Journal of Archaeological Science 35 (2008) 2640–2648

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Acheulean variation and selection: does handaxe symmetry fit neutral expectations? Stephen J. Lycett* British Academy Centenary Research Project, SACE, University of Liverpool, Hartley Building, Brownlow Street, Liverpool, L69 3BX, UK

a r t i c l e i n f o

a b s t r a c t

Article history: Received 17 March 2008 Received in revised form 6 May 2008 Accepted 8 May 2008

It has been suggested that the property of symmetry observed in Acheulean handaxes was selected for functional, adaptive or social and aesthetic reasons. However, selectionist accounts of variation may be contrasted with the approach taken by population geneticists to molecular variation. Population geneticists always first assume a neutral pattern of variation for molecular data, and only look to nonneutral (e.g., selective) scenarios for pattern and variation in the face of strong evidence against this null model of neutral expectation. Here, using a combination of cultural transmission theory, morphometrics, and the principles of population genetics, (null) neutral expectations for Acheulean handaxe symmetry are tested. The results of the analyses are inconsistent with a null hypothesis of neutral expectation for patterns of handaxe symmetry variation. Rather, the results imply that the property of symmetry in Acheulean handaxes was subject to selection for functional, adaptive or social reasons. Ó 2008 Elsevier Ltd. All rights reserved.

Keywords: Handaxes Palaeolithic Lithic analysis Social transmission Cultural evolution Symmetry Neutral evolution Drift Selection

1. Introduction From the perspective of archaeological taxonomy and terminology, ‘handaxes’ of the Lower Palaeolithic are defined by the imposition of a long axis on artefact form by means of invasive bifacial knapping around the edge of a core, nodule or large flake blank (Gowlett, 2006; Isaac, 1977; Roe, 1976; Schick and Toth, 1993). This knapping process tends to result in a broadly symmetrical form, although the extent of such symmetry is known to vary widely across time and space (Wynn, 2002; Clark, 1994). Currently, classic handaxe forms are known from across Africa, western Asia, western Europe and the Indian subcontinent. Collectively, this archaeological phenomenon is referred to as the ‘Acheulean’, and is known to date from ca. 1.6 Mya to less than 200 Kya (Asfaw et al., 1992; Klein, 1999; Roche and Kibunjia, 1994; Clark, 1994). Inevitably, debates surrounding variability in the form of Acheulean handaxes across this vast geographic and chronological expanse have pervaded the literature for many decades (Bordes, 1961; Callow, 1986; Clark, 1994, 2001; Davidson and Noble, 1993; Gamble and Marshall, 2001; Gowlett, 1984, 1998, 2006; Goren-Inbar and Saragusti, 1996; Isaac, 1986; Lycett, 2007; Lycett and von

* Tel.: þ44 151 7945787. E-mail address: [email protected] 0305-4403/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.jas.2008.05.002

Cramon-Taubadel, 2008; Lycett and Gowlett, in press; McNabb et al., 2004; McPherron, 2000, 2006; Norton et al., 2006; Noll and Petraglia, 2003; Petraglia, 2006; Roe, 1968, 1976; Vaughan, 2001; Wynn, 1979, 1995; Wynn and Tierson, 1990). The symmetrical property of typical Acheulean handaxe forms has, in particular, been the subject of intense scholarly discussion (Machin et al., 2007; Saragusti et al., 1998; Wynn, 2000, 2002). It has been suggested that handaxe symmetry increases through time during the known chronological range of the Acheulean (Saragusti et al., 1998), and that their symmetrical profile provides evidence of symbolic capacities in extinct hominins (Le Tensorer, 2006). Handaxe symmetry has also been argued to have implications for studying the evolution of human cognition (Wynn, 2002). Many authors, however, have suggested that the symmetrical form of Acheulean bifaces may be causally linked to their function as cutting and chopping tools, especially in relation to the task of animal butchery (Jones, 1980; Machin et al., 2007; McBrearty, 2003; McNabb, 2005; Mitchell, 1996; Shea, 2007), and thus that handaxe symmetry was potentially subject to selective forces for adaptive reasons (Sima˜o, 2002). It has also been suggested that handaxe form was a product of sexual selection, whereby artefact symmetry was an indicator of mate fitness (Kohn and Mithen, 1999). Such classic Darwinian mechanisms of adaptive and sexual selection are joined by arguments that symmetrical Acheulean bifaces may have been preferred due to aesthetic or symbolic reasons

