Journal of Archaeological Science 35 (2008) 553e562 http://www.elsevier.com/locate/jas

Acheulean variability and hominin dispersals: a model-bound approach Stephen J. Lycett*, Noreen von Cramon-Taubadel Leverhulme Centre for Human Evolutionary Studies, University of Cambridge, Fitzwilliam Street, Cambridge CB2 1QH, UK Received 16 January 2007; received in revised form 10 April 2007; accepted 1 May 2007

Abstract Understanding the pattern of hominin dispersal is a fundamental component of Palaeolithic archaeology and palaeoanthropology. A widely held assumption is that bifacial handaxe (i.e. Acheulean or ‘Mode 2’) technologies evolved in Africa and dispersed into northern and western Eurasia via subsequent hominin migrations. To date, however, few formal tests of this hypothesis have been presented. Here, we use a combination of morphometrics, cultural transmission theory, and a dispersal model drawn from population genetics in order to test this hypothesis. The iterative founder effect (repeated bottlenecking) model is assumed to be supported if a significant inverse relationship is found between geographic distance from source along an estimated dispersal route and within-assemblage variance. The results of our analyses support the hypothesis that Acheulean technologies evolved in Africa and dispersed with migrating hominin populations into northern and western Eurasia under the assumptions of this iterative founder effect model. Based on our results we suggest that the occurrence of certain Mode 1 technologies such as those east of the Movius Line, and some assemblages assigned to the Clactonian of Britain, plausibly represent instances where effective population sizes in colonising populations dropped below levels where Mode 2 technologies could be maintained. Ó 2007 Elsevier Ltd. All rights reserved. Keywords: Handaxes; Mode 2; Dispersal; Demography; Social transmission; Cultural evolution; Movius Line; Clactonian

1. Introduction: Acheulean handaxes and hominin dispersals Handaxes have been described as the most enigmatic artefacts of the Lower Palaeolithic (Wynn, 1995) and, along with cleavers, are the diagnostic feature of the Acheulean or Mode 2 phenomenon. Debates regarding the distribution of the Acheulean, potential variability and stasis within it, and its absence east of the Movius line (i.e. the line traditionally held to represent a geographic demarcation between the Mode 2 Acheulean industries of western Eurasia and the Mode 1 core/chopper and flake industries of eastern Eurasia) have appeared continuously in the literature for many decades (e.g. Callow, 1986; Carbonell et al., 1999; Clark, 1994, 1998, 2001; Corvinus, 2004; Crompton and Gowlett, 1993; Gamble and Marshall, 2001; Keates, 2002; Kohn and Mithen, 1999; McNabb et al., 2004; Movius, 1948;

* Corresponding author. Tel.: þ44 (0) 1223 764 722. E-mail address: [email protected] (S.J. Lycett). 0305-4403/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.jas.2007.05.003

Roe, 1976; Schick, 1994; Wynn, 1979). Particular attention has been paid to the significance of the outline or plan-form of Acheulean handaxes in regard to issues of ‘mental templates’, raw material, reduction intensity, function and the cognitive capacities of hominins (Gowlett and Crompton, 1994; Machin et al., 2007; McPherron, 1999, 2000; Vaughan, 2001; White, 1998a, 1998b; Wynn and Tierson, 1990). Understanding the pattern of hominin dispersals is a fundamental component of palaeoanthropological research (Anto´n and Swisher, 2004; Dennell, 2003; Gamble, 1993; Lahr and Foley, 1994; Roebroeks, 2006). Hence, testing scenarios of hominin dispersal is a difficult, but essential, task (Dennell and Roebroeks, 2005; Derricourt, 2005; Holmes, 2007; Mithen and Reed, 2002). A widely held assumption in Palaeolithic archaeology is that the Acheulean originates in East Africa (ca. 1.6 Mya.) and subsequently spreads across many regions of the Palaeolithic Old World via hominin dispersals (Bar-Yosef and Belfer-Cohen, 2001; Carbonell et al., 1999; Clark, 1994: 465; Goren-Inbar et al., 2000; Saragusti and Goren-Inbar, 2001). Since the oldest known handaxes are from eastern and

