Estimating sexual selection and sexual isolation effects from mating frequencies

Citation
E. Rolan-alvarez et M. Caballero, Estimating sexual selection and sexual isolation effects from mating frequencies, EVOLUTION, 54(1), 2000, pp. 30-36
Citations number
28
Categorie Soggetti
Biology,"Experimental Biology
Journal title
EVOLUTION
ISSN journal
00143820 → ACNP
Volume
54
Issue
1
Year of publication
2000
Pages
30 - 36
Database
ISI
SICI code
0014-3820(200002)54:1<30:ESSASI>2.0.ZU;2-B
Abstract
Sexual selection (defined as the change in genotypic or phenotypic frequenc ies of mated versus total population frequencies) and sexual isolation (def ined as the deviation from random mating in mated individuals) show differe nt evolutionary consequences and partially confounded causes. Traditionally , the cross-product estimator has been used to quantify sexual selection, w hereas a variety of indexes, such as Yule V, Yule a YA, joint I, and others have been used to quantify sexual isolation. Because the two types of esti mators use different scales, the effects of both processes cannot be monito red simultaneously. We describe three new related statistics that quantify both sexual selection (PSS) and sexual isolation (PSI) effects for every ma ting pair combination in polymorphic traits, as well as measure their combi ned effects (PTI = PSI x PSS). The new statistics have the advantage of pro viding information on every mating pair combination, quantifying the effect s of sexual selection and isolation in the same units, and detecting asymme try in sexual isolation. The ability of the new statistics to ascertain the biological causes of sexual selection and sexual isolation are investigate d under different models involving distinct marginal frequencies, mate prop ensity, and mate choice coefficients. We also studied the use of classical isolation indexes applied on PSI coefficients, instead of on raw data. The use of the classical indexes applied to PSI coefficients considerably reduc es the statistical bias of the estimates, revealing the good estimation pro perties of the new statistics.