S.J. Lycett / Journal of Archaeological Science 35 (2008) 2640–2648

(Pelegrin, 1993: 310; Reber, 2002; Le Tensorer, 2006), in turn, positively influencing the ‘replicative success’ (sensu Leonard and Jones, 1987) of symmetry in traditions of Acheulean biface manufacture. When witnessing a strong and recurring archaeological pattern there is a danger that scenarios invoking selection, if not adaptation, might too glibly be applied in order to explain the recurrence of a specific feature (Clark and Barton, 1997: 315; O’Brien and Holland, 1992; Wynn, 2000: 135). It is notable that in the field of population genetics, the concept of neutral variation (i.e. variation not due to selective forces) is always assumed as the default (null) hypothesis, and only when robust evidence for a departure from a theoretical expectation of neutral variation is found, are alternative explanations for a given pattern of molecular variability sought (Hey, 1999; Kreitman, 1996). In recent years, it has become increasingly apparent that cultural (i.e. social) transmission can be modelled as an information transmission mechanism broadly analogous to that of genetic transmission (Cavalli-Sforza and Feldman, 1981; Durham, 1992; Boyd and Richerson, 1985). This is not to say that genetic and social information transmission are identical in all parameters (Eerkens and Lipo, 2007). One obvious difference between the two inheritance mechanisms is that in the case of social transmission, the ability to acquire information is not limited to copying solely from biological parents; there is also the option to copy more distantly related kin and unrelated individuals (Richerson and Boyd, 2005). Rather, it is that because both cultural transmission and genetic transmission are mechanisms of information transfer between individuals within populations, many of the factors known to influence population-level patterns of genetic variation (e.g., population size, drift, migration, etc.) must also be considered when attempting to understand patterns of cultural variation (see e.g., Bentley et al., 2004; Eerkens and Lipo, 2007; Neiman, 1995; O’Brien and Lyman, 2003; Shennan, 2000, 2001). A further corollary of this is that models and methods of analysis originally designed in the field of population genetics can provide useful means of testing hypotheses concerning patterns of cultural variation (Bentley, 2007; Kohler et al., 2004; Neiman, 1995; Richerson and Boyd, 2005; Shennan, 2006). Hence, in line with other recent studies (e.g., Bettinger and Eerkens, 1999; Mesoudi and O’Brien, 2008, in press), the analyses presented here use cultural transmission theory to frame testable predictions regarding patterns of lithic variability. Specifically, a combination of social transmission theory, morphometrics and principles drawn from population genetics are used to test null expectations of neutrality for patterns of variation in handaxe symmetry. 2. Patterns of neutral and selective variation in genotypes, phenotypes and artefacts 2.1. Neutral theory and variation in genotypes and phenotypes: population genetic approaches As is well known in the case of biological evolution, particular patterns of both genetic and phenotypic variation reflect neutral forces of evolution (i.e. drift) versus selection to differing degrees. In the case of neutral evolution, variation is structured by mutation rates and stochastic sampling effects such as population size, migration and dispersal (Wright, 1931). Conversely, selection is reflected in instances wherever specific patterns of variation are related directly to increased survival and fecundity. Population genetics is the study of patterns of molecular variation against this context of natural selection, drift, mutation and gene flow (Crow and Kimura, 1970; Gillespie, 1998; Halliburton, 2004). As such, population genetic approaches aim to examine the specific factors (e.g., drift, selection and population dispersal) that structure allelic variation. The neutral theory of genetic evolution proposes that much of genetic evolution is determined by those factors that have

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a sampling effect on patterns of variation (e.g., population dispersal and drift), with the corollary being that unless strong evidence can be found to the contrary, the null hypothesis is that distinct patterns of variation are the product of stochastic sampling effects rather than selection (Kimura, 1989). As in all null hypotheses, the power of the neutral model lies in its ultimate default position: in the absence of selective forces, a neutral pattern of variation adequately explains the data and, thus, neutrality must be rejected before more inferentially complex explanations can be given credence (Hey, 1999; Kreitman, 1996; Roseman and Weaver, 2007). In cases where variation is selectively neutral, population genetic approaches may be used to study factors such as population dispersal. One recent example of this is the dispersal of modern human populations where it has been demonstrated that neutral genetic variation fits an iterative founder effect model (Prugnolle et al., 2005). This model predicts a sequential reduction of withinpopulation genetic variance (heterozygosity) due to repeated instances of reduced effective population sizes (serial bottlenecking) along a dispersal route. Hence, in essence, the parameters of the model reflect the combined and progressively acute effects of neutral drift and sequentially reduced effective population sizes as groups disperse over long distances (see Lycett and von CramonTaubadel, 2008 for further discussion). Several studies have demonstrated a statistically significant relationship between progressively reduced within-group heterozygosity and distance from East Africa, consistent with this serial founder effect model and the hypothesis of human global dispersal from sub-Saharan Africa (e.g., Prugnolle et al., 2005; Ramachandran et al., 2005; Liu et al., 2006; Manica et al., 2007; Li et al., 2008). A fit to the model has also been demonstrated in the case of human stomach bacteria (Helicobacter pylori), suggesting that the demographic consequences of human global dispersal also had an effect on the population genetics of these ‘hitchhiking’ bacterial populations, as humans carried them out of Africa in their stomachs (Linz et al., 2007). It should be noted that certain patterns of phenotypic (i.e. physiological and morphological) variation are also known to conform largely to neutral expectations. This has been demonstrated recently in the case of the human cranium (Relethford, 2002; Gonzalez-Jose et al., 2004; Roseman, 2004; Harvati and Weaver, 2006a, 2006b; Smith et al., 2007; Roseman and Weaver, 2007). Furthermore, both Manica et al. (2007) and von CramonTaubadel and Lycett (2008) have shown a statistically significant fit between modern human cranial variation and an iterative founder effect model with sub-Saharan origins, demonstrating congruence between patterns of neutral genetic diversity and phenotypic variation in modern human populations. However, because selection frequently operates on the phenotype directly, it is known that different phenotypic elements fit neutral expectations to varying degrees, with some phenotypic elements largely conforming to neutral expectations while others show the effects of strong selection (Roseman, 2004). For example, in the case of the human cranium, Harvati and Weaver (2006a,b) have averred that variation in the neurocranium and temporal bone reflect neutral genetic distances, while facial shape is more reflective of the selective influence of climate. Smith et al. (2007) partly confirm these results by demonstrating that temporal bone morphology fits neutral expectations rather than patterns consistent with strong selection. 2.2. Social transmission and selective versus neutral forces in cultural evolution Insights gained from population genetic approaches concerning the relative effects of neutral versus selective forces in shaping patterns of genetic and phenotypic variation, have the potential to inform studies of variation in hominin material culture such as

