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A Markov model for assessing ecological stability properties

Author

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  • Pawlowski, Christopher W.
  • McCord, Christopher

Abstract

Ecological systems are frequently modeled as dynamic systems. It is natural then to use the techniques of dynamic systems theory to analyze such models. However, the methods and results that are produced by dynamic systems theory do not always capture the aspects of ecological systems that are of greatest interest to managers and decision-makers. We identify some of the challenges of using dynamic systems theory to explore ecological systems and propose an alternative approach that emphasizes the understanding of transient effects in light of uncertainty and variability. We illustrate this method by an examination of a model for phosphorus levels in fresh water lakes.

Suggested Citation

  • Pawlowski, Christopher W. & McCord, Christopher, 2009. "A Markov model for assessing ecological stability properties," Ecological Modelling, Elsevier, vol. 220(2), pages 86-95.
    • Handle: RePEc:eee:ecomod:v:220:y:2009:i:2:p:86-95
    DOI: 10.1016/j.ecolmodel.2008.10.004
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    Cited by:

    1. Kilburn, R. & Gregory, A. & Murray, A.G., 2012. "Using a Markov-Chain Monte-Carlo modelling approach to identify the relative risk to farmed Scottish Rainbow trout (Oncorhynchus mykiss) in a multi-sector industry of Viral Haemorrhagic Septicaemia Vi," Ecological Modelling, Elsevier, vol. 237, pages 34-42.
    2. Craig, Peter D., 2010. "Imposed and inherent scales in cellular automata models of habitat," Ecological Modelling, Elsevier, vol. 221(20), pages 2425-2434.
    3. Molyneaux, Lynette & Brown, Colin & Wagner, Liam & Foster, John, 2016. "Measuring resilience in energy systems: Insights from a range of disciplines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1068-1079.

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