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An integrated bayesian theory of phenotypic flexibility.

Peter J Richerson1

  • 1Department of Environmental Science and Policy, University of California-Davis, One Shields Avenue, Davis, CA, 95616, USA.

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PubMed
Summary

Phenotypic flexibility, including learning and immunity, allows organisms to adapt to changing environments across diverse timescales. These systems use exploration and retention, akin to Bayesian processes, to navigate uncertainty and interact with genetic evolution.

Keywords:
Bayesian updatingEvolutionPhenotypic flexibility

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Area of Science:

  • Evolutionary biology
  • Cognitive science
  • Immunology

Background:

  • Phenotypic flexibility encompasses diverse adaptive systems like individual learning, social learning, and the adaptive immune system.
  • These mechanisms evolved to address environmental variations across timescales from milliseconds to millennia.
  • Environmental unpredictability necessitates creative adaptive strategies involving exploration and selective retention.

Purpose of the Study:

  • To explore the mechanisms and evolutionary significance of phenotypic flexibility.
  • To understand how phenotypic flexibility systems interact with genetic evolution.
  • To investigate the role of random innovation and selective retention in adaptation.

Main Methods:

  • Conceptual analysis of evolutionary and learning theories.
  • Comparison of phenotypic flexibility mechanisms with Bayesian inference.
  • Examination of gene-environment and gene-phenotype interactions.

Main Results:

  • Phenotypic flexibility provides adaptive solutions to non-stationary and fat-tailed environmental variations.
  • Systems of phenotypic flexibility employ exploration (innovation) and retention for adaptation.
  • Interactions between genes and phenotypic flexibility mechanisms are complex and bidirectional.

Conclusions:

  • Phenotypic flexibility is crucial for adapting to uncertain environments, complementing slower genetic evolution.
  • The interplay between genes and phenotypic flexibility is a key area of ongoing research.
  • Understanding these interactions offers insights into the evolution of complex adaptive systems.