554

S.J. Lycett, N. von Cramon-Taubadel / Journal of Archaeological Science 35 (2008) 553e562

southern Africa (Asfaw et al., 1992; Kuman and Clarke, 2000; Leakey, 1971), chronological data support the African dispersal hypothesis to some degree. However, it would be advantageous if additional predictions derived from the dispersal hypothesis were tested. Here we use a combination of morphometric methods, cultural transmission theory, and a model drawn from population genetics in order to test the African Acheulean dispersal hypothesis further. 2. Rationale, materials and methods In recent years, the role that demography may play in artefact variation has received increased discussion (Henrich, 2004; Mellars, 2006; Neiman, 1995; Shennan, 2000, 2001). This is because in traditional societies the skills associated with a task such as handaxe manufacture may reasonably be assumed to have been inherited via a process of social transmission (Mithen, 1999; Shennan and Steele, 1999; Stout, 2002). Indeed, there is evidence to suggest that cultural variability and technological traditions in some non-human primates are the result of analogous processes of social transmission of information between individuals and across generations (Biro, 2003; Bonnie et al., 2007; McGrew, 1992, 2004; Van Schaik et al., 2003; Whiten et al., 2001; Whiten, 2005). In situations where social transmission is operating, only a subset of the total population will be directly involved in the transmission of behavioural variants, and this subset may be referred to as the ‘‘effective population size’’ (Ne) (Henrich, 2004; Neiman, 1995; Shennan, 2001). As in population genetics, Ne (i.e. number of individuals actually involved in the cultural reproductive process) will be a function of overall demography, with attendant consequences for the variability exhibited in subsequent generations of the transmitted element (e.g. genes or artefacts), regardless of whether this is the result of biological or social transmission. The potential for socially transmitted cultural variation to exhibit similar patterns to that seen in genetic data due to migration has also recently received attention (Henrich, 2004; Mellars, 2006). Hence, models culled from population genetics provide a framework for testing hypotheses of hominin dispersals. Here, we employ a model of iterative founder effects to test the Acheulean dispersal hypothesis. The iterative founder effect model (Fig. 1) predicts a sequential reduction of within-group variance (s2) due to repeated instances of bottlenecking and reduction of effective population size (Ne) along a dispersal route (Harpending and Rogers, 2000). The model has been used recently with genetic data to test hypotheses regarding the dispersal of anatomically modern humans from Africa (Linz et al., 2007; Prugnolle et al., 2005; Ramachandran et al., 2005). These studies demonstrated a statistically significant inverse relationship between within-group genetic variance (heterozygosity) and geographic distance from Africa. Hence, the analogous situation here would predict a significant inverse relationship between within-group (i.e. intra-assemblage) variance and distance from East Africa. That is, in each successive dispersal generation, cultural diversity is lost because of a reduction in Ne (Henrich, 2004). Following Prugnolle et al. (2005) and Ramachandran et al. (2005), the model is assumed to be

< Ne

< σ2

< σ2 < Ne

< Ne

< Ne

< σ2 < Ne

< σ2

< Ne

Ancestral variance

Fig. 1. Model of iterative founder effects. A sequential reduction of withingroup variance (s2) is due to repeated instances of bottlenecking and reduction of effective population size (Ne) along a dispersal route (Harpending and Rogers, 2000). The model is assumed to be supported if geographic distance from source along a predicted dispersal route and cultural variance evince a significant (a  0.05) inverse relationship (Prugnolle et al., 2005).

