Sexual dimorphism in trait variability and its eco-evolutionary and statistical implications
Abstract
Biomedical and clinical sciences are experiencing a renewed interest in the fact that males and females differ in many anatomic, physiological, and behavioral traits. Sex differences in trait variability, however, are yet to receive similar recognition. In medical science, mammalian females are assumed to have higher trait variability due to estrous cycles (the 'estrus-mediated variability hypothesis'); historically in biomedical research, females have been excluded for this reason. Contrastingly, evolutionary theory and associated data support the 'greater male variability hypothesis'. Here, we test these competing hypotheses in 218 traits measured in >26,900 mice, using meta-analysis methods. Neither hypothesis could universally explain patterns in trait variability. Sex-bias in variability was trait-dependent. While greater male variability was found in morphological traits, females were much more variable in immunological traits. Sex-specific variability has eco-evolutionary ramifications including sex-dependent responses to climate change, as well as statistical implications including power analysis considering sex difference in variance.
Data availability
Data Availability: - The code and data generated during this study are freely accessible on github. [https://github.com/itchyshin/mice_sex_diff], as well as OSF [https://osf.io/25h4t/] - Original/source data (pre-cleaned dataset as downloaded from IMPC) can be downloaded from zenodo [DOI:10.5281/zenodo.3759701] - The supporting files also contain the full code workflow
Article and author information
Author details
Funding
Australian Research Council (DP180100818)
- Shinichi Nakagawa
NIH Common Fund (UM1-H G006370)
- Jeremy Mason
Australian Research Council Fellowship (DE180101520)
- Alistair M Senior
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Zajitschek et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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