An experimental approach on dynamic Occlusal Fingerprint Analysis to simulate use-wear development and localisation on Palaeolithic stone tools
Authors/Creators
- 1. University of Muenster
- 2. Senckenberg Research Institute and Natural History Museum Frankfurt/M., Germany; Goethe University, Institute of Ecology, Evolution, and Diversity, Frankfurt/M., Germany
- 3. TraCEr, MONREPOS Archaeological Research Centre and Museum for Human Behavioural Evolution, LEIZA, Neuwied; ICArEHB, Interdisciplinary Center for Archaeology and the Evolution of Human Behaviour, University of Algarve, Faro; Institute for Prehistoric and Protohistoric Archaeology, Johannes Gutenberg University, Mainz, Germany
- 4. TraCEr, MONREPOS Archaeological Research Centre and Museum for Human Behavioural Evolution, LEIZA, Neuwied; Institute of Archaeology, Faculty of Historical and Pedagogical Sciences, University of Wroclaw, Poland
- 5. TraCEr, MONREPOS Archaeological Research Centre and Museum for Human Behavioural Evolution, LEIZA, Neuwied
Description
Since the origin of the genus Homo, stone-based technologies were an important component of the toolkit of past humans. Studying the evidence left on stone tools is an important field in archaeology for understanding the evolution of human behaviour. Information about the use of stone tools in the past is encoded in the wear patterns left on the surface of a tool. Use-wear analysis investigates the mechanisms involved in the formation of diagnostic wear traces. Occlusal Fingerprint Analysis (OFA) is a well-established method in dental wear studies to simulate chewing actions and thus to locate and quantify kinematics of dental wear facets (see Kullmer et al. 2009, 2012). In a pilot study, we apply, for the first time, the OFA approach to a set of experimentally produced stone tools. The overarching goal is to build expectation models for where use-wear traces are expected to develop on stone tools based on their morphology and on the action performed. Methods include the use of robots in controlled experiments, 3D modelling and use-wear analysis. In producing expectation models, the results of this study confirm that the OFA method can contribute to differentiating between wear traces from human use and those from post-depositional alterations. Further, the method can be used for answering questions on tool performance because the software produces information regarding the amount of contact between the tool and the worked material.
Files
poster_obermaier_rausch.pdf
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