Assessing bite force estimates in extinct mammals and archosaurs using phylogenetic predictions

Sakamoto, Manabu (2021) Assessing bite force estimates in extinct mammals and archosaurs using phylogenetic predictions. Palaeontology, 64 (5). pp. 743-753. ISSN 0031-0239

Full content URL: https://doi.org/10.1111/pala.12567

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Assessing bite force estimates in extinct mammals and archosaurs using phylogenetic predictions
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Abstract

Bite force is an ecologically important biomechanical performance measure that is informative in inferring the ecology of extinct taxa. However, biomechanical modelling to estimate bite force is associated with some level of uncertainty. Here, I assess the accuracy of bite force estimates in extinct taxa using a Bayesian phylogenetic prediction model. I first fitted a phylogenetic regression model on a training set comprising extant data. The model predicts bite force from body mass and skull width while accounting for differences owing to biting position. The posterior predictive model has a 93% prediction accuracy as evaluated using leave-one-out cross-validation. I then predicted bite force in 37 species of extinct mammals and archosaurs from the posterior distribution of predictive models, generating posterior predictive distributions of null expectations given body mass, skull width and phylogenetic position. Biomechanically estimated bite forces from the literature fall within the posterior predictive distributions for all except four species of extinct taxa and are thus as accurate as predicted from body size and skull width, given the variation inherent in extant taxa and the amount of time available for variance to accrue. Biomechanical modelling remains a valuable means to estimate bite force in extinct taxa and should be reliably informative of functional performances and serve to provide insights into past ecologies.

Keywords:bite force, dinosaur, sabre-toothed cat, phylogenetic comparative methods, phylogenetic prediction, Regressions
Subjects:C Biological Sciences > C770 Biophysical Science
C Biological Sciences > C182 Evolution
F Physical Sciences > F641 Palaeontology
G Mathematical and Computer Sciences > G340 Statistical Modelling
Divisions:College of Science > School of Life Sciences
ID Code:46322
Deposited On:03 Sep 2021 09:10

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