6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Colour of environmental noise affects the nonlinear dynamics of cycling, stage-structured populations.

      Ecology Letters
      Animals, Beetles, physiology, Ecosystem, Larva, growth & development, Models, Biological, Nonlinear Dynamics, Population Dynamics, Stochastic Processes, Time Factors

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Populations fluctuate because of their internal dynamics, which can be nonlinear and stochastic, and in response to environmental variation. Theory predicts how the colour of environmental stochasticity affects population means, variances and correlations with the environment over time. The theory has not been tested for cycling populations, commonly observed in field systems. We applied noise of different colours to cycling laboratory beetle populations, holding other statistical properties of the noise fixed. Theory was largely validated, but failed to predict observations in sufficient detail. The main period of population cycling was shifted up to 33% by the colour of environmental stochasticity. Noise colour affected population means, variances and dominant periodicities differently for populations that cycled in different ways without noise. Our results show that changes in the colour of climatic variability, partly caused by humans, may affect the main periodicity of cycling populations, possibly impacting industry, pest management and conservation.

          Related collections

          Author and article information

          Journal
          18479454
          10.1111/j.1461-0248.2008.01194.x

          Chemistry
          Animals,Beetles,physiology,Ecosystem,Larva,growth & development,Models, Biological,Nonlinear Dynamics,Population Dynamics,Stochastic Processes,Time Factors

          Comments

          Comment on this article