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Fisher's geometric model with a moving optimum.

Sebastian Matuszewski1, Joachim Hermisson, Michael Kopp

  • 1Mathematics and BioSciences Group, Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, A-1090, Vienna, Austria. Sebastian.Matuszewski@univie.ac.at.

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Summary
This summary is machine-generated.

Populations adapt to changing environments by fixing beneficial mutations. The distribution of these mutations depends on environmental change rate and population adaptive potential, influencing evolutionary paths.

Keywords:
Adaptationmodels/simulationsmutationspleiotropypopulation geneticsselection-natural

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Area of Science:

  • Evolutionary biology
  • Theoretical ecology
  • Population genetics

Background:

  • Fisher's geometric model is a key framework for understanding adaptation.
  • Pleiotropy and organismic complexity influence evolutionary trajectories.
  • Previous models often assumed a static environmental optimum.

Purpose of the Study:

  • To investigate adaptation in Fisher's geometric model with a moving optimum.
  • To analyze the distribution of adaptive substitutions under environmental change.
  • To explore how ecological dynamics affect evolutionary rates and patterns.

Main Methods:

  • Utilized an adaptive-walk approximation.
  • Validated findings with individual-based simulations.
  • Focused on multivariate distribution of phenotypic effects of beneficial mutations.

Main Results:

  • Adaptive substitution distribution is governed by ecological dynamics and a composite parameter γ (environmental change rate scaled by adaptive potential).
  • Slow environmental change leads to adaptation reflecting fitness landscape shape; fast change mirrors mutation distribution.
  • Adaptation to a moving optimum involves larger steps for more complex organisms compared to static optimum models.

Conclusions:

  • Environmental change dynamics critically shape the evolutionary process.
  • The rate of adaptation is modulated by the interplay between environmental change and population's adaptive capacity.
  • Organismic complexity influences the scale of adaptive steps during evolution in dynamic environments.