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Data from: Consistent female preference for rare and unfamiliar male color patterns in wild guppy populations

Citation

Valvo, Jennifer; Rodd, Helen; Hughes, Kimberly (2019), Data from: Consistent female preference for rare and unfamiliar male color patterns in wild guppy populations, Dryad, Dataset, https://doi.org/10.5061/dryad.70v5js4

Abstract

How genetic variation is maintained in ecologically important traits is a central question in evolutionary biology. Male Trinidadian guppies, Poecilia reticulata, exhibit high genetic variation in color patterns within populations, and field and laboratory studies implicate negative frequency-dependent selection in maintaining this variation. However, behavioral and ecological processes that mediate this selection in natural populations are poorly understood. We evaluated female mate preference in 11 natural guppy populations, including paired populations from high-and low-predation habitats, to determine if this behavior is responsible for negative frequency-dependent selection and to evaluate its prevalence in nature. Females directed significantly more attention to males with rare and unfamiliar color patterns than to males with common patterns. Female attention also increased with the area of male orange coloration, but this preference was independent of the preference for rare and unfamiliar patterns. We also found an overall effect of predation regime; females from high-predation populations directed more attention toward males than those from low-predation populations. Again, however, the habitat-linked preference was statistically independent from the preference for rare and unfamiliar patterns. Because previous research indicates that female attention to males predicts male mating success, we conclude that the prevalence of female preference for males with rare and unfamiliar color patterns across many natural populations supports the hypothesis that female preference is an important process underlying the maintenance of high genetic variation in guppy color patterns.

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Funding

National Science Foundation, Award: DEB-1740466