Testing the fisherian mechanism: examining the genetic correlation between male song and female response in waxmoths
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Models of indirect (genetic) benefits sexual selection predict linkage disequilibria between genes that influence male traits and female preferences, owing to either non-random mate choice or physical linkage. Such linkage disequilibria, a genetic correlation, can accelerate the evolution of male traits and female preferences to exaggerated levels. But relatively few empirical studies have measured the genetic correlation between male traits and female responses in natural populations, and the findings of those few are mixed: often, genetic correlations are not found. We tested the above prediction in an acoustic pyralid moth, Achroia grisella, in which males attract females with a rhythmic train of sound pulses, and females respond only to song that exceeds a minimum pulse rhythm. Both male song rhythm and female threshold response are repeatable and heritable characters. Because female choice in A. grisella is based largely on male song, and males do not appear to provide direct benefits at mating, genetic correlation between male song rhythm and female response is expected. We studied 2 A. grisella populations, bred them according to a full-sib/half-sib design, split the progeny among 4 different environmental conditions, and measured the male song/female response genetic correlation in each of the 8 resulting groups. While song rhythm and response threshold were generally heritable, we found no evidence of significant genetic correlation between these traits. We suggest that the complexity of the various male song characters, of female response to male song, and of correlations between male song characters and between aspects of female response have mitigated the evolution of strong genetic correlation between song and response. Thus, exaggerated levels of trait development may be tempered.
KeywordsAcoustic communication Mate choice Runaway selection Sexual selection Signal evolution
We thank Bethany Harris, Hannah Hohendorf and Chelsea Medlock (Univ. of Kansas) for assistance in the laboratory and Robin Cargel, Robert Danka (U.S. Dept. Agriculture, Baton Rouge, Louisiana) and Jeffrey Pettis (U.S. Dept. Agriculture, Beltsville, Maryland) for field assistance. Software for analyzing song parameters was developed with the assistance of Simon Gray (Cambridge Electronic Design) and LaRoy Brandt (Univ. Kansas). Critical reviews by Rafael Rodriguez and two anonymous referees greatly improved an earlier version of the manuscript. The project was supported financially by U.S. National Science Foundation grant IOB-0516634.
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