Portable, non-destructive colorimetry and visible reflectance spectroscopy paired with machine learning can classify experimentally heat-treated silcrete from three South African sources.

The objective of this study was to determine if visible reflectance spectroscopy and quantitative colorimetry represent viable approaches to classifying the heat treatment state of silcrete. Silcrete is a soil duricrust that has been used as toolstone since at least the Middle Stone Age. The ancient practice of heat treating silcrete prior to knapping is of considerable interest to paleolithic archaeologists because of its implications for early modern human complex cognition generally and the ability to manipulate the material properties of stone specifically. Here, we demonstrate that our quantitative, non-invasive, and portable approach to measuring color, used in conjunction with k-Nearest Neighbors "lazy" machine learning, is a highly promising method for heat treatment detection. Traditional, expert human analyst approaches typically rely upon subjective assessments of color and luster and comparison to experimental reference collections. This strongly visual method can prove quite accurate, but difficult to reproduce between different analysts. In this work, we measured percent reflectance for the visible spectrum (1018 variables) and standardized color values (CIEL*a*b*) in unheated and experimentally heat-treated silcrete specimens from three sources in South Africa. k-NN classification proved highly effective with both the spectroscopy and colorimetry data sets. An important innovation was using the heat treatment state predicted by the k-NN model for the majority of replicate observations of a single specimen to predict the heat treatment state for the specimen overall. When this majority voting approach was applied to the 746 individual observations in this study, associated with 94 discrete silcrete flakes, both spectroscopy and colorimetry k-NN models yielded 0% test set misclassification rates at the specimen level.

Ancient DNA and deep population structure in sub-Saharan African foragers.

Multiple lines of genetic and archaeological evidence suggest that there were major demographic changes in the terminal Late Pleistocene epoch and early Holocene epoch of sub-Saharan Africa1-4. Inferences about this period are challenging to make because demographic shifts in the past 5,000 years have obscured the structures of more ancient populations3,5. Here we present genome-wide ancient DNA data for six individuals from eastern and south-central Africa spanning the past approximately 18,000 years (doubling the time depth of sub-Saharan African ancient DNA), increase the data quality for 15 previously published ancient individuals and analyse these alongside data from 13 other published ancient individuals. The ancestry of the individuals in our study area can be modelled as a geographically structured mixture of three highly divergent source populations, probably reflecting Pleistocene interactions around 80-20 thousand years ago, including deeply diverged eastern and southern African lineages, plus a previously unappreciated ubiquitous distribution of ancestry that occurs in highest proportion today in central African rainforest hunter-gatherers. Once established, this structure remained highly stable, with limited long-range gene flow. These results provide a new line of genetic evidence in support of hypotheses that have emerged from archaeological analyses but remain contested, suggesting increasing regionalization at the end of the Pleistocene epoch.

Long-distance stone transport and pigment use in the earliest Middle Stone Age.

Previous research suggests that the complex symbolic, technological, and socioeconomic behaviors that typify Homo sapiens had roots in the middle Pleistocene <200,000 years ago, but data bearing on human behavioral origins are limited. We present a series of excavated Middle Stone Age sites from the Olorgesailie basin, southern Kenya, dating from ≥295,000 to ~320,000 years ago by argon-40/argon-39 and uranium-series methods. Hominins at these sites made prepared cores and points, exploited iron-rich rocks to obtain red pigment, and procured stone tool materials from ≥25- to 50-kilometer distances. Associated fauna suggests a broad resource strategy that included large and small prey. These practices imply notable changes in how individuals and groups related to the landscape and to one another and provide documentation relevant to human social and cognitive evolution.

Pattern and process in hominin brain size evolution are scale-dependent.

A large brain is a defining feature of modern humans, yet there is no consensus regarding the patterns, rates and processes involved in hominin brain size evolution. We use a reliable proxy for brain size in fossils, endocranial volume (ECV), to better understand how brain size evolved at both clade- and lineage-level scales. For the hominin clade overall, the dominant signal is consistent with a gradual increase in brain size. This gradual trend appears to have been generated primarily by processes operating within hypothesized lineages-64% or 88% depending on whether one uses a more or less speciose taxonomy, respectively. These processes were supplemented by the appearance in the fossil record of larger-brained Homo species and the subsequent disappearance of smaller-brained Australopithecus and Paranthropus taxa. When the estimated rate of within-lineage ECV increase is compared to an exponential model that operationalizes generation-scale evolutionary processes, it suggests that the observed data were the result of episodes of directional selection interspersed with periods of stasis and/or drift; all of this occurs on too fine a timescale to be resolved by the current human fossil record, thus producing apparent gradual trends within lineages. Our findings provide a quantitative basis for developing and testing scale-explicit hypotheses about the factors that led brain size to increase during hominin evolution.

An experimental study of hafting adhesives and the implications for compound tool technology.

Experimental studies of hafting adhesives and modifications to compound tool components can demonstrate the extent to which human ancestors understood and exploited material properties only formally defined by science within the last century. Discoveries of Stone Age hafting adhesives at archaeological sites in Europe, the Middle East, and Africa have spurred experiments that sought to replicate or create models of such adhesives. Most of these studies, however, have been actualistic in design, focusing on replicating ancient applications of adhesive technology. In contrast, this study tested several glues based on Acacia resin within a materials science framework to better understand the effect of each adhesive ingredient on compound tool durability. Using an overlap joint as a model for a compound tool, adhesives formulated with loading agents from a range of particle sizes and mineral compositions were tested for toughness on smooth and rough substrates. Our results indicated that overlap joint toughness is significantly increased by using a roughened joint surface. Contrary to some previous studies, there was no evidence that particle size diversity in a loading agent improved adhesive effectiveness. Generally, glues containing quartz or ochre loading agents in the silt and clay-sized particle class yielded the toughest overlap joints, with the effect of particle size found to be more significant for rough rather than smooth substrate joints. Additionally, no particular ochre mineral or mineral mixture was found to be a clearly superior loading agent. These two points taken together suggest that Paleolithic use of ochre-loaded adhesives and the criteria used to select ochres for this purpose may have been mediated by visual and symbolic considerations rather than purely functional concerns.