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A framework for estimating the effects of sequential reproductive barriers: Implementation using Bayesian models with field data from cryptic species
Author(s) -
Peccoud Jean,
Pleydell David R. J.,
Sauvion Nicolas
Publication year - 2018
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.13595
Subject(s) - biology , reproductive isolation , gene flow , mating , bayesian probability , evolutionary biology , genetic algorithm , spermatophore , isolation (microbiology) , field (mathematics) , computational biology , genetics , statistics , gene , bioinformatics , demography , mathematics , genetic variation , population , sociology , pure mathematics
Abstract Determining how reproductive barriers modulate gene flow between populations represents a major step toward understanding the factors shaping the course of speciation. Although many indices quantifying reproductive isolation (RI) have been proposed, they do not permit the quantification of cross‐direction‐specific RI under varying species frequencies and over arbitrary sequences of barriers. Furthermore, techniques quantifying associated uncertainties are lacking, and statistical methods unrelated to biological process are still preferred for obtaining confidence intervals and P ‐values. To address these shortcomings, we provide new RI indices that model changes in gene flow for both directions of hybridization, and we implement them in a Bayesian model. We use this model to quantify RI between two species of the psyllid Cacopsylla pruni based on field genotypic data for mating individuals, inseminated spermatophores and progeny. The results showed that preinsemination isolation was strong, mildly asymmetric, and indistinguishably different between study sites despite large differences in species frequencies; that postinsemination isolation strongly affected the more common hybrid type; and that cumulative isolation was close to complete. In the light of these results, we discuss how these developments can strengthen comparative RI studies.