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Acheulean handaxe shape. This is because in traditional societies, the knowledge and skills associated with an activity such as handaxe manufacture can reasonably be assumed to have been inherited via a process of social transmission between individuals and across generations through time (Mithen, 1994, 1996, 1999; Shennan and Steele, 1999; Stout, 2002, 2005; Wynn, 1995). Indeed, there is growing evidence to suggest that population-specific patterns of behavioural variability and distinct technological traditions (i.e. ‘culture’) in some non-human primates are the result of analogous processes of social transmission of information between individuals and across generations (Biro et al., 2003, 2006; Bonnie et al., 2007; Hopper et al., 2007; Horner et al., 2006; Lycett et al., 2007; McGrew, 1992, 2004; van Schaik et al., 2003; Whiten et al., 1999, 2001, 2005, 2007). Because the social transmission of cultural information may be modelled as an inheritance mechanism broadly analogous to that of genetic (information) inheritance (Cavalli-Sforza and Feldman, 1981; Durham, 1992; Boyd and Richerson, 1985; Eerkens and Lipo, 2005; Whiten, 2005; Shennan, 2006), it has become increasingly apparent that many of the factors known to structure patterns of genetic variation (e.g., drift, effective population sizes, dispersal, etc.) must also be considered when studying patterns of cultural variation (see e.g., Bentley and Shennan, 2003; Bentley et al., 2004; Richerson and Boyd, 2005; Neiman, 1995; Shennan, 2000, 2001; Shennan and Wilkinson, 2001; Henrich 2004; Lipo et al., 1997; Lycett and von CramonTaubadel, 2008; O’Brien and Lyman, 2000, 2003; Bettinger et al., 1996; Eerkens and Lipo, 2007). In turn, models and methods of analysis originally designed in the field of population genetics can provide useful means of testing hypotheses regarding cultural variation. Neiman (1995) outlined how the mathematical principles derived from neutral genetics theory could be used to test quantitatively, the fit of cultural trait variation through time to neutral expectations. Recently, such insights have been used to test neutral versus selective expectations in various cultural data sets. Cultural traits such as name choice, choice of dog breeds, and turnover trends in popular music, have all been shown to fit a neutral (drift) pattern of change through time (e.g., Hahn and Bentley, 2003; Herzog et al., 2004; Bentley et al., 2004, 2007). Other studies, such as one concerning prehistoric (Linearbandkeramik) pottery designs, suggest potential deviations from neutral expectation (Shennan and Wilkinson, 2001). Hence, as in the case of population genetics, neutrality becomes the null (default) model, and unless there is strong evidence for a departure from neutrality, it is unnecessary to evoke processes other than drift as explanation for the factors producing given patterns of variability (Bentley, 2007; Bentley et al., 2004, 2007; Shennan, 2006). Brantingham (2003) has also recently exploited the advantages that a neutral perspective may bring to the issue of stone raw material procurement. 3. Handaxe symmetry and selection It is a commonly held view within Palaeolithic archaeology and palaeoanthropology that Acheulean technologies evolved in subSaharan Africa and spread across many regions of the Near East, Europe and the Indian subcontinent via subsequent hominin dispersals from Africa (e.g., Bar-Yosef and Belfer-Cohen, 2001; Carbonell et al., 1999; Clark, 1994; Goren-Inbar et al., 2000; Klein, 2005; Saragusti and Goren-Inbar, 2001). Drawing on a population genetics framework, Lycett and von Cramon-Taubadel (2008) predicted that if this hypothesis is correct, Acheulean handaxe assemblages would fit an iterative founder effect model, in an analogous manner to which some genetic and phenotypic data are known to vary in the case of similar long distance hominin dispersals (e.g., Prugnolle et al., 2005; Ramachandran et al., 2005; Manica et al., 2007; von Cramon-Taubadel and Lycett, 2008). Lycett

