A quantitative analysis of wear distributions on Middle Stone Age marine shell beads from Blombos Cave, South Africa

Journal of Archaeological Science: Reports 29 (2020) 102137

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A quantitative analysis of wear distributions on Middle Stone Age marine shell beads from Blombos Cave, South Africa

T

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Amy Hattona,b, , Benjamin J. Schovilled,a, Jayne Wilkinsc,a a

Department of Archaeology, Human Evolution Research Institute, University of Cape Town, Rondebosch, 7701, South Africa Institute of Archaeology, University College London, 31-34 Gordon Square, London WC1H 0PY, United Kingdom c Australian Research Centre for Human Evolution, Environmental Futures Research Institute, Griffith University, Nathan Campus, Nathan QLD 4111, Australia d School of Social Science, University of Queensland, St Lucia QLD 4072, Australia b

A R T I C LE I N FO

A B S T R A C T

Keywords: Beadwork Symbolism Edge damage distribution method Still Bay Nassarius kraussianus

Early archaeological evidence for symbolically-mediated behaviour, which is our ability to create and share coded information between and within groups, comes from the African Middle Stone Age. Nassarius kraussianus shell beads, discovered in the Late Pleistocene, Still Bay archaeological deposits at Blombos Cave, Western Cape, South Africa, are some of the worlds earliest personal ornaments and their discovery significantly pushed back the origins of complex human symbolling. Further analyses of these beads led to the hypothesis that stringing arrangements at Blombos Cave changed through time, with important implications for the development and maintenance of social norms and style in early human populations. This hypothesis was supported by qualitative comparisons of archaeological and experimental wear distributions. Here, we present the results of a quantitative approach, applying a modified edge damage distribution method and statistical modelling to published diagrams (Vanhaeren et al. 2013, Journal of Human Evolution 64, 500–517) of wear on N. kraussianus shell beads. Our results support the original findings that different beading arrangements result in different wear distributions, and that the wear distributions on Blombos Cave beads exhibit temporal variability. However, our results vary with respect to which stringing arrangements best match the archaeological samples. Furthermore, we conclude that a combination of multiple processes may best explain the archaeological wear distributions, a finding more congruent with a long and complicated life history of curated objects like beads. These findings add to a growing record of early human social behaviours, and contribute methodologically to use-wear analyses of personal ornaments recovered from the archaeological record.

1. Introduction The maintenance and use of symbols are key characteristics of Homo sapiens. Humans use a variety of symbols, such as sounds, movements, marks, or objects, to communicate information to others, and the meaning of symbols is culturally-learned (Preucel and Bauer, 2001). Some of the early archaeological evidence for symbolically-mediated behaviour in the form of incised objects and personal ornaments comes from the African Middle Stone Age (Bouzouggar et al., 2007; d'Errico et al., 2005; Henshilwood et al., 2009; Henshilwood et al., 2018) and the Levantine Middle Palaeolithic (Vanhaeren et al., 2006). Incised objects and personal ornaments are considered to represent externallystored symbols (Wadley, 2003) because they are extrinsic to the body (not sound or gesture-based). The origins of externally-stored symbols are significant from an evolutionary perspective because they set the foundation for many of humanity's accomplishments in visual art and ⁎

communication, and because human capacities for language may be interlinked with our capacities to maintain and use externally-store symbols. Furthermore, externally-stored symbolic objects leave physical traces that are discoverable in the archaeological record, whereas language does not. Externally-stored symbols also provide insight on the origins and evolution of human sociality. Within the animal kingdom, humans are ‘pro-social’ outliers in that we rely heavily on non-kin for survival, organising ourselves into multi-scaler and flexible groups that depend on intra-group cooperation and inter-group competition (Marean, 2015; Marean, 2016). Humans can use symbols to communicate information about group membership, and one way to accomplish this is to adhere to social norms, which may have material correlates in lithic assemblage characteristics. For instance, regional point styles in the African MSA are suggested to be early evidence for different cultural traditions across time and space (Clark, 1992; Clark, 1982; Foley and Lahr, 2003;

Corresponding author. E-mail address: [email protected] (A. Hatton).

https://doi.org/10.1016/j.jasrep.2019.102137 Received 22 August 2019; Received in revised form 26 November 2019; Accepted 27 November 2019 2352-409X/ © 2019 Elsevier Ltd. All rights reserved.

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2015), the analysis presented here also serves to contribute methodologically to developing quantitative assessments and comparisons of shell beads between assemblages and sites.

