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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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An adaptive dynamics framework for microbial ecology and evolution.

Carl-Joar Karlsson1, Philip Gerlee1, Julie Rowlett2

  • 1Department of Mathematical Sciences, Chalmers University of Technology and the University of Gothenburg, 412 96, Gothenburg, Sweden.

Scientific Reports
|July 7, 2025
PubMed
Summary
This summary is machine-generated.

Adaptive dynamics models microbial evolution, revealing that unstable evolutionary processes and branching explain biodiversity and phenotypic variability in microbes.

Keywords:
Adaptive dynamicsDynamical systemsEvolutionary game theoryMicrobe ecologyNash equilibriumNon-cooperative game theoryPlankton

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Area of Science:

  • Evolutionary biology
  • Mathematical biology
  • Game theory

Background:

  • Adaptive dynamics offers a deterministic approximation for evolving traits.
  • Game theory models are applicable to microbial evolution.
  • Understanding evolutionary processes is key to explaining biodiversity.

Purpose of the Study:

  • To construct and analyze an evolutionary process for a game-theoretic model of microbial evolution.
  • To demonstrate the existence and regularity of solutions in adaptive dynamics.
  • To identify stationary solutions and link them to Nash equilibria.

Main Methods:

  • Constructing an evolutionary process for a game-theoretic model.
  • Analyzing the existence and regularity of adaptive dynamics solutions.
  • Identifying stationary solutions and proving their connection to Nash equilibria.
  • Utilizing numerical examples to illustrate dynamics.

Main Results:

  • Existence and regularity of solutions to adaptive dynamics were demonstrated.
  • Stationary solutions were identified and proven to be Nash equilibria.
  • The evolutionary dynamics were found to be unstable, with oscillating non-stationary solutions.
  • Linear branching was observed, rather than shrinking perturbations.

Conclusions:

  • Adaptive dynamics provides a framework for understanding microbial evolution.
  • Unstable dynamics and branching mechanisms contribute to microbial biodiversity and phenotypic variability.
  • The model offers a mechanistic explanation for the complexity observed in microbial systems.