the characteristic level of population number does not correspond to the average balance between input (migration), output (fishing) and the growth of the population. The environment variability leads to stabilization far from equilibrium. This totally conforms to one of the fundamental results in Synergetics which assert that non‐equilibrium in the presence of fluctuations may serve as a source of new order. Copyright Kluwer Academic Publishers 2000

Suggested Citation

  • Vyacheslav Navrotsky, 2000. "Synergetic Approach and modeling of fish population dynamics," Annals of Operations Research, Springer, vol. 94(1), pages 357-373, January.
  • Handle: RePEc:spr:annopr:v:94:y:2000:i:1:p:357-373:10.1023/a:1018981519768
    DOI: 10.1023/A:1018981519768
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    Cited by:

    1. Karim, Md Aktar Ul & Aithal, Vikram & Bhowmick, Amiya Ranjan, 2023. "Random variation in model parameters: A comprehensive review of stochastic logistic growth equation," Ecological Modelling, Elsevier, vol. 484(C).

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