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An estimator of the Opportunity for Selection that is independent of mean fitness
Author(s) -
Waples Robin S.
Publication year - 2020
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/evo.14061
Subject(s) - statistics , selection (genetic algorithm) , estimator , variance (accounting) , biology , sample size determination , offspring , mathematics , econometrics , computer science , accounting , artificial intelligence , business , pregnancy , genetics
Variation among individuals in number of offspring (fitness, k ) sets an upper limit to the evolutionary response to selection. This constraint is quantified by Crow's Opportunity for Selection ( I ), which is the variance in relative fitness ( I = σ 2 k /( u k ) 2 ). Crow's I has been widely used but remains controversial because it depends on mean offspring number in a sample ( k ¯ ). Here, I used a generalized Wright‐Fisher model that allows for unequal probabilities of producing offspring to evaluate behavior of Crow's I and related indices under a wide range of sampling scenarios. Analytical and numerical results are congruent and show that rescaling the sample variance ( s 2 k ) to its expected value at a fixedk ¯ 2 removes dependence of I on mean offspring number, but the result still depends on choice ofk ¯ 2 . A new index is introduced, Δ I = Î – E ( Î drift ) = Î – 1/ k ¯ , which makes Î independent of sample k ¯ without the need for variance rescaling. Δ I has a straightforward interpretation as the component of variance in relative fitness that exceeds that expected under a null model of random reproductive success. Δ I can be used to directly compare estimates of the Opportunity for Selection for samples from different studies, different sexes, and different life stages.