and von Cramon-Taubadel (2008) tested the predictions of this model using a series of Acheulean handaxe assemblages from Africa, the Near East, Europe and Asia. Mean within-group (i.e. assemblage) variance was calculated using a series of (n ¼ 48) sizeadjusted (plan-form) shape variables. As noted above, the iterative founder effect model predicts the sequential reduction of withingroup variance as geographic distance from origin increases along a hypothesised dispersal route. Hence, the model is assumed to be supported by a statistically significant inverse relationship between within-group variance and geographic distance from origin. Two measures of geographic distance were utilised in the analyses: (1) ‘as-the-crow-flies’ minimum distances between East Africa (Olduvai Gorge, Tanzania) and each site locality, and (2) the distances derived from a minimum-spanning network linking site localities and two ‘waypoints’ (see Fig. 2 in Lycett and von Cramon-Taubadel, 2008). The latter distances were designed to approximate more closely the geographic distances covered by hominins in landbased scenarios of population dispersal(s) from Africa. Lycett and von Cramon-Taubadel (2008) found statistically significant support for the serial founder effect model, with ~45–50% of within-assemblage handaxe shape variance explained by geographic distance from East Africa. Using a contrasting series of nonAfrican start points, they found that no residual variation could be explained by a significant fit to the iterative founder effect model. Indeed, using non-African start points for the distance calculations does not merely produce non-significant results, but also generates R2 values (range ¼ 0.001–0.297) markedly different from those using the East African origin (Lycett and von Cramon-Taubadel, 2008: Table 3). Hence, using the non-African start points produces both weak and non-significant relationships (neither positive nor negative) between distance and within-assemblage variance patterns. These latter analyses are important since they suggest that the strength of relationship in the primary analyses is due to geographical parameters (i.e. African origin) rather than factors such as sampling bias. As Lycett and von Cramon-Taubadel (2008) noted, their results imply that a high proportion of handaxe (plan-form) shape varies according to the principles of neutral drift. As such, these analyses provide a baseline of comparison against which other aspects of handaxe variability might usefully be assessed for goodness-of-fit to a neutral model. This is especially useful since the dating parameters of Palaeolithic artefacts such as Acheulean handaxes are frequently unknown and/or less precise than examples of material culture change in later (i.e. Holocene) societies. Such factors lead to increased difficulty in applying some of the methodologies that others have previously used to assess the relative contribution of selective versus neutral mechanisms, in instances where the necessary high resolution chronological data are available (e.g., Neiman, 1995; Shennan and Wilkinson, 2001; Bentley et al., 2004; Hahn and Bentley, 2003). The 48 shape variable measurements used by Lycett and von Cramon-Taubadel (2008) in their analyses, however, detailed only discrete information about shape at specific points of the handaxe. Hence, the property of overall symmetry was not considered. Notably it is Acheulean handaxe symmetry that is specifically invoked as being one of the primary defining characteristics of Acheulean bifaces, and is frequently considered to have been a property of handaxe shape that was subject to selection. In principle, the statistically significant regression results (i.e. R2 values) of Lycett and von Cramon-Taubadel (2008) may be used as a baseline of comparison against which to test neutral expectations for handaxe symmetry. That is, including a quantitative measure of symmetry as part of the dataset upon which mean within-assemblage variance values are computed, enables specific predictions to be made (see below) as to whether, on average, handaxe symmetry values are less selectively neutral than the handaxe plan form

