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Complex Population Dynamics in Mussels Arising from Density-Linked Stochasticity

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  • J Timothy Wootton
  • James D Forester

Abstract

Population fluctuations are generally attributed to the deterministic consequences of strong non-linear interactions among organisms, or the effects of random stochastic environmental variation superimposed upon the deterministic skeleton describing population change. Analysis of the population dynamics of the mussel Mytilus californianus taken in 16 plots over 18-years found no evidence that these processes explained observed strong fluctuations. Instead, population fluctuations arose because environmental stochasticity varied with abundance, which we term density-linked stochasticity. This phenomenon arises from biologically relevant mechanisms: recruitment variation and transmission of disturbance among neighboring individuals. Density-linked stochasticity is probably present frequently in populations, as it arises naturally from several general ecological processes, including stage structure variation with density, ontogenetic niche shifts, and local transmission of stochastic perturbations. More thoroughly characterizing and interpreting deviations from the mean behavior of a system will lead to better ecological prediction and improved insight into the important processes affecting populations and ecosystems.

Suggested Citation

  • J Timothy Wootton & James D Forester, 2013. "Complex Population Dynamics in Mussels Arising from Density-Linked Stochasticity," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-12, September.
  • Handle: RePEc:plo:pone00:0075700
    DOI: 10.1371/journal.pone.0075700
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    References listed on IDEAS

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    1. J. Timothy Wootton, 2001. "Local interactions predict large-scale pattern in empirically derived cellular automata," Nature, Nature, vol. 413(6858), pages 841-844, October.
    2. E. L. Berlow, 1999. "Strong effects of weak interactions in ecological communities," Nature, Nature, vol. 398(6725), pages 330-334, March.
    3. Martin J. Crowder, 1978. "Beta‐Binomial Anova for Proportions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 27(1), pages 34-37, March.
    4. Ottar N. Bjørnstad & Steven M. Sait & Nils C. Stenseth & David J. Thompson & Michael Begon, 2001. "The impact of specialized enemies on the dimensionality of host dynamics," Nature, Nature, vol. 409(6823), pages 1001-1006, February.
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