Published September 14, 2023 | Version v1
Journal article Open

Predicting body mass in Ruminantia using postcranial measurements

  • 1. University of Chicago

Description

Size plays an important role in mammalian ecology. Accurate prediction of body mass is therefore critical for inferring aspects of ecology in extinct mammals. The unique digestive physiology of extant ruminant artiodactyls, in particular, is suggested to place constraints on their body mass depending on the type of food resources available. Therefore, reliable body mass estimates could provide insight into the habitat preferences of extinct ruminants. While most regression equations proposed thus far have used craniodental predictors, which for ungulates may produce misleading estimates based on indirect relationships between tooth dimensions and size, postcranial bones support the body and may be more accurate predictors of body mass. Here, I use phylogenetically informed bivariate and multiple regression techniques to establish predictive equations for body mass in 101 species of extant ruminant artiodactyls based on 56 postcranial measurements. Within limb elements, stepwise multiple regression models were typically preferred, though bivariate models often received comparable support based on Akaike's information criterion scores. The globally preferred model for predicting mass is a model including both proximal and distal width of the humerus, though several models from the radioulna received comparable support. In general, widths of long bones were good predictors, while lengths and midshaft circumferences were not. Finally, I show that where the best elements for prediction are unavailable for fossil taxa, selection of the model with lowest percent prediction error for the lowest level clade to which the fossil can be assigned could be a productive and novel way forward for predicting mass and subsequently aspects of ecology in fossil mammals.

Notes

The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1002/jmor.21636.

Data availability

R scripts and data files have been deposited on Data Dryad. (https://doi.org/10.5061/dryad.8sf7m0ctf).

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Additional details

Identifiers

DOI
10.1002/jmor.21636
Other
oai:uchicago.tind.io:8040

Funding

Smithsonian Institution
Predoctoral Fellowship program
Field Museum
Women in Science Graduate Student Fellowship

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Organismal Biology and Anatomy