Cut marks on bone surfaces: influences on variation in the form of traces of ancient behaviour

Anthropogenic modification of a giant ground sloth tooth from Brazil supported by a multi-disciplinary approach

Identifying evidence of human modification of extinct animal remains, such as Pleistocene megafauna, is challenging due to the similarity of anthropogenic and non-anthropogenic taphonomic features observed under optical microscopy. Here, we re-investigate a Late Pleistocene ground sloth tooth from northeast Brazil, previously suggested as human-modified based only on optical observation. To characterize the macro- and micro-morphological characteristics of the marks preserved in this tooth and evaluate potential human modification, we used stereomicroscope and scanning electron microscopy (SEM) supplemented by energy dispersive spectroscopy (EDS), UV photoluminescence (UV/PL), synchrotron-based X-ray fluorescence (SR-XRF), and synchrotron micro-computed tomography (SR-µCT). These methods allowed us to discriminate non-anthropogenic taphonomic features (root and sedimentary damage), anthropogenic marks, and histological features. The latter shows the infiltration of exogenous elements into the dentine from the sediments. Our evidence demonstrates the sequence of anthropogenic and non-anthropogenic taphonomic modification of this tooth and supports its initial intentional modification by humans. We highlight the benefits of emerging imaging and spectral imaging techniques to investigate and diagnose human modification in fossil and archaeological records and propose that human modification of tooth tissues should be further considered when studying possibly anthropogenically altered fossil remains.

Using machine learning on new feature sets extracted from three-dimensional models of broken animal bones to classify fragments according to break agent

Distinguishing agents of bone modification at paleoanthropological sites is an important means of understanding early hominin evolution. Fracture pattern analysis is used to help determine site formation processes, including whether hominins were hunting or scavenging for animal food resources. Determination of how these behaviors manifested in ancient human sites has major implications for our biological and behavioral evolution, including social and cognitive abilities, dietary impacts of having access to in-bone nutrients like marrow, and cultural variation in butchering and food processing practices. Nevertheless, previous analyses remain inconclusive, often suffering from lack of replicability, misuse of mathematical methods, and/or failure to overcome equifinality. In this paper, we present a new approach aimed at distinguishing bone fragments resulting from hominin and carnivore breakage. Our analysis is founded on a large collection of scanned three-dimensional models of fragmentary bone broken by known agents, to which we apply state of the art machine learning algorithms. Our classification of fragments achieves an average mean accuracy of 77% across tests, thus demonstrating notable, but not overwhelming, success for distinguishing the agent of breakage. We note that, while previous research applying such algorithms has claimed higher success rates, fundamental errors in the application of machine learning protocols suggest that the reported accuracies are unjustified and unreliable. The systematic, fully documented, and proper application of machine learning algorithms leads to an inherent reproducibility of our study, and therefore our methods hold great potential for deciphering when and where hominins first began exploiting marrow and meat, and clarifying their importance and influence on human evolution.

Life and death at Dmanisi, Georgia: Taphonomic signals from the fossil mammals

There are many hypotheses regarding influences on the early hominin biogeographic spread into Eurasia; among them is increased meat-eating. Dmanisi in Georgia is one of the rare Early Pleistocene sites in Eurasia, and here we present primary information and analysis of the medium and large mammal taphonomy, contributing information about site formation and the hominins' interaction with the fauna. Nearly 85% of the specimens come from the B1 stratum. Relative abundances of mammal families demonstrate some bias toward carnivores, especially Canis borjgali, and diverse Felidae species. Bones display little weathering. Post-depositional surface modifications and matrix obscure many bone surfaces, but carnivore tooth marking is the most common bone surface modification from the nutritive taphonomic phase. Tooth pits are large, in the size range of those made by modern Crocuta crocuta and Panthera leo. Breakage variables indicate most breaks occurred while the bones were still fresh, many by carnivore consumption. Fairly even limb bone representation of herbivores suggests carcasses were introduced to the site nearly whole. Hominin tool marks are present in low frequencies, but they suggest a variety of behaviors. These marks are found on Equus, Palaeotragus, Bison, large cervids, Pseudodama, Canis, and Mammuthus. Some were made by filleting proximal limb segments, and so are likely indicative of early access to carcasses, while other marks suggest scavenging. The Homo taphonomic variables resemble the rest of the taphonomic signatures from the site with little weathering, a slightly higher percentage of their bones are whole, but only a few have probable carnivore damage. The assemblage characteristics are compared to modern actualistic and experimental assemblages, and it is concluded that Dmanisi presents a palimpsest of hyena denning, felid activity, hominin meat-eating and likely natural deaths.

Validity of the use of porcine bone in forensic cut mark studies

Porcine bone is often used as a substitute for human bone in forensic trauma studies, but little has been published on its comparative mechanical behavior. The factors affecting mechanical properties and therefore selection of bone models are complex and include the age of the animal at death, and physiological loading conditions, the latter being of particular relevance when using a quadrupedal animal as a human substitute. The regional variation in hardness of adult and infant porcine bones was investigated using Vickers' indentation tests and compared to published data for human limb bones to relate differences to inherent genetic effects and loading influences, and to examine the validity of the porcine-human model. Significant differences in hardness were observed both along and around the adult porcine humerus and femur, but no significant differences were found along the length of the infant bones. Significant differences were found between the forelimb and hindlimb, but only in the infant specimens. The hardness values for porcine adult cortical bone from the femur (52.23 ± 1.00 kg mm^-2 ) were comparable to those reported in the literature for adult human cortical bone from the fibula, ilium, and calcaneus. These data will help inform subject selection in terms of both species and bone type for use in future trauma studies.

