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Non-Linear Analysis Indicates Chaotic Dynamics and Reduced Resilience in Model-Based Daphnia Populations Exposed to Environmental Stress

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  • Richard Ottermanns
  • Kerstin Szonn
  • Thomas G Preuß
  • Martina Roß-Nickoll

Abstract

In this study we present evidence that anthropogenic stressors can reduce the resilience of age-structured populations. Enhancement of disturbance in a model-based Daphnia population lead to a repression of chaotic population dynamics at the same time increasing the degree of synchrony between the population's age classes. Based on the theory of chaos-mediated survival an increased risk of extinction was revealed for this population exposed to high concentrations of a chemical stressor. The Lyapunov coefficient was supposed to be a useful indicator to detect disturbance thresholds leading to alterations in population dynamics. One possible explanation could be a discrete change in attractor orientation due to external disturbance. The statistical analysis of Lyapunov coefficient distribution is proposed as a methodology to test for significant non-linear effects of general disturbance on populations. Although many new questions arose, this study forms a theoretical basis for a dynamical definition of population recovery.

Suggested Citation

  • Richard Ottermanns & Kerstin Szonn & Thomas G Preuß & Martina Roß-Nickoll, 2014. "Non-Linear Analysis Indicates Chaotic Dynamics and Reduced Resilience in Model-Based Daphnia Populations Exposed to Environmental Stress," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-13, May.
    • Handle: RePEc:plo:pone00:0096270
    DOI: 10.1371/journal.pone.0096270
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    1. Lutz Becks & Frank M. Hilker & Horst Malchow & Klaus Jürgens & Hartmut Arndt, 2005. "Experimental demonstration of chaos in a microbial food web," Nature, Nature, vol. 435(7046), pages 1226-1229, June.
    2. Gabsi, Faten & Hammers-Wirtz, Monika & Grimm, Volker & Schäffer, Andreas & Preuss, Thomas G., 2014. "Coupling different mechanistic effect models for capturing individual- and population-level effects of chemicals: Lessons from a case where standard risk assessment failed," Ecological Modelling, Elsevier, vol. 280(C), pages 18-29.
    3. Elisa Benincà & Jef Huisman & Reinhard Heerkloss & Klaus D. Jöhnk & Pedro Branco & Egbert H. Van Nes & Marten Scheffer & Stephen P. Ellner, 2008. "Chaos in a long-term experiment with a plankton community," Nature, Nature, vol. 451(7180), pages 822-825, February.
    4. Preuss, Thomas Günter & Hammers-Wirtz, Monika & Hommen, Udo & Rubach, Mascha Nadine & Ratte, Hans Toni, 2009. "Development and validation of an individual based Daphnia magna population model: The influence of crowding on population dynamics," Ecological Modelling, Elsevier, vol. 220(3), pages 310-329.
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