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Type: Journal article
Title: Incorporating intraspecific variation into dental microwear texture analysis
Author: Arman, S.
Prowse, T.
Couzens, A.
Ungar, P.
Prideaux, G.
Citation: Journal of the Royal Society Interface, 2019; 16(153):1-14
Publisher: Royal Society
Issue Date: 2019
ISSN: 1742-5689
Statement of
Samuel D. Arman, Thomas A. A. Prowse, Aidan M. C. Couzens, Peter S. Ungar and Gavin J. Prideaux
Abstract: Dental microwear texture analysis (DMTA) quantifies microscopic scar or wear patterns left on teeth by different foods or extraneous ingested items such as grit. It can be a powerful tool for deducing the diets of extinct mammals. Here we investigate how intraspecific variation in the dental microwear of macropodids (kangaroos and their close relatives) can be used to maximize the dietary signal inferable from an inherently limited fossil record. We demonstrate significant intraspecific variation for every factor considered here for both scale-sensitive fractal analysis and International Organization for Standardization surface texture analysis variables. Intraspecific factors were then incorporated into interspecific (dietary) analyses through the use of Linear Mixed Effects modelling, incorporating Akaike's Information Criterion to compare models, and testing models through independent cross-validation. This revealed that for each DMTA variable only a small number of intraspecific factors need to be included to improve differentiation between species. Including specimen as a random factor accounted for stochastic inter-individual variation, and facet, incorporated effects of sampling location. Intraspecific effects of ecoregion, microscope, tooth position and wear were often but not universally important. We conclude that models of microwear data that include intraspecific variation can improve the resolution of dietary reconstructions.
Keywords: kangaroos; metrology; microwear; modelling; palaeodiet; palaeontology
Rights: © 2019 The Author(s) Published by the Royal Society. All rights reserved.
RMID: 0030113494
DOI: 10.1098/rsif.2018.0957
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Appears in Collections:Mathematical Sciences publications

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