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Measuring Microbial Mutation Rates with the Fluctuation Assay
Published on: November 28, 2019
Fluctuation domains in adaptive evolution
Carl Boettiger1, Jonathan Dushoff, Joshua S Weitz
1Center for Population Biology, University of California, Davis, United States. cboettig@ucdavis.edu
Theoretical Population Biology
|October 22, 2009
Summary
This study introduces fluctuation domains to predict evolutionary rates. These domains, based on fitness landscape curvature, reveal predictable (dissipation) and variable (enhancement) evolutionary paths.
Area of Science:
- Evolutionary Biology
- Theoretical Ecology
- Quantitative Genetics
Background:
- Predicting evolutionary trajectories is crucial in adaptive dynamics and quantitative genetics.
- Understanding variation around the mean evolutionary path requires further theoretical development.
Purpose of the Study:
- To derive an expression for variation between parallel evolutionary trajectories.
- To introduce and define 'fluctuation domains' within the fitness landscape.
- To explore how landscape curvature influences evolutionary predictability.
Main Methods:
- Derivation of a novel mathematical expression for evolutionary trajectory variation.
- Analysis of fitness landscape curvature (positive and negative).
- Application to ecological scenarios involving competition for resources.
Main Results:
- Identified 'fluctuation domains' characterized by fluctuation dissipation (negative curvature, adaptive peaks) and enhancement (positive curvature, adaptive valleys/branching points).
- Demonstrated that landscape curvature dictates the predictability of evolutionary rates.
- Showcased these dynamics in models of implicit and explicit resource competition.
Conclusions:
- The derived expression provides a framework for understanding evolutionary unpredictability.
- Fitness landscape curvature is a key determinant of evolutionary fluctuation domains.
- This work offers new insights into the dynamics of phenotypic evolution under varying ecological pressures.
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