The 89th Annual Meeting of the American Association of Physical Anthropologists (2020)

Elucidating Paralouatta’s semi-terrestriality using the virtual morpho-functional toolbox


1Institute of Cognitive and Evolutionary Anthropology, University of Oxford, 2Department of Pathology and Anatomical Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 3Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, 4Department of Engineering, Shared Materials Instrumentation Facility (SMIF), Duke University, 5Department of Integrative Anatomical Sciences, Keck School of Medicine, University of Southern California, 6Division of Anthropology, American Museum of Natural History, 7New York Consortium in Evolutionary Primatology, American Museum of Natural History, 8School of Earth and Environmental Sciences, University of Manchester

April 16, 2020 4:15PM, Diamond 5 Add to calendar

Currently, there are no extant platyrrhine primates living in the main Caribbean islands. However, the fossil record of this island region has provided spectacular findings of different platyrrhines that were part of a diverse radiation showing exceptionally unusual morphologies. Among these, the Cuban genus Paralouatta represents some of the most enigmatic primates ever discovered in the Greater Antilles. Paralouatta’s post-cranium has been interpreted as showing signs of semi-terrestriality, a locomotor adaptation without known analog in platyrrhine evolutionary history. Nevertheless, whether or not the post-cranial traits of Paralouatta are truly indicative of semi-terrestriality is still uncertain. Using different virtual morpho-functional tools on a comparative sample of 3D talar models of diverse anthropoids representing diverse locomotor modes, this study aims to further assess if Paralouatta corresponds to a semi-terrestrial species. Specifically, finite-element analysis and geometric morphometrics were used to quantify biomechanical performance and shape, respectively, and then several machine-learning (ML) algorithms were trained using both the biomechanical and morphometric data to clarify the locomotor behavior of the fossil specimens. The ML algorithms categorized the Paralouatta fossils as arboreal quadrupeds. However, some of the obtained results are still suggestive of some level of terrestriality, hence all this information is discussed in terms of platyrrhine evolution. The proposed methodological approach can be certainly beneficial when elucidating the behaviors of other fossil species.

T.A.P: Leverhulme Trust Early Career Fellowship, ECF-2018-264; SA: NSF-BCS 1316947, AEI/FEDER EU (CGL2017-82654-P), and the Generalitat de Catalunya (CERCA Programme); BAP: National Science Foundation (BCS-1317047; BCS-1317029; BCS-1539741); The Leakey Foundation. 

Slides/Poster (pdf)