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Evolution in fluctuating environments: A generic modular approach.

Bnaya Steinmetz¹, Immanuel Meyer¹, Nadav M Shnerb¹

¹Department of Physics, Bar-Ilan University, Ramat-Gan, IL, 52900, Israel.

Evolution; International Journal of Organic Evolution

|September 13, 2022

Summary

This study introduces a general analytic framework to understand evolutionary dynamics in fluctuating environments. The new method simplifies calculating key evolutionary factors like fixation probability and time.

Keywords:

Competition chance of ultimate fixation fitness fluctuations varying environment

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Area of Science:

Evolutionary biology
Population genetics
Mathematical modeling

Background:

Evolutionary processes are influenced by environmental fluctuations, affecting carrying capacities and selective pressures.
Existing methodologies for analyzing evolutionary dynamics in varying environments are limited to specific scenarios.
A general framework is needed to address the complex interplay of environmental change and evolutionary trajectories.

Purpose of the Study:

To develop a general analytic framework for studying evolutionary dynamics in fluctuating environments.
To provide a method for evaluating the mean and variance of mutant frequency changes.
To enable calculation of key evolutionary quantities in arbitrary environmental scenarios.

Main Methods:

Identification of elementary demographic processes (e.g., logistic growth, competition, sudden decline) as building blocks.
Evaluation of the mean and variance of mutant frequency changes for each elementary process.
Derivation of diffusion equations for arbitrary combinations of these demographic blocks.

Main Results:

A general analytic framework for evolutionary dynamics in fluctuating environments has been established.
The framework allows for the calculation of mean and variance of mutant frequency changes.
The method facilitates the derivation of diffusion equations for complex environmental scenarios.

Conclusions:

The presented framework offers a versatile tool for analyzing evolutionary dynamics under environmental variability.
Researchers can now more easily calculate critical evolutionary parameters such as fixation probability and fixation time.
This methodology advances our understanding of how fluctuating environments shape evolutionary outcomes.