McBrearty and Brooks, 2000, Willoughby 2006). At Sibudu Cave, on a smaller-scale, temporal variability through the sequence in tool types and core reduction strategies is interpreted as reflecting changing styles and cultural traditions (Conard and Will, 2015). Stone tools, however, do not generally have high visibility, and their form is linked to functional and economic factors. For those reasons, stone tool variability may rather reflect differences related to unintentional technological style (Sackett, 1985), communities of learning and practice (Wenger, 1999), and/or adaptions to local environmental pressures. Personal ornaments are a more visible avenue through which early humans may have expressed style and communicated information about group identity. Humans today use beads to decorate their hair, body, and clothes, and beadwork characteristics (material, association, size, and location) are known to actively communicate ethnic and cultural affiliations (Hodder, 1982). Beads are recovered from archaeological deposits across southern Africa; the manufacture of ostrich eggshell beads seems to be a long and widespread tradition through the terminal Pleistocene and Holocene (d’Errico et al., 2012; Collins and Steele, 2017; Steele et al., 2016). The earliest known beads to date have been recovered in Late Pleistocene deposits in the Levant where they date to ~100 ka (Vanhaeren et al., 2006). In North Africa, Nassarius gibbosulus shell beads were discovered at Oued Djebenna and Tarforalt (Grotte des Pigeons), where they date to ~90 ka and ~82 ka, respectively (Bouzouggar et al., 2007; d’Errico et al. (2009); Vanhaeren et al., 2006). In South Africa, the earliest evidence for beads is from Border Cave, where a perforated Conus ebraeus shell has been recovered from an infant burial dated to ~76 ka (d’Errico and Backwell, 2016). A small sample of possible beads on Afrolittorina africana dated to more than 70 ka have also been recovered from Sibudu Cave (d’Errico et al., 2008). As early as 100 thousand years ago marine shells were collected for their aesthetic properties at Pinnacle Point 13B, but they were not perforated and there is no evidence they were strung (Jerardino and Marean, 2010). Use wear analysis of perforated shells is used to determine whether they were used as personal ornaments. Smoothed perforations, localised abrasion and facets are evidence that the shells were modified by friction due to their rubbing against thread, skin, or other beads (Bouzouggar et al., 2007; d’Errico and Backwell, 2016; d'Errico et al., 2005; d’Errico et al., 2009; d’Errico et al. (2008); Vanhaeren et al., 2006). At Blombos Cave, beads made from N. kraussianius shells have been excavated from the M1 and Upper M2 phases in association with Still Bay points (d'Errico et al., 2005; Vanhaeren et al., 2013). Use-wear analysis has been used to investigate how the Blombos beads may have been strung, and to investigate temporal changes in stringing arrangements. Based on comparisons with experimentally-strung N. kraussianius beads, Vanhaeren et al. (2013) argued that bead stringing arrangements, and thus social norms about beadwork manufacture and design, changed through time in the MSA levels at Blombos Cave. This result supports an early chronology for the kind of stylistic variability in personal ornamentation that characterises our species. Here, building on the work of Vanhaeren et al. (2013), we further investigate the question of stringing arrangements and change through time at Blombos Cave. We apply a modified edge damage distribution method (Bird et al., 2007; Schoville, 2010, 2014; Schoville et al., 2016; Wilkins et al., 2015) and statistical modelling to the published diagrams of wear patterns provided by Vanhaeren et al. (2013). Because Vanhaeren et al. (2013) have published their complete raw dataset of wear distributions, we are able to apply a quantitative method to further test their hypotheses that (1) different beading arrangements result in different wear distributions, (2) the wear distributions on Blombos Cave beads are similar to the experimental wear distributions, and (3) the wear distributions on Blombos Cave beads exhibit temporal variability. As this edge damage distribution method has previously only been applied to stone tools (Bird et al., 2007; McPherron et al., 2014; Schoville, 2010, 2014; Schoville et al., 2016; Werner and Willoughby, 2018; Wilkins and Schoville, 2016; Wilkins et al., 2012; Wilkins et al.,