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variables employed in the initial baseline analyses of Lycett and von Cramon-Taubadel (2008), and thus whether handaxe symmetry was subject to stronger selection than discrete outline (plan-form) shape variables. Here, the (null) hypothesis of neutral expectation for handaxe symmetry is tested against this predictive framework, using the procedures detailed below. 4. Materials, methods and predictions 4.1. Materials and morphometric methods For purposes of direct comparison, the same artefact samples as used in Lycett and von Cramon-Taubadel (2008) were employed here. By keeping all of the variables other than symmetry constant (e.g., raw material, sample sizes, distance measures, etc.) in this manner, we can be sure that the only parameter that differs is the addition of symmetry to the analysis. The data comprise a total sample size of n ¼ 255 handaxes from 10 localities, including African, Near Eastern, European and Asian assemblages (Table 1). Following Lycett and von Cramon-Taubadel (2008), the 48 outline (plan-form) variables (Table 2) were obtained using a Crossbeam Co-ordinate Caliper and associated artefact orientation protocol, previously described in detail elsewhere (Lycett et al., 2006; Lycett, 2007). As McPherron (2000) has noted, comparisons of shape in lithic artefacts may be confounded by size changes associated with reduction intensity. Hence, Euclidean distance variables were size-adjusted using the geometric mean method (Mosimann, 1970; Jungers et al., 1995; Lycett et al., 2006), in order to remove the confounding effect of size differences in various finished artefacts and raw material blank size. The geometric mean method of size-adjustment equalises the volume of each specimen while maintaining overall shape information (Falsetti et al., 1993). In contrast to alternative scaling methods (e.g., allometric size-adjustment based on regression residuals) the method has been demonstrated experimentally to allow the identification of differently sized specimens of the same shape following adjustment (Jungers et al., 1995). 4.2. Measuring handaxe bilateral symmetry The symmetry of each handaxe was measured using Lycett et al.’s (2006) ‘Index of Symmetry’. The left and right lateral (width) measurements taken with the Crossbeam Co-ordinate Caliper at various percentage points either side of a biface’s length (see variables 1–26, Table 2) were used in the computation of this variable. Thus, this index allows the relative bilateral symmetry of nuclei to be compared on a quantitative basis. The Index of Symmetry (S) was computed as:

0qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1 ðXi  Yi Þ2 @ A S ¼ Xi þ Yi i¼1 n X

(1)

Table 1 Taxonomic units employed in analyses (total n ¼ 255 handaxes) Taxonomic unit number

Locality

n

Raw material

1 2 3 4 5 6 7 8 9 10

Olduvai Gorge (Bed II), Tanzania Kariandusi, Kenya Lewa, Kenya Kharga Oasis (KO10c), Egypt Tabun Cave (Ed), Israel Bezez Cave (Level C), Adlun, Lebanon St. Acheul, France Elveden, Suffolk, UK Morgah, Pakistan Attirampakkam, India

13 30 30 17 30 30 30 24 21 30

Quartz, lava Lava Chert Chert Chert Chert Chert Chert Quartzite Quartzite

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Table 2 Left/right lateral (1–26) and distal/proximal (27–48) handaxe outline (‘plan-form’) variables employed in analyses (see Lycett et al., 2006 for details) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core Core

left width at 10% of length left width at 20% of length left width at 25% of length left width at 30% of length left width at 35% of length left width at 40% of length left width at 50% of length left width at 60% of length left width at 65% of length left width at 70% of length left width at 75% of length left width at 80% of length left width at 90% of length right width at 10% of length right width at 20% of length right width at 25% of length right width at 30% of length right width at 35% of length right width at 40% of length right width at 50% of length right width at 60% of length right width at 65% of length right width at 70% of length right width at 75% of length right width at 80% of length right width at 90% of length length distal at 10% of width length distal at 20% of width length distal at 25% of width length distal at 30% of width length distal at 40% of width length distal at 50% of width length distal at 60% of width length distal at 70% of width length distal at 75% of width length distal at 80% of width length distal at 90% of width length proximal at 10% of width length proximal at 20% of width length proximal at 25% of width length proximal at 30% of width length proximal at 40% of width length proximal at 50% of width length proximal at 60% of width length proximal at 70% of width length proximal at 75% of width length proximal at 80% of width length proximal at 90% of width

where Xi is the width value left of the length line taken at a particular percentage point, Yi is the width value right of the length line taken at the corresponding percentage point, and n is the number of percentage points at which Xi and Yi are taken. Hence, a value of zero would correspond to perfect bilateral symmetry. It is important to note that the Index of Symmetry (S) expresses the degree of asymmetry between the two bilateral measurements (Xi  Yi) as a ratio of the overall width (Xi þ Yi) of the nucleus at that point, such that the variable is a size-independent measure. 4.3. Measuring within-assemblage variance The total dataset of morphometric traits included the 48 sizeadjusted outline (plan-form) shape variables, plus the index of symmetry for each handaxe. Assemblage variation was computed as the mean within-group variance of all 49 variables for each assemblage. The variance (s2) of each variable within an assemblage was computed as:

s2 ¼

Pn

 xÞ2 n1

i ¼ 1 ðxi

(2)

