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Chaos and unpredictability in evolution.

Michael Doebeli1, Iaroslav Ispolatov

  • 1Department of Zoology, University of British Columbia, 6270 University Boulevard, Vancouver, B.C. V6T 1Z4, Canada; Department of Mathematics, University of British Columbia, 6270 University Boulevard, Vancouver, B.C. V6T 1Z4, Canada. doebeli@zoology.ubc.ca.

Evolution; International Journal of Organic Evolution
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Summary
This summary is machine-generated.

Evolutionary chaos is common in complex systems with multiple interacting traits. Traditional "survival of the fittest" models oversimplify long-term evolutionary dynamics, failing to capture chaotic trajectories in high-dimensional phenotype spaces.

Keywords:
Adaptive dynamicschaoscomplex dynamicshigh-dimensional phenotype spacelogistic competition models

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Area of Science:

  • Evolutionary biology
  • Dynamical systems theory
  • Theoretical ecology

Background:

  • Nonlinear feedbacks drive complex dynamics in scientific models.
  • Evolutionary theory often assumes simple, directional optimization ('survival of the fittest').
  • This perspective is limited, especially with frequency-dependent selection on multiple traits.

Purpose of the Study:

  • To investigate the potential for long-term evolutionary chaos.
  • To model evolutionary dynamics with frequency-dependent selection on multiple phenotypes.
  • To challenge the traditional view of evolution as purely predictable.

Main Methods:

  • Developed models for evolutionary dynamics with frequency-dependent selection.
  • Analyzed systems with multiple interacting phenotypic components.
  • Explored large-dimensional phenotype spaces.

Main Results:

  • Complicated, chaotic evolutionary trajectories are common in high-dimensional phenotype spaces.
  • Selective interactions between phenotypic components increase the likelihood of chaos.
  • Simple, predictable dynamics represent only a fraction of possible long-term evolutionary outcomes.

Conclusions:

  • Evolutionary chaos is a prevalent feature in complex ecological and phenotypic interactions.
  • Rethinking evolutionary predictability is necessary for understanding long-term biological change.
  • Current models may underestimate the complexity of evolutionary trajectories.