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
Null hypothesis significance testing (NHST) is the most common statistical framework used by scientists, including archaeologists. Owing to increasing dissatisfaction, however, Bayesian inference has become an alternative to these methods. In this article, we review the application of Bayesian statistics to archaeology. We begin with a simple example to demonstrate the differences in applying NHST and Bayesian inference to an archaeological problem. Next, we formally define NHST and Bayesian inference, provide a brief historical overview of their development, and discuss the advantages and limitations of each method. A review of Bayesian inference and archaeology follows, highlighting the applications of Bayesian methods to chronological, bioarchaeological, zooarchaeological, ceramic, lithic, and spatial analyses. We close by considering the future applications of Bayesian statistics to archaeological research.
Toward the end of the Pleistocene, the world experienced a mass extinction of megafauna. In North America these included its proboscideans—the mammoths and mastodons. Researchers in conservation biology, paleontology, and archaeology have debated the role played by human predation in these extinctions. They point to traces of human butchery, such as cut marks and other bone surface modifications (BSM), as evidence of human-animal interactions—including predation and scavenging, between early Americans and proboscideans. However, others have challenged the validity of the butchery evidence observed on several proboscidean assemblages, largely due to questions of qualitative determination of the agent responsible for creating BSM. This study employs a statistical technique that relies on three-dimensional (3D) imaging data and 3D geometric morphometrics to determine the origin of the BSM observed on the skeletal remains of the Bowser Road mastodon (BR mastodon), excavated in Middletown, New York. These techniques have been shown to have high accuracy in identifying and distinguishing among different types of BSM. To better characterize the BSM on the BR mastodon, we compared them quantitatively to experimental BSM resulting from a stone tool chopping experiment using “Arnold,” the force-calibrated chopper. This study suggests that BSM on the BR mastodon are not consistent with the BSM generated by the experimental chopper. Future controlled experiments will compare other types of BSM to those on BR. This research contributes to continued efforts to decrease the uncertainty surrounding human-megafauna associations at the level of the archaeological site and faunal assemblage—specifically that of the BR mastodon assemblage. Consequently, we also contribute to the dialogue surrounding the character of the human-animal interactions between early Americans and Late Pleistocene megafauna, and the role of human foraging behavior in the latter’s extinction.
Manuscript accepted to the Handbook of Archaeological Sciences, 2nd ed. Forthcoming volume under contract (2022). Edited by M. Pollard, R.A. Armitage, and C.M. Makarewicz. Wiley.
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