S.J. Lycett / Journal of Archaeological Science 35 (2008) 2640–2648

4.4. Geographic distances Following Lycett and von Cramon-Taubadel (2008) two separate measures of geographic distance were used in the analyses. These were: (1) ‘as-the-crow-flies’ minimum distance between Olduvai Gorge (Tanzania) and each site locality; and (2) the minimum distance network linking individual site localities and two ‘waypoints’ (see Fig. 2 Lycett and von Cramon-Taubadel, 2008). The two waypoints used here were Cairo, Egypt (30N, 31E) and Istanbul, Turkey (41N, 28E). This latter distance measure was designed to make a more accurate estimation of geographical distances involved in dispersals between the regions concerned (compared with the ‘asthe-crow-flies’ distances) by excluding large sea crossings, which are improbable in any case and may be ruled out with certainty in others (e.g., between Olduvai Gorge, Tanzania and Attirampakkam, India). In all cases, geographic distances were calculated in kilometres using great circle distances based on the haversine (see Appendix A). Great circle distances take account of the Earth’s curvature and thus are appropriate measures of distance when covering large geographic areas (Sinnott, 1984). 4.5. Predictions Using the results of Lycett and von Cramon-Taubadel (2008) as a baseline of comparison, specific predictions can be made with regard to neutral expectations for handaxe symmetry values. If symmetry variances within the Acheulean assemblages conform to neutral expectations, we can predict that the coefficient of determination (R2) values for the regressions will either increase (i.e. a greater degree of mean within-assemblage variance can be explained by geographic distance at statistically significant levels (a ¼ 0.05)), or the addition symmetry will have no appreciable effect. Conversely, if symmetry is, on average, not conforming to neutral expectation on a comparative basis with the 48 (plan form) shape variables, then we can predict that R2 values will be lower than those produced in the initial (baseline) analyses of Lycett and von Cramon-Taubadel (2008). To reiterate, these values were R2 ¼ 0.45 when the as-the-crow-flies geographic distances were used, and R2 ¼ 0.50 when the minimum spanning network distances were used. A more conservative prediction of non-neutral expectation would state that with symmetry values included in the mean within-assemblage variance scores, R2 values will not merely be lower than in the baseline levels, but that symmetry is under such strong selection that the previously significant R2 values will be reduced to non-significant levels (i.e. p > 0.05). All analyses were performed in SPSS 12.0.1. The analyses were initially performed with as-the-crow-flies distances and then repeated using the minimum-spanning network distances (with waypoints). In both cases, the independent variable of mean within-group (i.e. assemblage) variance was regressed on the dependent variable of geographic distance from East Africa (Olduvai Gorge). 5. Results Fig. 1 shows the regression results for the ‘as-the-crow-flies’ distances. The regression results demonstrate that with symmetry measures included in the mean within-assemblage variance values, a lower amount of residual variation (R2 ¼ 0.196) is explained by geographic distance, compared to the baseline results of Lycett and von Cramon-Taubadel (2008), which produced R2 values of 0.45 for

14

Within-assemblage variance

where n is the number of artefacts in that sample, xi is the variable value for a given specimen, and x is the mean of the variable for all specimens in that sample.

R2 = 0.196 P = 0.20

12

Olduvai Kariandusi Lewa Kharga Oasis Tabun Bezez Morgah ATPKM St. Acheul Elveden

10 8 6 4 2 0 0

2000

4000

6000

8000

Geographic distance (km) Fig. 1. Least-squares regression of the ‘as-the-crow-flies’ distances against mean within-assemblage variance.

the same geographic distances. Moreover, on this occasion, the results evince a non-significant (p ¼ 0.20) relationship. Fig. 2 shows the regression results using the minimum spanning network distances with waypoints. Consistent with the first analysis, the regression indicates a lower relationship between mean within-assemblage variance values and geographic distances (R2 ¼ 0.283) compared with the equivalent baseline results, which produced R2 values of 0.50 (Lycett and von Cramon-Taubadel, 2008). Again, it is important to note that the analysis indicates not merely that a lower amount of residual variation is being explained by the regression, but that the relationship is statistically non-significant (p ¼ 0.113). Thus, in both cases, the regression analyses are consistent in suggesting that adding symmetry measures to the mean withinassemblage variance values produces a lower and non-significant fit to the predictions of the iterative founder effect model for the Acheulean assemblages. As such, these results do not support the null hypothesis of neutral expectation for the property of bilateral handaxe symmetry. 6. Discussion and conclusions It was predicted that if patterns of symmetry variation in Acheulean handaxes conforms to neutral expectations, the degree of within-assemblage variation explained by geographic distance

14

Within-assemblage variance

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R2 = 0.283 P = 0.113

12

Olduvai Kariandusi Lewa Kharga Oasis Tabun Bezez Morgah ATPKM St. Acheul Elveden

10 8 6 4 2 0 0

2000

4000

6000

8000

10000

Geographic distance (km) Fig. 2. Least-squares regression of the minimum-spanning network distances (including waypoints) against mean within-assemblage variance.