2. Background 2.1. Blombos Cave Blombos Cave is located on the southern coast of South Africa, 25 km west of the town of Still Bay. Excavations have exposed several meters of well-preserved stratified archaeological deposits (Henshilwood et al., 2001a). The stratigraphic sequence consists of Later Stone Age deposits stratified above four MSA occupation phases, artefacts from the latter being the focus of this manuscript. The four occupation phases in the MSA from the top to the bottom are the M1, Upper M2, Lower M2, and M3. The M1 and Upper M2 phases contain lithic artefacts consistent with a Still Bay designation, including finelymade, lanceolate bifacial points (Henshilwood et al., 2001a; Mourre et al., 2010; Soriano et al., 2015; Villa et al., 2009). They also contain the perforated shell beads discussed here, as well as engraved pieces of ochre, bone tools, an engraved bone fragment, an ochre drawing, and human teeth (d'Errico et al., 2001; d'Errico et al., 2005; d'Errico and Henshilwood, 2007; Grine et al., 2000; Henshilwood et al., 2001b; Henshilwood et al., 2009; Henshilwood et al., 2011; Henshilwood et al., 2018; Vanhaeren et al., 2013). The M1 and Upper M2 levels at Blombos Cave have been robustly dated using various methods, including optically stimulated luminescence, thermoluminescence, and electron spin resonance to between ~71 and 76 ka (Henshilwood et al., 2002; Jacobs et al., 2013; Jacobs et al., 2019; Tribolo et al., 2006). 2.2. N. kraussianius beads at Blombos Cave Sixty-eight N. kraussianius beads have been reported from the M1 and Upper M2 phases at Blombos Cave (d'Errico et al., 2005; Henshilwood et al., 2004; Vanhaeren et al., 2013). In the M1, beads were recovered from levels CA, CB, CC, and CD. In the Upper M2, beads were recovered from levels CF and CFA. Some of the archaeological beads were excavated from closely-associated ‘groups’ composed of between two and 24 beads, hypothesised to each constitute a single beadwork, lost or disposed in a single event (Vanhaeren et al. 2013). Groups 1–5 were recovered from levels CA/CB/CC, and groups 6–7 were recovered from level CC. The apertures of the shells exhibit microchipping of the outer prismatic layer, consistent with intentional perforation using bone points (d'Errico et al., 2005). Use wear analyses revealed that the shells have been exposed to regular friction, which generated wear facets on the parietal walls and outer lips, and smoothing of the perforation (d'Errico et al., 2005). The wear facets exhibit “distinctly-oriented” 1 µm wide striations, and often flatten the outer lip or create a concave surface on the lip close to the anterior canal (d'Errico et al., 2005:16). A similar concave facet is often seen on the opposite of the aperture on the parietal wall. The recorded use wear characteristics and locations are consistent with the shells rubbing against thread, skin or other beads (d’Errico et al., 1993). Vanhaeren et al., (2013) further investigated use wear on the Blombos Cave N. kraussianius beads with a focus on determining whether use wear distributions varied through time. This investigation was coupled with a set of experiments with N. kraussianius beads in six different stringing arrangements. The experimental beads were strung using three strands of 0.5 mm cotton thread. Three different wear scenarios were carried out, but the experimental shells only regularly developed wear in the scenario where the strands were soaked every 15 mins in a mixture of water, vinegar, and ochre powder and shaken in a sieve shaker for 3 h (Vanhaeren et al., 2013). The resulting wear distributions on the experimental beads were then compared to the archaeological assemblages from Blombos Cave. 2

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Fig. 1. Applying edge damage distribution method to experimental arrangement b (“continuous stringing with same orientation”), image adapted from Vanhaeren et al. (2013). The grey shaded area indicates areas which were ascribed as use-wear in the original study. The blue and yellow lines show the polyline that was generated using ArcGIS in this study. “Edge” represents unmodified shell edge. “Wear” represents modified shell edge.

Table 1 Number of Blombos shell beads according to arrangement, group and layer. Broken shell beads were excluded from analysis. Total number beads

Number of analysed beads

b c e f Total

6 6 6 6 24

6 6 5 6 23

CA CB/CBA CC CA/CB/CC CD CF/CFA Total 1 2 3 4 5 6 7 Isolated Total

6 8 30 21 1 2 68 7 2 2 12 5 24 4 12 68

6 8 25 20 1 1 61 7 2 1 12 5 20 3 11 61

Arrangement, Group, Layer

Experimental

Archaeological

Stratigraphic Layers

Groups

Fig. 2. Diagram showing the two naming conventions for locations of wear. A) Naming convention based on the edge damage distribution method, applied in this study. B) Naming convention employed by Vanhaeren et al. 2013.

arrangement interpretations presented by Vanhaeren et al. (2013) are based exclusively on the wear locations (and not individual wear feature characteristics), the edge damage distribution method is an ideal approach for quantitatively testing their hypotheses.

Based on their results, Vanhaeren et al. (2013) argued that intra-group wear patterns are similar, consistent with the interpretation that they represent a single discarded beadwork. Furthermore, they state that wear characteristics differ through the Blombos Cave sequence. Archaeological beads from level CC were more similar to the experimental arrangement where beads are continuously strung in alternate orientation. In contrast, the beads from levels CA and CB were more similar to the experimental arrangement with knotted pairs of dorsallyjoined shells. For their analysis of wear distribution, Vanhaeren et al. (2013) created digital outlines of the 68 N. kraussianius beads from the MSA levels at Blombos, and the 36 experimental beads. On each outline, they mapped the wear locations with the aid of a microscope. For the archaeological beads, the presence of wear was tallied for each of four locations - the perforation, the outer lip, the parietal wall and the columella – and all possible combinations. These results were then compared qualitatively to the resulting experimental distributions to make interpretations about how the archaeological samples were strung. The presented data includes mapped use wear distributions for each individual bead within each sample set so that visual comparisons are possible, but as it is a complex dataset, the suggested similarities are not obviously apparent through visual inspection. While the data are perfectly suitable for statistical comparison, no statistical comparisons involving the wear distributions were presented. Because the stringing

