An Evaluation of Landmark-Based Methods to Explore Tooth Score Morphology: A Case Study on Felids and Hyenids

Taphonomic studies aim to identify the modifying agents that intervene in bone assemblages found at archaeopaleontological sites. Carnivores may modify, accumulate, or scavenge skeletal parts inflicting tooth marks, including scores, on the cortical surface. Several works have studied tooth score mo...

Full description

Bibliographic Details
Main Authors: Mari Carmen Arriaza, Julia Aramendi, Lloyd A. Courtenay, Miguel Ángel Maté-González, Darío Herranz-Rodrigo, Diego González-Aguilera, José Yravedra
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/13/6/3864
Description
Summary:Taphonomic studies aim to identify the modifying agents that intervene in bone assemblages found at archaeopaleontological sites. Carnivores may modify, accumulate, or scavenge skeletal parts inflicting tooth marks, including scores, on the cortical surface. Several works have studied tooth score morphology to discern which carnivore group modified the bone assemblages, achieving different results. In the present study, different methods based on the use of landmarks and semilandmarks have been tested to describe and analyze the score profile cross-sections of spotted and brown hyenas, leopards, and lions. According to our results, the already published seven-landmark method is useful in order to differentiate between carnivore species from different families (e.g., felids and hyenids). Meanwhile, felid species (e.g., leopards and lions) cannot be consistently distinguished using any of the methods tested here. In contrast, hyenid species can be morphologically differentiated. On the other hand, the use of semilandmarks does not generally improve morphological characterization and distinction, but low numbers of landmarks and the inclusion of the score’s deepest point might provide the best results when semi-automatic semilandmark models are preferred to avoid sampling biases.
ISSN:2076-3417