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Data From: Females alter their mate preferences depending on hybridization risk

Cite this dataset

Calabrese, Gina; Pfennig, Karin (2022). Data From: Females alter their mate preferences depending on hybridization risk [Dataset]. Dryad.


Mating with another species is often maladaptive because it generally results in no or low-fitness offspring. When hybridization is sufficiently costly, individuals should avoid mating with heterospecifics even if it reduces their ability to mate with high-quality conspecifics that resemble heterospecifics. Here, we used spadefoot toads, Spea multiplicata, to evaluate whether females alter their preferences for conspecific male sexual signals (call rate) depending on heterospecific presence. When presented with conspecific signals against a background including both conspecific and heterospecific signals, females preferred male traits that were most dissimilar to heterospecifics—even though these signals are potentially associated with lower-quality mates. However, when these same females were presented with a background that included only conspecific signals, some females switched their preferences, choosing conspecific signals that were exaggerated and indicative of high-quality conspecific mates. Because only some females switched their preferences between these two chorus treatments, there was no population-level preference for exaggerated male signals in the absence of heterospecifics. Thus, hybridization risk can impact mate choice and thereby alter patterns of sexual selection. These results also emphasize that reproductive barriers between species (such as mate choice) can be context-dependent, with important implications for the origins and maintenance of species boundaries.


Female S. mulitplicata mate preferences were measured via two-choice phonotaxis experiments in the laboratory at University of North Carolina-Chapel Hill.  Detailed data collection methods can be found in the manuscript and associated supplementary methods file.

Usage notes

The analysis code files can be opened using R (open source).  All analyses were conducted using R version 3.6.1.  The data files can be opened using excel, R (open source), or any software capable of reading .csv files.


National Science Foundation of Sri Lanka, Award: IOS 1555520

Sigma Xi

Oklahoma Biological Survey

American Museum of Natural History

University of North Carolina at Chapel Hill

Chiricahua Desert Museum