3. Methods The edge damage distribution method was developed by Bird et al. (2007) to analyse patterns of edge damage on stone artefacts, allowing for inferences of function to be made. The method was first applied to a sample of convergent flakes (points), from Pinnacle Point Cave 13B (PP13B). A number of other studies have since adopted and adapted this method (Schoville et al., 2016; Schoville, 2014; McPherron et al., 2014; Wilkins et al., 2012; Schoville, 2010; Schoville & Brown, 2010; Werner & Willoughby, 2018). Schoville et al. (2016) improved the edge damage distribution method by implementing a modelling approach to analysing data and applied this to a number of archaeological assemblages as well as experimental stone artefacts. Statistical models of edge damage distribution were fit to each archaeological assemblage, using the experimental damage distributions as explanatory variables. A forward stepwise regression procedure was used to determine the best-fit model for each archaeological assemblage. This statistical procedure is an advance as it multivariate, less sensitive to small sample sizes and less susceptible to Type II errors (Schoville et al., 2016). The modified edge damage distribution method is applied here, as outlined by Schoville et al. (2016), allowing for precise mapping of usewear on shell beads. The wear patterns of N. kraussianus shell beads from stratigraphic layers and groups will be compared to experimental 3

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Fig. 3. Archaeological wear distributions of Blombos Middle Stone Age Nassarius kraussianus shell beads by layer. Ordered from the youngest (CA) to the oldest layer (CF/CFA).

were downloaded. These figures were placed onto a 1 × 1 cm grid in GIMP The GIMP Development Team, 2018 in order to match the 1 cm scale bar present on the figures. Digital images were georeferenced in ESRI ArcGIS 10.4, using grid corners as landmarks, allowing for precise measurement of wear distance. A polyline is traced around the shell perforation, with each section of wear, edge or alteration, coded as such. ArcGIS then automatically calculates the length of each polyline section (Fig. 1).

wear patterns in order to determine which pattern they best match and show whether there was a change in style of the N. kraussianus beadworks from Blombos Cave, South Africa. 3.1. Data acquisition High-resolution diagrams showing use-wear patterns on the Blombos N. kraussianus shell beads and their experimental counterparts, 4

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Fig. 4. Archaeological wear distributions of Blombos Middle Stone Age Nassarius kraussianus shell beads according to group as assigned by Vanhaeren et al. (2013).

to calculate the total length of each side (right or left) and scaled to 100, thereby creating 100 positions along each edge. This process removed the effect of size differences between shell perforations while standardising edge wear locations. The Excel template was created as a matrix of data, with each shell bead’s side and face (e.g. Specimen 36CA, dorsal left), and 100 columns representing the positions along the shell perforation, which are coded as either “1″ – indicating wear is present, or “0” -where wear is not present. Altered edges, edges which could not

A shapefile was created for each archaeological layer, group, and experimental arrangement. These shapefiles contain the specimen number, archaeological layer/experimental arrangement, face (dorsal or ventral) as well as the wear classification code (wear, edge, altered). ArcGIS measurements were standardised by measuring wear from the centre bottom of each perforation, up each side (left or right) to the centre top. The data from ArcGIS were input into an Excel template, and used

5

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Fig. 5. Wear distributions of experimental Nassarius kraussianus shell beads. An image of the corresponding experimental arrangement is visible in the top right corner of each plot, modified from Vanhaeren et al. 2013: Fig. 2.

wear, and thus could not be used to explain any archaeological wear patterns. One experimental and seven archaeological beads were excluded from analysis as they were broken along the shell perforation (dorsal) or the aperture (ventral). This was done as it is impossible to know whether the broken section exhibited wear or not. For clarity, all the experimental arrangements from Vanhaeren et al. (2013) are lowercase letters (b, c, e, and f), while the archaeological stratigraphic layers are upper-case (e.g., CA, CB, CC).

be assigned as use-wear by Vanhaeren et al. (2013), were coded as “wear”, following Wilkins et al. (2012). This is done in order to map the distribution of wear without an assumption about its cause, as the likelihood of taphonomic causes of wear in archaeological samples is high. The analysed sample presented here consists of 23 experimental beads and 61 archaeological beads (Table 1). Experimental arrangements a and d were not included in the analysis as they exhibited no 6

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2002; Hilborn & Mangel, 1997) and is, therefore, more appropriate for trying to understand archaeological questions. The data were imported into JMP 14.1.0, and a forward stepwise regression model was fitted to each archaeological layer and group. The procedure is that parameters with the lowest AIC are added first, and subsequent parameters are added and removed until the best-fit model is found (model with the lowest AIC). Each term is given equal weight to enter the model, but will explain different amounts of residual error. All experimental arrangements were added as explanatory variables. The ‘fit all possible models’ option was also selected in order to retrieve a model with the best-fit parameter as the only explanatory variable for each archaeological stratigraphic and group wear distribution.