supported if geographic distance from source along an estimated dispersal route can also be used to predict cultural variance by evincing a significant ( p  0.05) relationship. This was tested using least-squares regression in SPSS v.12.0.1. It should be noted that the model is compatible with both single and multiple dispersals of Acheulean populations from Africa, since the same basic relationship (i.e. between geographic distance from Africa and reduced within-group variance) should be evinced independently of how frequently any such dispersal(s) took place. 2.1. Geographical distances The model was tested using two estimates of geographical distance. (1) ‘As-the-crow-flies’ minimum distance between Olduvai Gorge, Tanzania and each site locality; and (2) the minimum distance network linking site localities and ‘waypoints’ (Fig. 2). Following Ramachandran et al. (2005), the two waypoints used here were Cairo, Egypt (30N, 31E) and Istanbul, Turkey (41N, 28E). This latter hypothetical dispersal route (Fig. 2) is intended to make a more accurate estimation of geographical distances involved in any potential dispersal between these sites (compared with the ‘as-the-crow-flies’ distances) by excluding large sea crossings, which are unlikely in any case and can be ruled out with certainty in others (e.g. between Olduvai, Tanzania and Attirampakkam, India). The real benefit of using the two estimates of geographic distance is that the hypothetical route should make a better approximation than ‘as-the-crow-flies’ distances, and a prediction can be made that the correlation is improved as a result of using distances that approximate more accurately (rather than with exact precision) the distances travelled under a dispersal model.

S.J. Lycett, N. von Cramon-Taubadel / Journal of Archaeological Science 35 (2008) 553e562

555

      d1  d2 a1  a2 þ cos d1 cos d2 sin2 hav q ¼ sin2 2 2

ð2Þ

8

and R ¼ radius of earth (6371 km). In addition to the East African dispersal hypothesis we also conducted regression analyses for ‘as-the-crow-flies’ geographic distances and minimum spanning network distances using Elveden (UK), Attirampakkam (India) and Tabun (Israel) as starting points for calculation of distances. Again, the virtue of these analyses lies in their comparative value to results produced under the assumptions of the African dispersal model.

7

6 5 9 4 10

2

3

2.2. Materials and morphometric methods

1

Acheulean locality Waypoint

Fig. 2. Hypothetical dispersal route based on minimum-spanning network distance between Acheulean localities used in the analyses (numbers refer to taxonomic unit numbers and site localities shown in Table 1) and two additional ‘waypoints’ (Cairo, Egypt and Istanbul, Turkey).

Continental comparisons of the geographic distances between sites must take into account that the Earth is a sphere rather than a flat surface. The geographic distances employed here 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) co-ordinates with a central angle of q between the two points was computed as: pffiffiffiffiffiffiffiffiffiffiffiffi ! havðq D ¼ 2R arctan pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1  havðqÞ

ð1Þ

Where

Handaxes from 10 Acheulean localities were employed in the analysis (Table 1). Sites were chosen to maximise geographic coverage and raw material types. It should be noted that the samples employed contain handaxes from points close to both the northern and eastern limits of the Acheulean (i.e. Elveden and Attirampakkam). Sample sizes were circumscribed to some extent by the material available in the museum collections employed. However, in order to keep sample size discrepancies between various localities within reasonable bounds, a decision was taken not to sample more than 30 specimens from each locality. Where the collection from a specific locality contained more than 30 artefacts, the specimens were sampled randomly using the program Research Randomizer (http://www.randomizer.org). This strategy resulted in a total sample size of n ¼ 255 handaxes. As noted above, many debates regarding Acheulean handaxe shape have concentrated on variation in plan-forms, since much of the variability in handaxes is evident in their outline shapes (Vaughan, 2001). Plan-form Euclidean distance variables (n ¼ 48; Table 2) were obtained using a Crossbeam Co-ordinate Caliper (Lycett et al., 2006; Lycett, 2007). In any assessment of morphometric variables, the raw data will generally reflect differences in the size (i.e. isometric scaling) of individual specimens rather than differences in shape. In order to remove the confounding effect of size differences between various finished artefacts and raw material blank form

Table 1 Taxonomic units employed in analyses Taxonomic unit number

Locality

n

Raw material

Mean within-group variance (s2)

1 2 3 4 5 6 7 8 9 10

Olduvai Gorge (Middle/Upper Bed II), Tanzania Kariandusi, Kenya Lewa, Kenya Kharga Oasis (KO10c), Egypt Tabun Cave (Layer Ed) 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 Lava Chert Chert Chert Chert Chert Quartzite Quartzite

0.0270 0.0181 0.0264 0.0199 0.0173 0.0168 0.0165 0.0191 0.0169 0.0149

Total n ¼ 255 handaxes.