S.J. Lycett / Journal of Archaeological Science 35 (2008) 2640–2648

will either increase or exhibit no difference from the baseline levels. In consistently showing both a lower and a statistically non-significant fit between mean within-assemblage variance values and geographic distance, the results of the two regression analyses do not support the null hypothesis of neutral expectation for the property of handaxe symmetry. Rather, the analyses suggest that symmetry was subject to selective forces. Importantly, the analyses appear to support the more conservative prediction of a non-neutral hypothesis for handaxe symmetry measures, which (as noted above) states that if symmetry was under particularly strong selection, R2 values will not merely be lower than in the baseline levels, but that the previously significant R2 values of Lycett and von Cramon-Taubadel (2008) will be reduced to non-significant levels. Hence, such results strongly support suggestions that bilateral handaxe symmetry was subject to selective forces, such that Acheulean assemblages vary according to non-neutral patterns for this specific variable. A selective basis for handaxe symmetry is entirely consistent with suggestions that Acheulean handaxes became more symmetrical through time during their known chronological span (e.g. Saragusti et al., 1998; Wynn, 2002; de Heinzelin et al., 2000), although the strength and pattern of relationship between handaxe symmetry and chronology requires further testing. Several different categories or ‘types’ of handaxe form (e.g., ‘cordiform’, ‘pointed’, ‘ovate’, etc.) have been delineated by previous generations of Palaeolithic archaeologists (Bordes, 1961; Debe´nath and Dibble, 1994), although the most important aspects of variation in the basic outline form of handaxes between assemblages may well be clinal in nature rather than typological (Lycett and Gowlett, in press). A clinal view of variation in outline form would also be consistent with McPherron’s (1999, 2003) assertion that a major cause of variation in the outline form of bifaces is reduction intensity, although a clinal view is not mutually exclusive to additional sources of variation. In combination, the analyses of Lycett and von Cramon-Taubadel (2008), who provided evidence that the basic – but analytically discrete – plan-form variables of Acheulean handaxes vary in a neutral manner, and the results reported here, which suggest that the property of symmetry was subject to selection, have implications for the interpretation of traditionally recognised ‘types’ of handaxe shape. That is, they suggest that the specific shape of handaxes was neutral and specific to the particular historical dynamic of given Acheulean populations, whereas regardless of shape, symmetry acted non-neutrally and can be seen as subject to strong selective forces. Hence, the specific means by which symmetry was achieved (i.e. particular variety or ‘type’ of handaxe shape produced) in this category of artefact was, on average, less important to Acheulean populations from a selective standpoint than the property of overall symmetry per se. Hence, just as in the human cranium (Roseman, 2004; Harvati and Weaver, 2006a, b), different aspects of handaxe form appear to reflect neutral versus selected patterns of variation to differing degrees. 6.1. The selection of symmetry in handaxes: categories of mechanism Several different mechanisms of selection regarding handaxe symmetry have been evoked in the literature. The analyses reported here cannot determine the precise selective mechanism(s) responsible for the non-neutral pattern of variation observed. However, having identified evidence of selection, it is now important to distinguish more precisely between several different categories of selection that might account for the non-neutral pattern. The types of selective forces discussed in the literature each belong to distinct categories. These include scenarios of functional selection, whereby symmetrical handaxes are seen as more effective as cutting and chopping tools (e.g., Ohel, 1987; Mitchell, 1996; Sima˜o, 2002).

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Functional selection can further be subdivided into those selective hypotheses that involve conscious choice on the part of Acheulean toolmakers, and those that that do not necessarily rely on any conscious choice by hominins. An hypothesis of functional selection lacking conscious choice implies that handaxes operated in the form of an ‘extended phenotype’ (sensu Dawkins, 1982) under the parameters of classic natural selection, with populations who made more symmetrical handaxes having greater (biological) reproductive fitness and, in turn, giving rise to a greater number of symmetrical handaxe producing offspring than populations who made less symmetrical tools. This type of selection, were it in operation, would indirectly impact selection of cognitive and biomechanical abilities involved in the production of more symmetrical handaxe forms (cf. Wynn, 2002). An hypothesis of functional selection involving more conscious (agency-based) selectivity on the part of hominins (cf. Hopkinson and White, 2005) would imply a greater degree of reflective cognition in the selection process, with hominins perceiving that more symmetrical handaxes were more effective in functional tasks than less symmetrical forms, and thus striving toward more symmetrical tools through time (Sima˜o, 2002), even in instances where this did not necessarily improve biological fitness. This latter hypothesis of selection would be classed as a form of ‘cultural selection’ or ‘artificial selection’. Indeed, it is important to note here that despite claims to the contrary (e.g., Shanks and Tilley, 1992: 55–56; Bryant, 2004; Benton, 2000; Ingold, 2007), issues of conscious choice on the part of individuals are not incompatible with evolutionary perspectives on cultural variation and change (Shennan, 2004; Mesoudi, 2008). A second distinct category of selection to which handaxe symmetry may have been exposed is that proposed by Kohn and Mithen (1999), who posited that handaxe symmetry was subject to sexual selection (Darwin, 1871), whereby an ability to manufacture symmetrical handaxes was an indicator of mate fitness. Again, such selection would put a premium on the cognitive and biomechanical abilities involved in the manufacture of more symmetrical bifaces. A third group of hypotheses regarding symmetry selection can be classed under the category of aesthetic selection. This category refers to conscious cultural selection on the part of Acheulean hominins whereby for purely aesthetic or socially symbolic meanings, symmetrical forms of handaxe were favoured over less symmetrical forms (e.g., Schick and Toth, 1993: 282; Le Tensorer, 2006). As in the case of the category of conscious functional selection, it is cognisant reflection by Acheulean hominins themselves on the variable of symmetry, which is here positively influencing the ‘replicative success’ of more symmetrical forms in handaxe traditions, although in this instance, the variable is favoured for aesthetic rather than functional reasons. Outlining the various categories of selection to which handaxe symmetry was potentially subject in these terms, serves to highlight the complex nature of the available selective scenarios. For instance, it is interesting to note that hypotheses of conscious cultural selection can be invoked under both the category of functional selection and that of aesthetic selection. Indeed, the various categories and individual mechanisms of selection are not necessarily mutually exclusive, and symmetry may have been subject to selection for a combination of factors, both consciously and unconsciously. However, more precise delineation of the potential selective forces under which handaxe symmetry was – according to the results of the analyses presented here – subject to, may assist future efforts to test the candidate selective mechanisms in explicit terms, especially in regard to which hypotheses can (and cannot) be rejected in each case. For instance, a test suggesting that functional selective mechanisms for handaxe symmetry are plausible, would not necessarily be able to distinguish between conscious (cultural) selective mechanisms and one

