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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Evolutionary branching in deme-structured populations.

Joe Yuichiro Wakano1, Laurent Lehmann2

  • 1Meiji Institute for Advanced Study of Mathematical Sciences, Meiji University, Tokyo 164-8525, Japan; Japan Science and Technology, PRESTO, Japan.

Journal of Theoretical Biology
|March 18, 2014
PubMed
Summary
This summary is machine-generated.

Evolutionary branching, where a single trait splits into two, can occur in structured populations. This study derives a simplified condition for this process, especially when traits affect survival or reproduction.

Keywords:
Genetic driftHamilton׳s ruleInclusive fitness effect on trait varianceIndividual-based simulationRelatedness

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Area of Science:

  • Evolutionary Biology
  • Theoretical Ecology
  • Quantitative Genetics

Background:

  • Adaptive dynamics theory describes how continuous traits under frequency-dependent selection can lead to evolutionary branching.
  • Evolutionary branching involves a unimodal trait distribution transitioning to a bimodal one, indicating diversification.
  • Previous models often relied on relatedness or mutant-resident dynamics to predict branching.

Purpose of the Study:

  • To investigate evolutionary branching in deme-structured populations using a quantitative genetic model.
  • To derive an analytic condition for evolutionary branching based on trait variance dynamics.
  • To simplify the branching condition, particularly for traits influencing fecundity and survival.

Main Methods:

  • Construction of a quantitative genetic model for trait variance dynamics in a structured population.
  • Derivation of an analytic condition for evolutionary branching.
  • Comparison of the derived condition with existing relatedness-based and mutant-resident approaches.

Main Results:

  • The derived analytic condition for evolutionary branching aligns with previous theoretical frameworks.
  • A simplified branching condition is obtained when the evolving trait directly impacts fecundity or survival.
  • The model predicts a threshold migration rate below which evolutionary branching is inhibited in pairwise interaction games.

Conclusions:

  • The quantitative genetic model provides a robust framework for studying evolutionary branching in structured populations.
  • The simplified condition offers new insights into the role of trait-dependent selection pressures on diversification.
  • Model predictions show strong agreement with individual-based simulation results, validating its applicability.