4.3 Article

Ecomorphological analysis of bovid mandibles from Laetoli Tanzania using 3D geometric morphometrics: Implications for hominin paleoenvironmental reconstruction

Journal

JOURNAL OF HUMAN EVOLUTION
Volume 114, Issue -, Pages 20-34

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jhevol.2017.09.010

Keywords

Australopithecus afarensis; Pateoecology; Chewing mechanics; Dietary adaptations; Functional morphology

Funding

  1. Professional Staff Congress-City University of New York Research Award Program

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The current study describes a new method of mandibular ecological morphology (ecomorphology). Three-dimensional geometric morphometrics (3D GM) was used to quantify mandibular shape variation between extant bovids with different feeding preferences. Landmark data were subjected to generalized Procrustes analysis (GPA), principal components analysis (PCA), and discriminant function analysis (DFA). The PCA resulted in a continuum from grazers to browsers along PC1 and DFA classified 88% or more of the modern specimens to the correct feeding category. The protocol was reduced to a subset of landmarks on the mandibular corpus in order to make it applicable to incomplete fossils. The reduced landmark set resulted in greater overlap between feeding categories but maintained the same continuum as the complete landmark model. The DFA resubstitution and jackknife analyses resulted in classification success rates of 85% and 80%, respectively. The reduced landmark model was applied to fossil mandibles from the Upper Laetolil Beds (similar to 4.3-3.5 Ma) and Upper Ndolanya Beds (similar to 2.7-2.6 Ma) at Laetoli, Tanzania in order to assess antelope diet, and indirectly evaluate paleo-vegetation structure. The majority of the fossils were classified by the DFA as browsers or mixed feeders preferring browse. Our results indicate a continuous presence of wooded habitats and are congruent with recent environmental studies at Laetoli indicating a mosaic woodland-bushland-grassland savanna ecosystem. (C) 2017 Elsevier Ltd. All rights reserved.

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