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Dryad

Black and orange coloration predict success during male-male competition in the guppy

Cite this dataset

Guerrera, Alexa; Daniel, Mitchel; Hughes, Kimberly (2022). Black and orange coloration predict success during male-male competition in the guppy [Dataset]. Dryad. https://doi.org/10.5061/dryad.8pk0p2nr4

Abstract

Investigating how both intrasexual competition and intersexual mate choice act within a single system is crucial to understanding the maintenance and diversity of sexually-dimorphic traits. These two processes can act in concert by selecting for the same trait, or in opposition by selecting for different extremes of the same trait; they can also act on different traits, potentially increasing overall trait complexity. We asked whether male-male competition and female mate choice act on the same male traits using Trinidadian guppies, which exhibit complex male-limited color patterns and sexual size dimorphism. We used behavioral assays to assess the relationship between color and male competitive success and then compared our results to the plethora of data on female choice and male color in our study population. We found that males initiated more contests if they were larger than their competitor. Males won contests more often if they had more black coloration than their competitor, and the effect of black was stronger when the male had less orange than his competitor. Additionally, males won more often if they had either more structural color (iridescence) and more orange, or less structural color and less orange than their competitor, suggesting multiple combinations of color traits predict success. Females from our study population exhibit strong preferences for orange coloration. Thus, traits favored in male contests differ from those favored by intersexual selection in this population. Our results suggest that mate choice and male-male competition together promote increased color pattern complexity in this species.

Methods

Data was collected by observation of animal behavior in the lab and processed using raw data in R v 3.6.2.

Usage notes

R is the only software needed to open the data.

Funding

Natural Sciences and Engineering Research Council, Award: CGSM-427283-2012

National Science Foundation, Award: DEB-1740466