Table 2 Single best-fit experimental parameter for each of the wear distributions of archaeological layers. Archaeological

Best-fit Parameter

AICc

R2

Stratigraphic Layers

CA CB/CBA CC CA/CB/CC CD CF/CFA

Arrangement Arrangement Arrangement Arrangement Arrangement Arrangement

b b c b f b

−4281.1 −4638.2 −4993.1 −4465.9 −3910.7 −3672.3

0.7276 0.619 0.2684 0.5993 0.1179 0.1984

Groups

1 2 3 4 5 6 7

Arrangement Arrangement Arrangement Arrangement Arrangement Arrangement Arrangement

b b b b b c c

−4355.7 −4167.1 −4144.8 −4414.7 −4317.8 −4927.2 −5019.4

0.7151 0.4672 0.4078 0.6151 0.5397 0.3132 0.0389

4. Results 4.1. Wear distributions 4.1.1. Stratigraphic layers Layers CA, CB/CBA and CA/CB/CC are all characterised by continuous wear along the dorsal perforation (positions 1–200). The ventral face has a lower frequency of wear, with low frequencies of wear along the columellar and parietal walls (position 200–300), and high frequencies of wear concentrated at the middle of the outer lip (position 350) (Fig. 3) Layer CC is characterised by continuous wear along the dorsal perforation (position 1–200). The ventral face has a fairly high frequency of wear, although not as continuous as the dorsal face. There is infrequent wear at the bottom of the columellar wall (position 200–220), wear frequency increases towards the parietal wall (position 250) and stays high with small fluctuations (Fig. 3). Layer CF/CFA and CD each only consist of one shell bead. CD is characterised by wear along the left dorsal (position 1–100), and wear along the columellar and parietal wall (position 190–350). Layer CF/ CFA exhibits wear along most of the perforation (position 20–150), and at the parietal wall and top of the outer lip (position 280–350).

For data analysis, positions were renamed for ease of analysis (see Fig. 2), where 1–100 was left dorsal, 101–200 right dorsal, 201–300 left ventral, and finally, 301–400 the right ventral, following Schoville et al. (2016). Vanhaeren et al. (2013: Table 1) described the use-wear patterns on the Blombos shell beads according to shell anatomy, shells were described as having use-wear in four distinct locations, the perforation (P), outer lip (L), parietal wall (W) and the columella (C). The anatomical assignment of use-wear corresponds to the positions (1–400) as described by the edge damage distribution method here (Fig. 2). Wear data for each of these positions (1–400) was summed according to archaeological layer, group and experimental arrangement allowing for the frequency of wear at each position to be established. For example, in arrangement ‘c’ (“knotting with floating pairs of dorsally joining shells”, see Fig. 5) there are 6 beads, if all of these beads show wear at position 140 then the frequency of wear for that position is 6. The frequency plots are a good visual indication of the aggregated wear pattern for each unit of analysis (archaeological layer, group and experimental arrangement). Frequency of wear plots for each layer, group and arrangement were created using the ‘geom_bar’ function in the R statistical programming (R Core team, 2018) package ggplot2 (Wickham, 2016). The frequency plots were examined in order to identify any patterns or similarities between the archaeological and experimental wear distributions. All R code is available in the supplementary material.

4.1.2. Groups Groups 1–5 are characterised by continuous wear on the dorsal face along the perforation (positions 1–200). Wear on the ventral face in concentrated in positions 300–400, along the outer lip (Fig. 4). Groups 6 and 7 also show continuous wear on the dorsal face along the perforation. The ventral face has more wear than in groups 1–5, with high frequencies of wear along most of the ventral face, excluding positions 200–210. These positions on the columellar wall show no wear in both group 6 and 7 (Fig. 4).

3.2. Model fitting Frequency of wear data for each layer, group and arrangement was converted to relative frequency of wear. This was done by dividing the sum of wear in a position by the sum of wear for all positions for that arrangement. The calculation of relative frequency was done in order to correct for different sample sizes between and within the experimental and archaeological samples. Models were fitted in an attempt to describe variability of the wear patterns. Experimental wear distributions were treated as explanatory variables and assessed against wear distributions of archaeological layers and groups. Model fit can be compared through the use of an Information Criterion (Hilborn & Mangel, 1997), Akaike’s Information Criterion (AIC) was used to compare models in this study. This is done by balancing the trade-off of a model which underfits the data (too simple) or a model which overfits the data (too complex), thereby identifying the model which optimally describes the variation in the data (Burnham & Anderson, 2002). The model fitting approach follows Schoville et al. (2016) and is an improvement on previous application of the edge damage distribution method, which relied on hypothesis testing only. The model fitting approach allows for multivariate analysis which is less sensitive to small sample sizes (Burnham & Anderson,

