A probabilistic model for distinguishing between sheep and goat postcranial remains

Wolfhagen, Jesse; Price, Max D.

Abstract

Distinguishing morphologically-similar taxa is a perennial problem for zooarchaeologists. As an example, zooarchaeological methods to distinguish sheep and goat bones are limited by the fact that diagnostic traits are not exclusive to each species. For this reason, we argue that sheep/goat bones should be considered probabilistically, not absolutely. That is, each bone should be considered as falling along a spectrum from sheep to goat. To that end, we present a probabilistic method for assigning taxonomic status to sheep/goat postcranial specimens. Suites of diagnostic traits present on each specimen are translated into probabilities, which we then use in simulations to estimate the number of sheep and goat bones. We apply our model to two assemblages: ‘Ain Dara (Syria) and Tell Sakhariya (Iraq). We evaluate the effectiveness of standard diagnostic traits, finding that distal tibias and second phalanges particularly problematic to identify to species. In addition, our probabilistic method improves the reliability and replicability of sheep/goat identifications in zooarchaeological assemblages by making explicit the diagnostic criteria used and providing clear standards that other projects can follow and thus be directly compared.

Citation

Wolfhagen, J., & Price, M. D. (2017). A probabilistic model for distinguishing between sheep and goat postcranial remains. Journal of Archaeological Science: Reports, 12, 625-631. https://doi.org/10.1016/j.jasrep.2017.02.022

• Journal Article Type: Article
• Acceptance Date: Feb 14, 2017
• Online Publication Date: Apr 4, 2017
• Publication Date: 2017-04
• Deposit Date: Mar 7, 2023
• Journal: Journal of archaeological science, reports.
• Print ISSN: 2352-409X
• Electronic ISSN: 2352-4103
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Pages: 625-631
• DOI: https://doi.org/10.1016/j.jasrep.2017.02.022
• Public URL: https://durham-repository.worktribe.com/output/1180219