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

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.

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 Urheber:
Wolfhagen, Jesse Langdon1, Autor           
Affiliations:
1Department of Archaeology, Max Planck Institute of Geoanthropology, Max Planck Society, ou_3398738              

Inhalt

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Schlagwörter: Zooarchaeology, Biometry, Logarithmic size index (LSI), Domestication, Bayesian statistics
 Zusammenfassung: 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.

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Sprache(n): eng - English
 Datum: 2023-04-242023-05-252024-06
 Publikationsstatus: Erschienen
 Seiten: 50
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: Introduction
- Morphometric Sex Determination in Zooarchaeology
- Mixture Modeling in Zooarchaeology
A Bayesian Multilevel Mixture Model for Zooarchaeological Measurements
- Benefits of the Bayesian Multilevel Mixture Model
- Developing Prior Distributions from a Prior Assemblage
- Extending the Multilevel Analysis to Multiple Sites
- Interpreting Model Results: Measured, Modeled, and Full Assemblages
- Computational Details of the Bayesian Analysis
Testing the Bayesian Multilevel Mixture Model
- Simulated Assemblages
- Archaeological Case Studies
-- Single Assemblage: Biometric Analysis of Sheep from 7th Millennium BCE Central Anatolia (Pinarbaşı B)
-- Multiple Assemblages: Biometric Analysis of Cattle from 7th to 6th Millennium BCE Northwest Anatolia (Barcın Höyük, Ilıpınar Höyük, Menteşe Höyük)
Results
- Simulated Assemblages: Testing Model Accuracy
- Pinarbaşı B Sheep: The Impact of Immature Specimens
- 7th–6th Millennium BCE Northwest Anatolian Cattle: Examining Differences Between Assemblages
Discussion
Conclusions
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1007/s10816-023-09611-y
Anderer: gea0062
 Art des Abschluß: -

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Quelle 1

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Titel: Journal of Archaeological Method and Theory
  Andere : J Archaeol Method Theory
  Kurztitel : J Arch Meth Th
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Dordrecht : Springer Science + Business Media B.V
Seiten: - Band / Heft: 31 (2) Artikelnummer: s10816-023-09611-y Start- / Endseite: 507 - 556 Identifikator: ISSN: 1573-7764
ISSN: 1072-5369
CoNE: https://pure.mpg.de/cone/journals/resource/1573-7764