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Stochastic Identification of Stability of Competitive Interactions in Ecosystems

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  • Marek Vach
  • Pavla Vachová

Abstract

The problem of finding an optimum within a set of possibilities that represent the varying successfulness of numerous subjects competing with one another is highly relevant in the field of ecosystem interactions. We propose a method for solving this problem by the application of the Nash equilibrium concept, which is frequently used in ecology. The proposed model is based on the transformation of the initial payoff vectors of subjects that interact in different situations into a statistical set of symmetrical game matrices that consist of permutations of payoff values. The equilibrium solution is expressed as values of the probability of Nash equilibrium occurrence with uniform distribution over all possible permutations based on uncertainty of positions of payoff values in the matrix. We assume that this equilibrium solution provides information on the distribution of the degree of stability among individual situations and interacting subjects. In this paper, we validate this assumption and demonstrate its application to a dataset that represents interspecies interactions in plant ecology. We propose that the use of the Nash equilibrium in the analysis of datasets formalized according to the Pareto optimality scheme is applicable in numerous other contexts.

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  • Marek Vach & Pavla Vachová, 2016. "Stochastic Identification of Stability of Competitive Interactions in Ecosystems," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-12, May.
    • Handle: RePEc:plo:pone00:0155023
    DOI: 10.1371/journal.pone.0155023
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    References listed on IDEAS

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    1. Miguel Porto & Otília Correia & Pedro Beja, 2014. "Optimization of Landscape Services under Uncoordinated Management by Multiple Landowners," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-16, January.
    2. Matteo Convertino & L James Valverde Jr, 2013. "Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-14, June.
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