4.1.3. Experimental Arrangement b has high frequency of wear along the perforation, concentrated at the top of the perforation (position 100), wear along the ventral face is discontinuous, with low frequencies at the columellar wall and outer lip (positions 210–220 and 330–360). Arrangement c has discontinuous wear along the perforation, with highest frequency of wear at position 220–240. There is no wear on the ventral face. Only one shell in Arrangement e (“knotting with floating pairs of ventrally joining shells”) exhibited wear, located along the perforation (position 160–240 and 280–290). Arrangement f (“continuous stringing with alternate orientation”) is characterised by high frequencies of discontinuous wear along the dorsal and ventral face, with the highest frequencies along the perforation (positions 60–90 and 190–200) (Fig. 5). 4.2. Model fitting The best fit parameter for most archaeological stratigraphic layer wear distributions is arrangement b, while arrangement c and f are the best fit-parameters for layers CC and CD respectively (Table 2, Fig. 6). 7

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Fig. 6. Wear distribution plots for each archaeological layer (black), with corresponding best-fit parameters in colour. A sketch of the best fit experimental arrangement for each layer is visible to the right of each distribution (modified from Vanhaeren et al. 2013, Fig. 2).

The R-squared values are particularly high for the models fitted to layers CA, CB/CBA and CA/CB/CC (Table 2). The best fit parameter for groups 1–5 is arrangement b, while the best fit parameter for groups six and seven is arrangement c (Table 2). The R-squared values are fairly high for most of the groups, with the exception of group seven which has an R-squared value of 0.0389. The best fit parameter provides a general understanding, while the model fit allows for a more nuanced understanding of the processes

resulting in wear patterns. (Table 3). Layer CA’s wear distribution is best described by a model which incorporates all four experimental arrangements (b, c, e, f), with arrangement b contributing the most. This layer’s model has the highest R-squared value (0.8428) and is therefore well described by the parameters. Layer CB/CBA is best described by a model that incorporates all experimental arrangements, with arrangement c contributing the most explanation for the variation in the data. 8

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Fig. 7. Wear distribution plots for each archaeological group (black), with corresponding best-fit parameters in colour. A sketch of the best fit experimental arrangement for each layer is visible to the right of each distribution.

and f), with arrangement f contributing the most. The model however only explains 24% of the variation in archaeological shell bead wear (Rsquared = 0.2399, Table 3). Layer CF/CFA is best described by a model with all possible parameters, arrangement b contributes the most to the variation. Layer CA/CB/CC is also best described by a model which includes all experimental arrangements, with arrangements b and f contributing

Wear distributions of shell beads from layer CC are best described by a model which incorporates experimental arrangements b, c, and f, however this model only explains 32% of the variation in the data (Rsquared = 0.3199, Table 3), this is a slight improvement from the model which included only one parameter and had an R-squared value of 0.2684 (Table 2). Layer CD is best described by a model which incorporates all possible parameters (experimental arrangements b, c, e 9

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Table 3 Results of model-fitting experimental wear distributions to archaeological wear distributions. Parameter residual sum-of-squares percentage contribution in parentheses. Archaeological

Best fit model

AICc

R2

Stratigraphic Layers

CA CB/CBA CC CA/CB/CC CD CF/CFA

b(48%) + c(28%) + e(6%) + f(18%) b(40%) + c(22%) + e(8%) + f(30%) c(53%) + b(33%) + f(14%) b(38%) + f(35%) + c(17%) + e(10%) f(69%) + c(19%) + e(10%) + b(2%) b(61%) + c(23%) + f(9%) + e(7%)

−4494.71 −4794.56 −5018.22 −4627.32 −3964.14 −3692.98

0.8428 0.7462 0.3199 0.7364 0.2399 0.2505

Groups

1 2 3 4 5 6 7

b(47%) + c(28%) + f(19%) b(46%) + f(31%) + e(12%) b(41%) + f(36%) + e(12%) b(38%) + f(34%) + c(19%) b(38%) + f(37%) + c(15%) c(53%) + b(32%) + f(15%) c(100%)

−4557.61 −4237.39 −4208.41 −4587 −4444.74 −4960.5 −5019.38

0.8306 0.5599 0.5026 0.7536 0.6667 0.3745 0.0389

+ + + + +

e(6%) c(11%) c(11%) e(10%) e(11%)