556

S.J. Lycett, N. von Cramon-Taubadel / Journal of Archaeological Science 35 (2008) 553e562

Table 2 Left/right lateral (1e26) and distal/proximal (27e48) handaxe outline (‘planform’) variables employed in analyses (see Lycett et al., 2006 for details) 1. Core left width at 10% of Length 2. Core left width at 20% of Length 3. Core left width at 25% of Length 4. Core left width at 30% of Length 5. Core left width at 35% of Length 6. Core left width at 40% of Length 7. Core left width at 50% of Length 8. Core left width at 60% of Length 9. Core left width at 65% of Length 10. Core left width at 70% of Length 11. Core left width at 75% of Length 12. Core left width at 80% of Length 13. Core left width at 90% of Length 14. Core right width at 10% of Length 15. Core right width at 20% of Length 16. Core right width at 25% of Length 17. Core right width at 30% of Length 18. Core right width at 35% of Length 19. Core right width at 40% of Length 20. Core right width at 50% of Length 21. Core right width at 60% of Length 22. Core right width at 65% of Length 23. Core right width at 70% of Length 24. Core right width at 75% of Length 25. Core right width at 80% of Length 26. Core right width at 90% of Length 27. Core Length distal at 10% of Width 28. Core Length distal at 20% of Width 29. Core Length distal at 25% of Width 30. Core Length distal at 30% of Width 31. Core Length distal at 40% of Width 32. Core Length distal at 50% of Width 33. Core Length distal at 60% of Width 34. Core Length distal at 70% of Width 35. Core Length distal at 75% of Width 36. Core Length distal at 80% of Width 37. Core Length distal at 90% of Width 38. Core Length proximal at 10% of Width 39. Core Length proximal at 20% of Width 40. Core Length proximal at 25% of Width 41. Core Length proximal at 30% of Width 42. Core Length proximal at 40% of Width 43. Core Length proximal at 50% of Width 44. Core Length proximal at 60% of Width 45. Core Length proximal at 70% of Width 46. Core Length proximal at 75% of Width 47. Core Length proximal at 80% of Width 48. Core Length proximal at 90% of Width

n X

s2 ¼

ðxi  xÞ

2

i¼1

ð3Þ

n1

Where n ¼ the number of artefacts in that sample, xi ¼ the variable value for a given specimen, and x ¼ the mean of the variable for all specimens in that sample. 3. Results Fig. 3 shows the least squares regression for the ‘as-the-crowflies’ geographic distances. The results demonstrate a significant ( p ¼ 0.033) inverse relationship between geographic distance from East Africa and within-group handaxe shape variance. Indeed, as much as 45% of within-group variance can be explained by geographic distance from East Africa (r2 ¼ 0.452). Fig. 4 shows the least squares regression for the minimumspanning network distances, using the waypoints and hypothetical dispersal route distances. Again, the results demonstrate a significant ( p ¼ 0.023) inverse relationship between geographic distance from East Africa and within-group handaxe variance. Importantly, using this more likely estimation of geographic distance leads to an increased degree of fit between geographic distance and within-group variance. In this instance, as much as 50% of within-group variance can be explained by geographic distance from East Africa (r2 ¼ 0.50). Using Elveden, Attirampakkam and Tabun as starting points for the calculation of ‘as-the-crow-flies’ and minimum spanning network distances, produced results unlike those produced under the assumptions of the African Acheulean dispersal hypothesis (Table 3). None of these analyses evinced a significant relationship between geographic distance and within-group variance. 4. Discussion The least-squares regression analyses fit the predictions of the iterative founder effect dispersal model for Acheulean 0.02800

