An Evolutionary Theory for the Variability Hypothesis

TL;DR

This paper introduces a biostatistical theory explaining how sex-based variability differences evolve in species, based on selectivity and variability interactions, supported by mathematical models for short-term and long-term behaviors.

Contribution

It presents a novel selectivity-variability principle and two mathematical models explaining variability evolution without assuming mean differences or fixed selectivity.

Findings

More variable subpopulations prevail with high selectivity.

Less variable subpopulations prevail with low selectivity.

Models demonstrate the theory's applicability to different distribution types.

Abstract

An elementary biostatistical theory based on a selectivity-variability principle is proposed to address a question raised by Charles Darwin, namely, how one sex of a sexually dimorphic species might tend to evolve with greater variability than the other sex. Briefly, the theory says that if one sex is relatively selective then from one generation to the next, more variable subpopulations of the opposite sex will generally tend to prevail over those with lesser variability. Moreover, the perhaps less intuitive converse also holds: if a sex is relatively non-selective, then less variable subpopulations of the opposite sex will prevail over those with greater variability. This theory requires certain regularity conditions on the distributions, but makes no assumptions about differences in means between the sexes, nor does it presume that one sex is selective and the other non-selective. Two mathematical models of the selectivity-variability principle are presented: a discrete-time one-step probabilistic model of short-term behavior with an example using normally distributed perceived fitness values; and a continuous-time deterministic model for the long-term asymptotic behavior of the expected sizes of the subpopulations with an example using exponentially distributed fitness levels.