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of unconscious (natural) selection, as defined above. However, recent experimental work suggests that testing certain categories of hypothesis directly via quantitative methodologies is feasible (Machin et al., 2007).

where

havðqÞ ¼ sin2



d1  d2 2



þ cosd1 cosd2 sin2



a1  a2 2



(A2)

and R is the radius of Earth (6371 km). 6.2. Conclusions: the importance of a null hypothesis of neutral artefact variation

References

There has often been a tendency within Palaeolithic archaeology to assume that distinctive or recurring tool types and/or patterns of lithic variability are evidence of ‘adaptive’ processes by extinct hominins. At times, it has even been assumed that functional or ‘adaptive’ variation will override all other potentially meaningful patterns of artefactual variability (e.g., Binford and Binford, 1966; Binford, 1973). Such adaptationist views stand in direct contrast to the approach taken by population geneticists who always first assume a neutral pattern of variation for molecular data, and only look to non-neutral (e.g., selective) scenarios for explanation of pattern and variation in the face of strong evidence against the null model of neutral expectation (Roseman and Weaver, 2007). Others have previously lamented the potential for accommodative posthoc selectionist and adaptationist ‘just-so-stories’ in archaeological interpretation (e.g., Clark and Barton, 1997; O’Brien and Holland, 1992; Wynn, 2000: 135). Although Isaac (1972: 186–187) mentioned the concept of drift in connection with Palaeolithic artefacts, this insight was not subsequently operationalised so that the concept might become a predictive means of testing a null hypothesis of artefact variation. Rather, ‘drift’ merely became one of the many possible explanations (e.g., function, raw material, reduction intensity, etc.) that might be invoked to explain variation in the Palaeolithic record. Here, in line with studies of more recent cultural phenomena (e.g., Neiman, 1995; Bentley et al., 2004, 2007; Shennan and Wilkinson, 2001), it has been shown that, in combination with cultural transmission theory, modification of the methods and principles used by population geneticists can be used to test (null) neutral expectations for Palaeolithic artefacts, and lead to a more satisfactory basis on which selective hypotheses of artefactual variation might be founded. Acknowledgements I am indebted to Parth Chauhan, Mark Collard, Noreen von Cramon-Taubadel, John Gowlett and Alex Mesoudi for important conversations and constructive comments on this manuscript. I am also grateful for additional important comments provided by John Grattan, Richard Klein, Gil Tostevin, and two anonymous reviewers. Access to lithic material and hospitability during data collection were gratefully received from Anne Taylor, Assistant Curator, Cambridge University Museum of Archaeology and Anthropology. This research was funded by and undertaken within the British Academy Centenary Research Project, Lucy to Language; I am especially grateful to John Gowlett for his kindness and generosity at this time. Appendix A The geographic distances employed in the analyses were calculated in kilometres using great circle distances based on the haversine (Sinnott, 1984). Hence, the distance (D) between two points specified by latitudinal (a1, d1) and longitudinal (a2, d2) coordinates with a central angle of q between the two points was computed as:

pffiffiffiffiffiffiffiffiffiffiffiffiffiffi ! havðqÞ D ¼ 2Rarctan pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1  havðqÞ

(A1)

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