Scratches and grazes: a detailed microscopic analysis of trampling phenomena

Sedimentary abrasion and postdepositional damage to fossil remains are of great interest if considering the possible distortion they could produce in the archaeological and paleontological record. Since their discovery, natural agents such as trampling phenomena have been a topic of great taphonomic interest. Nevertheless, the majority of investigation into these traces has focused almost exclusively on their differentiation from other anthropic agents such as cut marks. In recent years, advances into bone surface modification analysis via geometric morphometrics have proven useful for in-depth characterization of different taphonomic traces; including cut, tooth and percussion marks. Through this, a preliminary study of trampling marks using advanced 3D digital microscopy was able to detect differences between what have since been known as scratch and graze marks. The present study expands from this, developing a more detailed analysis of these traces. Here, we use advanced data science techniques to provide a means of understanding trampling mark variations, contributing to our knowledge of site formation processes. Our results show how scratch and graze marks are a product of progressional decay and changes in cortical hardness, providing a new means of understanding taphonomic processes. LAY DESCRIPTION: The study of microscopic bone surface modifications in archaeology and palaeontology is of great importance, allowing for a detailed reconstruction of the formation of a site and providing a means of interpreting the fossil register. The damage that sedimentary abrasion can produce, however, is likely to distort and influence these studies, thus requiring a detailed understanding of the different traces that can be found on different materials. Here, we use advanced 3D digital microscopy and pattern recognition algorithms to analyse the different marks produced in different sedimentological contexts, also controlling for other variables such as the state of the bone when buried, the type of bone and the time exposed to these types of damages. Through this detailed microscopic analysis of these types of damages, we are able to conclude that morphological variations in trampling marks are product of the state of decay when the bones are buried.

Deep learning and taphonomy: high accuracy in the classification of cut marks made on fleshed and defleshed bones using convolutional neural networks

Accurate identification of bone surface modifications (BSM) is crucial for the taphonomic understanding of archaeological and paleontological sites. Critical interpretations of when humans started eating meat and animal fat or when they started using stone tools, or when they occupied new continents or interacted with predatory guilds impinge on accurate identifications of BSM. Until now, interpretations of Plio-Pleistocene BSM have been contentious because of the high uncertainty in discriminating among taphonomic agents. Recently, the use of machine learning algorithms has yielded high accuracy in the identification of BSM. A branch of machine learning methods based on imaging, computer vision (CV), has opened the door to a more objective and accurate method of BSM identification. The present work has selected two extremely similar types of BSM (cut marks made on fleshed an defleshed bones) to test the immense potential of artificial intelligence methods. This CV approach not only produced the highest accuracy in the classification of these types of BSM until present (95% on complete images of BSM and 88.89% of images of only internal mark features), but it also has enabled a method for determining which inconspicuous microscopic features determine successful BSM discrimination. The potential of this method in other areas of taphonomy and paleobiology is enormous.

The trajectory of bone surface modification studies in paleoanthropology and a new Bayesian solution to the identification controversy

A critical issue in human evolution is how to determine when hominins began incorporating significant amounts of meat into their diets. This fueled evolution of a larger brain and other adaptations widely considered unique to modern humans. Determination of the spatiotemporal context of this shift rests on accurate identification of fossil bone surface modifications (BSM), such as stone tool butchery marks. Multidecade-long debates over the agents responsible for individual BSM are indicative of systemic flaws in current approaches to identification. Here we review the current state of BSM studies and introduce a novel probabilistic approach to identifying agents of BSM. We use control assemblages of bones modified by modern agents to train a multivariate Bayesian probability model. The model then identifies BSM agents with associated uncertainties, serving as the basis for a predictive probabilistic algorithm. The multivariate Bayesian approach offers a novel, probabilistic, and analytical method for BSM research that overcomes much of the bias that has typified previous, more qualitative approaches.

Earliest Human Presence in North America Dated to the Last Glacial Maximum: New Radiocarbon Dates from Bluefish Caves, Canada

The timing of the first entry of humans into North America is still hotly debated within the scientific community. Excavations conducted at Bluefish Caves (Yukon Territory) from 1977 to 1987 yielded a series of radiocarbon dates that led archaeologists to propose that the initial dispersal of human groups into Eastern Beringia (Alaska and the Yukon Territory) occurred during the Last Glacial Maximum (LGM). This hypothesis proved highly controversial in the absence of other sites of similar age and concerns about the stratigraphy and anthropogenic signature of the bone assemblages that yielded the dates. The weight of the available archaeological evidence suggests that the first peopling of North America occurred ca. 14,000 cal BP (calibrated years Before Present), i.e., well after the LGM. Here, we report new AMS radiocarbon dates obtained on cut-marked bone samples identified during a comprehensive taphonomic analysis of the Bluefish Caves fauna. Our results demonstrate that humans occupied the site as early as 24,000 cal BP (19,650 ± 130 ¹⁴C BP). In addition to proving that Bluefish Caves is the oldest known archaeological site in North America, the results offer archaeological support for the “Beringian standstill hypothesis”, which proposes that a genetically isolated human population persisted in Beringia during the LGM and dispersed from there to North and South America during the post-LGM period.