The 82nd Annual Meeting of the American Association of Physical Anthropologists (2013)

Applying Anthropological Shape Analysis Techniques to Archaeological Research: Overcoming Problems and Exploring Possibilities


1Department of Anthropology, Durham University, 2Department of Archaeology, Durham University, 3Department of Archaeology, University of Aberdeen

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The last two decades have seen geometric morphometrics (GMM) revolutionise anthropological studies of morphological variation. Their statistical power and ready visualisation have allowed the teasing apart of complex causes of morphological variation, explaining them in readily interpretable ways, even to non-specialist audiences. This revolution in bioanthropology has been accompanied by similar revolutions in other fields of morphological research, including primatology, biology, and palaeontology. Despite this, it is relatively recently that archaeology, which shares many of the same materials and methods as bioanthropology, has started exploring the use of GMM.

In this paper we discuss the possibilities and problems faced when applying anthropological methods to archaeological data, using a number of case studies from our Anth/Arch morphometrics group at Durham University. The studies cross the boundaries of these disciplines and illustrate research questions in palaeopathology, migration studies, and zooarchaeology. Can GMM help us quantify disease processes ? Can they aid interpretation of human migration and social change on large and local scales? What can animal remains tell us about the human past, and the potential problems when studying species undergoing artifical selection of domestication, and/or used for human consumption?

Through the results of multiple bioarchaeological studies, we show that GMM have the potential to increase our understanding of the past in terms of aetiology of disease, and morphological affinities of both humans and their domesticates. We also highlight limitations to their application in archaeological contexts, and questions which are not readily answerable even with these advanced methods.

This research was funded by NERC, AHRC, The Leverhulme Trust, and Durham University.

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