et al. (2013) reported that on eight of the archaeological beads, “some areas were affected by alteration and cannot be well described”. It is our understanding that these areas were not included in their considerations of wear distribution, because whether they represent use wear or taphonomic wear cannot be confidently determined. In our analysis, we included these areas. The strength of the edge damage distribution method is that it does not rely on interpretations about the proximate cause of individual damage marks. It is possible, and perhaps one of the strengths of our analysis, that our wear distributions also capture wear with a taphonomic origin. The approach applied by Vanhaeren et al. (2013) prioritises a single factor explanation for wear distributions. This is seen in the attribution of one experimental stringing arrangement to each assemblage of shell beads. The stepwise models applied in this study, however, show that wear distributions of nearly all archaeological layers and groups are best explained by a model that incorporates multiple experimental stringing arrangements, with most models incorporating all the experimental arrangements. In these models there is one experimental term which explained most of the variation in the wear patterns of the archaeological specimens, but the second term often also explains a large proportion of the variation. Unfortunately, there is no way of differentiating between a palimpsest of use traces and traces from a single untested bead arrangement, and this is a limitation of the current dataset that can only be resolved with further experimentation. Nonetheless, personal ornaments are the kinds of curated objects that may have long life histories with multiple processes acting on the object during its use-life and after its discard (Stiner et al., 2013). There is the possibility that shell beads at Blombos were valued objects, reused, and possibly strung in more than one arrangement during the course of their life history. Nassarius shells are relatively thick and durable (Bar-Yosef Mayer, 2015; Stiner et al., 2013), and based on the low frequency of beads with completely broken apertures at Blombos Cave (n = 5, 7%) one can assume that bead breakage was not the main factor responsible for their incorporation in the archaeological record. Rather, the majority of beads became part of the archaeological record through other processes that included discard or loss as a completed beadwork, as evidenced by the excavated groups of beads with similar wear patterns (Vanhaeren et al., 2013), and may have also included loss of beads during beadwork manufacture, and/or string failure (see Langley and O'Connor, 2015). N. kraussianus shells have a limited distribution on the landscape and there is a cost, though not a prohibitive one, to their collection. Shellfish for consumption (predominately brown mussel, Perna perna) were collected and brought back to the site during the M1 and M2 occupations at Blombos, even when the coast was located an average distance of 5–7 km away (Langejans et al. 2012). It is possible that everyday foraging activities also provided opportunities for the collection of N. kraussianus shells. Their best known source for collection

the most. The model fit for this model is very good, with 74% of the variation in the data explained by the model (R-squared = 0.7364, Table 3). Groups 1–5 are best described by models which incorporate all 4 experimental arrangements as explanatory variables. The model fit for all of these models is good, all R-squared values are above 0.5. Group 6 is best described by a model which incorporates 3 explanatory variables, arrangements c, b and f. Group 7 is best described by a model which only includes arrangement C as an explanatory variable, although the R-squared value for this model is very low (Table 3). 5. Discussion and conclusions The quantitative method applied here adds support to the hypothesis that different stringing arrangements create different wear pattern on shell beads. Many of the differing experimental stringing arrangements resulted in wear patterns that differed significantly from each other. The results also support the hypothesis that some beadworks were discarded in single events and these are recognised in what Vanhaeren et al. (2013) described as 'groups'. Many of the groups showed distinct distributions that differed significantly from other groups. Lastly, our results support the hypothesis that the lower levels at Blombos cave exhibit significantly different stringing arrangements than the upper levels, and that stringing arrangements varied temporally. However, our statistical modelling approach leads to different interpretations about which stringing arrangements characterise the archaeological assemblage (Table 4). In contrast to the findings of Vanhaeren et al. 2013, it was found that the single best-fit parameter for the single best-fit arrangement for groups 1–5 was arrangement b. Vanhaeren et al. (2013) had implied stringing arrangement c based on their qualitative assessment. The single best-fit parameter for groups 6–7 is arrangement c, whereas Vanhaeren et al. (2013) had suggested stringing arrangement f. Similarly, the single best-fit parameter for the lowest level of M1 (CC) is stringing arrangement c, and for the upper levels (CA, CB) stringing arrangement b. Vanhaeren et al. (2013) had suggested stringing arrangements f and c, respectively. There are two probable reasons for the differing results. Firstly, the wear distributions in this study are more detailed. In their consideration of wear distribution, Vanhaeren et al. (2013) collapsed this variation into four defined locations – the perforation, outer lip, parietal wall, and columella – and for the most part relied on qualitative assessments of the relative amounts of wear within each of the four locations. In this study, we analysed presence/absence data for 400 locations around the aperture, which provides a much more nuanced reflection of wear distributions, and these are quantitatively compared using the AIC model selection approach. A second contributing factor may be due to how ‘altered’ locations were handled in the two studies. Vanhaeren 10

