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Related Concept Videos

Limits to Natural Selection01:38

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Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
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Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli
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Limiting fitness distributions in evolutionary dynamics.

Matteo Smerlak1, Ahmed Youssef2

  • 1Perimeter Institute for Theoretical Physics, 31 Caroline St. N., Waterloo, Canada, ON N2L 2Y5.

Journal of Theoretical Biology
|January 11, 2017
PubMed
Summary

Predicting evolution requires understanding fitness variation. This study identifies tail indices of fitness distributions as key to forecasting long-term evolutionary trajectories, going beyond short-term predictions.

Keywords:
Evolutionary dynamicsFisher fundamental theorem of natural selectionLimiting distribution

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Area of Science:

  • Evolutionary biology
  • Population genetics
  • Theoretical ecology

Background:

  • Natural selection drives evolution by acting on fitness variation.
  • Fisher's fundamental theorem relates short-term evolution rate to fitness variance.
  • Existing models struggle to predict long-term evolutionary dynamics due to evolving variance.

Purpose of the Study:

  • To develop a method for predicting long-term evolutionary trajectories from limited statistical information.
  • To identify key statistical properties of fitness distributions that govern future evolution.
  • To extend predictive capabilities beyond short-term evolutionary dynamics.

Main Methods:

  • Analysis of fitness distributions and their statistical properties.
  • Identification and application of tail indices for predicting distribution evolution.
  • Validation through numerical simulations of the Wright-Fisher model and genetic algorithms.

Main Results:

  • Tail indices of fitness distributions are identified as critical for predicting late-time evolution.
  • Location, scale, and shape of fitness distributions can be forecasted from initial tail index measurements.
  • The predictive pattern applies to both positive and negative selection, and diverse population structures.

Conclusions:

  • Tail indices offer a powerful tool for long-term evolutionary prediction.
  • This approach overcomes limitations of previous models, providing a more comprehensive understanding of evolutionary trajectories.
  • The findings are robust, supported by simulations across different evolutionary models.