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Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

Iaroslav Ispolatov1, Vaibhav Madhok2, Michael Doebeli3

  • 1Departamento de Fisica, Universidad de Santiago de Chile, Casilla 302, Correo 2, Santiago, Chile.

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Evolutionary diversification theories often assume equilibrium, but this study shows non-equilibrium dynamics in complex trait spaces. Introducing Gaussian competition promotes diversification, even against directional selection.

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Area of Science:

  • Evolutionary Biology
  • Theoretical Ecology
  • Mathematical Biology

Background:

  • Traditional evolutionary diversification theories rely on equilibrium assumptions.
  • Adaptive dynamics models may not converge to equilibrium in high-dimensional trait spaces, leading to complex evolutionary trajectories.
  • Reconstructing individual-based models is crucial for studying non-equilibrium diversification.

Purpose of the Study:

  • To develop a method for constructing individual-based models that accurately replicate adaptive dynamics without diversification.
  • To investigate how to introduce diversification into these models.
  • To explore the role of frequency-dependent selection in driving diversification.

Main Methods:

  • Construction of individual-based models from adaptive dynamics attractors.
  • Inclusion of Gaussian competition terms to induce frequency dependence.
  • Analysis of disruptive selection generated by frequency-dependent interactions.

Main Results:

  • A method was established to reproduce adaptive dynamics without diversification.
  • Gaussian competition successfully introduced a propensity for diversification.
  • Disruptive selection from frequency dependence drove diversification in directions orthogonal to the selection gradient.

Conclusions:

  • Non-equilibrium dynamics are important for understanding evolutionary diversification in complex trait spaces.
  • Frequency-dependent selection, induced by competition, can promote diversification.
  • Diversification can occur in unexpected phenotypic directions, challenging equilibrium-based predictions.