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Metabolic rate shapes phenotypic covariance among physiological, behavioral, and life history traits in honeybees


Mugel, Stephen; Naug, Dhruba (2021), Metabolic rate shapes phenotypic covariance among physiological, behavioral, and life history traits in honeybees, Dryad, Dataset,


Metabolic rate is often cited as the fundamental rate that determines the rate of all biological processes by shaping energetic availability for the various behavioral and life history traits that contribute to performance. It has therefore been suggested that metabolic rate drives the widely observed covariance among these different levels of phenotypic traits. However, much of the work on this topic has relied on pairwise correlational analysis, thereby leaving an important gap in our understanding regarding the functional links that shape this phenotypic covariance, often referred to as pace-of-life. Using honeybees as an experimental model, we measured a large number of behavioral, life history and physiological traits in individual bees and used a structural equation model to characterize the phenotypic covariance structure among these traits. Following this with a path analysis, we demonstrate that variation in metabolic rate plays a fundamental proximate role in driving this phenotypic covariance structure in honeybees. We discuss the importance of these findings in the context of how interindividual variation in terms of slow-fast phenotypes may drive the phenotype of a group and the functional role metabolic rate might play in shaping division of labor and social evolution.


The dataset was collected through observational methods including behavioral sampling, respirometry, and physiological assay. The variables were converted into usable units, and then further transformed to achieve more unifrom variance in the models. 

Usage Notes

The final columns of data, labeled "2" are the transformed units used in the models presented in the paper. See the methods section for further detail.


National Science Foundation

Foundation for Food and Agriculture Research