TY - JOUR
T1 - Differentiating between cutting actions on bone using 3D geometric morphometrics and Bayesian analyses with implications to human evolution
AU - Otárola-Castillo, Erik
AU - Torquato, Melissa G.
AU - Hawkins, Hannah C.
AU - James, Emma
AU - Harris, Jacob A.
AU - Marean, Curtis
AU - McPherron, Shannon P.
AU - Thompson, Jessica C.
N1 - Funding Information:
EOC, MGT, and HCH thank the members of the Laboratory for Computational Anthropology and Anthroinformatics and the Department of Anthropology at Purdue University. Contributions by MGT were partially financially supported by the National Science Foundation Graduate Research Fellowship Program (Grant No. 106469). EOC acknowledges the financial support from the Margo Katherine Wilke Undergraduate Research fund and College of Liberal Arts’ ASPIRE fund at Purdue University. SPM, JCT and EJ thank Emilija Nicolosi, Nicolas Zwyns, the UQ Archaeology Laboratory and the Max Planck Institute for Evolutionary Anthropology for support during data collection. CWM and JAH recognize the support of a grant from the John Templeton Foundation to the Institute of Human Origins at Arizona State University. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation or the John Templeton Foundation. All authors thank the managing editor and two annonymous reviewers for their time and helpful comments. This manuscript has certainly been improved through the peer-review process. Data and R-code are available upon request. Appendix A
Publisher Copyright:
© 2017 The Authors
PY - 2018/1
Y1 - 2018/1
N2 - Studies of bone surface modifications (BSMs) such as cut marks are crucial to our understanding of human and earlier hominin subsistence behavior. Over the last several decades, however, BSM identification has remained contentious, particularly in terms of identifying the earliest instances of hominin butchery; there has been a lack of consensus over how to identify or differentiate marks made by human and non-human actors and varying effectors. Most investigations have relied on morphology to identify butchery marks and their patterning. This includes cut marks, one of the most significant human marks. Attempts to discriminate cut marks from other types of marks have employed a variety of techniques, ranging from subjectively characterizing cut mark morphology using the naked eye, to using high-powered microscopy such as scanning electron microscopy (SEM) or micro-photogrammetry. More recent approaches use 3D datasets to obtain even more detailed information about mark attributes, and apply those to the fossil record. Although 3D datasets open promising new avenues for investigation, analyses of these datasets have not yet taken advantage of the full 3D surface morphology of BSM. Rather, selected cross-sectional slices of 3D scans have been used as proxies for overall shape. Here we demonstrate that 3D geometric morphometrics (GM), under the “Procrustes paradigm” and coupled with a Bayesian approach, probabilistically discriminates between marks caused by different butchery behaviors. At the same time, this approach provides a complete set of 3D morphological measurements and descriptions. Our results strengthen statistical confidence in cut mark identification and offer a novel approach that can be used to discriminate subtle differences between cut mark types in the fossil record. Furthermore, this study provides an incipient digital library with which to make future quantitative comparisons to archaeological examples, including contentious specimens that are key to understanding the earliest hominin butchery.
AB - Studies of bone surface modifications (BSMs) such as cut marks are crucial to our understanding of human and earlier hominin subsistence behavior. Over the last several decades, however, BSM identification has remained contentious, particularly in terms of identifying the earliest instances of hominin butchery; there has been a lack of consensus over how to identify or differentiate marks made by human and non-human actors and varying effectors. Most investigations have relied on morphology to identify butchery marks and their patterning. This includes cut marks, one of the most significant human marks. Attempts to discriminate cut marks from other types of marks have employed a variety of techniques, ranging from subjectively characterizing cut mark morphology using the naked eye, to using high-powered microscopy such as scanning electron microscopy (SEM) or micro-photogrammetry. More recent approaches use 3D datasets to obtain even more detailed information about mark attributes, and apply those to the fossil record. Although 3D datasets open promising new avenues for investigation, analyses of these datasets have not yet taken advantage of the full 3D surface morphology of BSM. Rather, selected cross-sectional slices of 3D scans have been used as proxies for overall shape. Here we demonstrate that 3D geometric morphometrics (GM), under the “Procrustes paradigm” and coupled with a Bayesian approach, probabilistically discriminates between marks caused by different butchery behaviors. At the same time, this approach provides a complete set of 3D morphological measurements and descriptions. Our results strengthen statistical confidence in cut mark identification and offer a novel approach that can be used to discriminate subtle differences between cut mark types in the fossil record. Furthermore, this study provides an incipient digital library with which to make future quantitative comparisons to archaeological examples, including contentious specimens that are key to understanding the earliest hominin butchery.
KW - Butchery
KW - Cut marks
KW - Multivariate methods
KW - Shape
KW - Taphonomy
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U2 - 10.1016/j.jas.2017.10.004
DO - 10.1016/j.jas.2017.10.004
M3 - Article
AN - SCOPUS:85044392529
SN - 0305-4403
VL - 89
SP - 56
EP - 67
JO - Journal of Archaeological Science
JF - Journal of Archaeological Science
ER -