Predicting euarchontan body mass: A comparison of tarsal and dental variables.

Journal Article (Journal Article)

OBJECTIVE: Multiple meaningful ecological characterizations of a species revolve around body mass. Because body mass cannot be directly measured in extinct taxa, reliable body mass predictors are needed. Many published body mass prediction equations rely on dental dimensions, but certain skeletal dimensions may have a more direct and consistent relationship with body mass. We seek to evaluate the reliability of prediction equations for inferring euarchontan body mass based on measurements of the articular facet areas of the astragalus and calcaneus. METHODS: Surface areas of five astragalar facets (n = 217 specimens) and two calcaneal facets (n = 163) were measured. Separate ordinary least squares and multiple regression equations are presented for different levels of taxonomic inclusivity, and the reliability of each equation is evaluated with the coefficient of determination, standard error of the estimate, mean prediction error, and the prediction sum of squares statistic. We compare prediction errors to published prediction equations that utilize dental and/or tarsal measures. Finally, we examine the effects of taxonomically specific regressions and apply our equations to a diverse set of non-primates. RESULTS: Our results reveal that predictions based on facet areas are more reliable than most linear dental or tarsal predictors. Multivariate approaches are often better than univariate methods, but require more information (making them less useful for fragmentary fossils). While some taxonomically specific regressions improve predictive ability, this is not true for all primate groups. CONCLUSIONS: Among individual facets, the ectal and fibular facets of the astragalus and the calcaneal cuboid facet are the best body mass predictors. Since these facets have primarily concave curvature and scale with positive allometry relative to body mass, it appears that candidate skeletal proxies for body mass can be identified based on their curvature and scaling coefficients.

Full Text

Duke Authors

Cited Authors

  • Yapuncich, GS; Gladman, JT; Boyer, DM

Published Date

  • July 2015

Published In

Volume / Issue

  • 157 / 3

Start / End Page

  • 472 - 506

PubMed ID

  • 25821153

Electronic International Standard Serial Number (EISSN)

  • 1096-8644

Digital Object Identifier (DOI)

  • 10.1002/ajpa.22735


  • eng

Conference Location

  • United States