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Journal Article

Estimating the ontogenetic age and sex composition of faunal assemblages with Bayesian multilevel mixture models


Wolfhagen,  Jesse Langdon
Department of Archaeology, Max Planck Institute of Geoanthropology, Max Planck Society;

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Wolfhagen, J. L. (2024). Estimating the ontogenetic age and sex composition of faunal assemblages with Bayesian multilevel mixture models. Journal of Archaeological Method and Theory, 31(2): s10816-023-09611-y, pp. 507-556. doi:10.1007/s10816-023-09611-y.

Cite as: https://hdl.handle.net/21.11116/0000-000D-3D08-7
Understanding the ontogenetic age and sex composition of zooarchaeological assemblages can reveal details about past human hunting and herding strategies as well as past animal morphology and behavior. As such, the accuracy of our estimates underlies our ability to ascertain details about site formation and gain insights into how people interacted with different animals in the past. Unfortunately, our estimates typically rely on only a small number of bones, limiting our ability to fruitfully use these estimates to make meaningful comparisons to theoretical expectations or even between multiple assemblages. This paper describes a method to use zooarchaeological remains with standard biometric measurements to estimate the ontogenetic age and sex composition of the assemblage, focused on immature, adult-sized female, and adult-sized male specimens. The model uses a Bayesian framework to ensure that the parameter estimates are biologically meaningful. Simulated assemblages show that the model can accurately estimate the biometry and composition of zooarchaeological assemblages. Two archaeological case studies also show how the model can be applied to produce tangible insights. The first, focused on sheep from Neolithic Pinarbaşı B, highlights the model’s ability to elucidate site formation and function. The second, focused on cattle remains from four assemblages from 7th-6th millennium BCE northwestern Anatolia, showcases how to use the mixture modeling results to compare assemblages to one another and to specific hypotheses. This modeling framework provides a new avenue for investigating long-term trajectories in animal biometry alongside contextual analyses of past human choices in butchery and consumption.