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On Measurements of Phenotypic Parallel Evolution.

Jeff D Arendt, Joseph Travis, David N Reznick

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    Several metrics for phenotypic parallel evolution exist, but not all accurately measure evolutionary parallelism. The R-squared metric is unreliable and should be avoided when analyzing evolutionary trajectories.

    Keywords:
    evolutionary trajectorymeasurementmethodparallel evolutionparallelism

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    Area of Science:

    • Evolutionary biology
    • Quantitative genetics

    Background:

    • Phenotypic parallel evolution is a key concept in evolutionary biology.
    • Existing metrics for quantifying parallel evolution often rely on geometric interpretations of evolutionary trajectories.

    Purpose of the Study:

    • To evaluate the validity of different metrics used to measure phenotypic parallel evolution.
    • To identify reliable methods for quantifying the parallelism of evolutionary trajectories.

    Main Methods:

    • Geometric analysis of multivariate evolutionary trajectories.
    • Statistical evaluation of ANOVA-derived metrics, including interaction terms and R-squared values.

    Main Results:

    • Two metrics, the ANOVA interaction term and the angle between trajectories, align with the geometric definition of parallelism.
    • The R-squared metric derived from a one-factor ANOVA is shown to be unreliable for measuring parallelism.
    • The direction of multivariate trajectories, while intuitive, does not strictly adhere to the geometric definition of parallel evolution.

    Conclusions:

    • The R-squared metric should not be used to measure phenotypic parallelism.
    • Accurate quantification of parallel evolution requires careful consideration of ancestor-descendent relationships.
    • Researchers should be explicit about which aspect of evolutionary trajectories (angle, direction, or length) they aim to measure.