Journal of Archaeological Science: Reports 29 (2020) 102137

c

b

b

f

b

c

b

b

today are estuaries, and they are readily available in the closest estuaries to Blombos Cave (Vanhaeren et al., 2013, d'Errico et al., 2005), where the Duiwenhoks and Goukou Rivers meet the Indian Ocean, 20 km west and east respectively. Once located, 100 shells can be foraged within 20 min (d'Errico et al., 2005). Sea levels have fluctuated (Ramsay & Cooper, 2002) over the period of time during which people have periodically occupied Blombos Cave, and reconstructions of the now submerged Palaeo-Agulhas Plain indicate that estuaries may have been located nearer the site in the past when sea levels were lower (Cawthra et al., 2019; Jacobs et al., 2019). Nassarius is known to seek shelter in wracks of estuarine grasses, which has been used by LSA hunter-gatherers for bedding (Liengme, 1987), but this is an unlikely mode of import for the MSA shells at Blombos Cave based on their restricted age class representation (d'Errico et al., 2005). There is of course also a possibility that other processes, such as taphonomy, contributed to the complex wear patterns exhibited by the archaeological shell beads. Surface modifications on faunal remains recovered from Blombos Cave show that trampling variably affected the archaeological assemblages; levels CF and CC exhibit relatively high frequencies of trampling marks, whereas level CD exhibits relatively low frequencies (Reynard and Henshilwood, 2018, 2019). While taphonomy on the shell beads have been previously explored, it was to confirm that the perforations had been anthropogenically produced and not a result of taphonomic processes (d'Errico et al., 2005; Vanhaeren et al., 2013). The effect of taphonomy on the wear patterns, in the form of smoothing and faceting, and contributing to some of the observed wear distributions, has not been thoroughly investigated. Our results suggest that multiple processes produce wear patterns recorded on archaeological specimens; taphonomy is one of these potential processes. However, experimental research programs that include proxies for postdepositional processes are required to understand the impact of taphonomy on shell bead wear distributions. The quantitative approach presented here builds on previous qualitative analyses and adds new insights to the life history of the Blombos shell beads that supports the interpretation of changing styles of personal ornamentation in the MSA. Beadworks, the strings and backing of which have not been preserved, were discarded or lost at Blombos Cave. Based on wear distributions on the beads that remain, the beadworks within levels CA and CB, are more similar to each other than they are to the beadworks in level CC. Though sample sizes are small, older beads from levels CD and CF seem to have come from other stringing variants. These changing styles were learned in a cultural environment, and had the potential to communicate group membership and other forms of identity (Preucel and Bauer, 2001). This evidence from Blombos Cave adds to a growing record of complex symbolic communications in the Late Pleistocene among some of the earliest members of our species (Bouzouggar et al., 2007; d'Errico et al., 2001; Henshilwood et al., 2009; Henshilwood et al., 2018; Wadley 2003). The edge damage distribution method employed here on shell beads for the first time contributes to an increased understanding of wear distribution variability due to different stringing arrangements. Our replicable methodology, which is based on digitisation and statistics, lends itself to comparative studies on beads from other archaeological contexts to further investigate the distribution various stringing styles through time and across space.

c implied

Wear located on perforation and outer lip Wear located on four locations Groups 1–5

f implied

– – Level CF/CFA

CRediT authorship contribution statement Amy Hatton: Methodology, Investigation, Formal analysis, Writing - original draft. Benjamin J. Schoville: Methodology. Jayne Wilkins: Methodology, Writing - original draft, Supervision.

Groups 6–7

–

– Level CA/CB/CC

–

f Wear located on three or four locations Level CC

Level CD

c Level CB/CBA

–

c

Wear located on perforation, on the outer lip, or both Wear types seen in both CA and CC

Wear occurs in high frequencies and is evenly distributed between locations 0–200 (dorsal) and 300–400 (ventral right), nearly absent between locations 200–300. Wear occurs in high frequencies and is evenly distributed between locations 0–200 (dorsal) and 300–400 (ventral right), nearly absent between locations 200–300. Wear occurs in high frequencies between locations 0–200 (dorsal),and is frequent and evenly distributed between 210 and 400 (ventral). Wear occurs in high frequencies and is evenly distributed between locations 0–200 (dorsal) and 300–400 (ventral right), low frequencies between locations 200–300. Wear occurs in high frequencies and is evenly distributed between locations 0–100 (dorsal left), and 190–350 (mainly ventral left). Small sample. Wear occurs in high frequencies and is evenly distributed between locations 20–150 (portion of dorsal), and 280–350 (portion of ventral). Small sample Wear occurs in high frequencies and is evenly distributed between locations 0–200 (dorsal) and 300–400 (ventral right), nearly absent between locations 200–300. Wear occurs in high frequencies is evenly distributed between locations 0–200 (dorsal), and 210–400 (ventral).

Wear distribution (also see wear distributions in Figs. 6–7) Interpreted stringing arrangement Wear distribution Sample

Level CA

This study Vanhaeren et al. 2013

Table 4 Summary comparison of interpretations from Vanhaeren et al. (2013) and this study.

Interpreted single best-fit stringing arrangement

A. Hatton, et al.

Acknowledgements We thank Marc Hatton and Nikolas Botha. Thank you also to our anonymous reviewers, who provided insightful and helpful comments. 11

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Funding This research was supported by grants to Amy Hatton by the DST NRF Centre of Excellence in Palaeosciences and the University of Cape Town. Jayne Wilkins is the recipient of DST NRF Centre of Excellence in Palaeosciences funding and an Australian Research Council Australian Discovery Early Career Award (DE190100160) funded by the Australian Government.

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