r2 = 0.452 p = 0.033

0.02600

Kariandusi Lewa Kharga oasis Tabun

Variance

0.02400

size, Euclidean distance variables were size-adjusted using the geometric mean method (Jungers et al., 1995; Lycett et al., 2006). This method equalises the volume of the specimens 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 different sized specimens of the same shape following adjustment (Jungers et al., 1995). Acheulean variability was computed as the mean within-group variance of all sizeadjusted Euclidean distances for each assemblage. The variance (s2) of each Euclidean distance variable within an assemblage was computed as:

Olduvai

Bezez Morgah ATPKM

0.02200

St Acheul Elveden

0.02000 0.01800 0.01600 0.01400 0.00

1000.00 2000.00 3000.00 4000.00 5000.00 6000.00 7000.00

Geographic Distance

Fig. 3. Least-squares regression of the ‘as-the-crow-flies’ geographic distances (km) against mean within-assemblage shape variance.

S.J. Lycett, N. von Cramon-Taubadel / Journal of Archaeological Science 35 (2008) 553e562

Olduvai

0.02800

Kariandusi

r 2 = 0.50

0.02600

p = 0.023

Lewa

Table 3 Comparison of alternative starting points for ‘as-the-crow-flies’ and minimum spanning network routes and resulting regression statistics

Kharga oasis Tabun

Start point

Morgah

Variance

‘As-the-crow-flies’ route

Minimum spanning network route

r2

p

r2

p

0.019 0.031 0.001

0.702 0.624 0.930

0.056 0.297 0.003

0.511 0.103 0.886

Bezez

0.02400

ATPKM St Acheul

0.02200

557

Elveden

0.02000 0.01800

Elveden Attirampakkam Tabun

Note that in contrast to the analysis using Olduvai Gorge as a starting point (Figs. 3 and 4), none are statistically significant (a  0.05).

0.01600 0.01400 0.00

2000.00

4000.00

6000.00

8000.00

10000.00

Geographic Distance

Fig. 4. Least-squares regression of the minimum-spanning network distances (km), using the waypoints and hypothetical dispersal route distances, against mean within-assemblage shape variance.

data. That is, a significant inverse relationship between withinassemblage variance and geographic distance from East Africa is evinced. Interestingly, there is a greater degree of fit between geographic distance and within-group variance when the more likely hypothetical dispersal route distances are employed as opposed to the crude ‘as-the-crow-flies’ geographic distances. Conversely, using alternative European (Elveden), South Asian (Attirampakkam) and Levantine (Tabun) sites as start points for the calculation of geographic distances, did not produce a significant result in any instance. This reduces the probability that the significant relationship between geographic distance from East Africa and within-group variance is the result of random factors. However, while our analyses are consistent with the stated predictions, at least 50% of within assemblage variance cannot be explained by the model. This suggests that extraneous factors are influencing the data. There are at least seven potential reasons1 why the correlation between geographic distance and variance is not stronger than evinced in our analyses (Fig. 5): 1) Raw material. It has long been considered that lithic raw materials will have an influence on the form of stone tools due to variations in the brittleness, elasticity, homogeneity and granularity of different categories of stone (Clegg, 1977; Goodman, 1944). If such factors are at work here, it may provide a source of increased artefact variability than predicted by the iterative founder effect model for some assemblages. However, comparison of Table 1 with Figs. 3 and 4 suggest no clear pattern in this regard. Some assemblages made of lava, for instance, exhibit variances higher than might be predicted by the regressions (e.g. Lewa), although other assemblages made of lava (e.g. Kariandusi) exhibit variance well below expectations. There are also instances where assemblages (e.g. Morgah and St. Acheul) are made of different raw material (i.e. quartzite and chert respectively), yet do not have significantly

1

We do not imply that this list is exhaustive.

different mean within-group variances (t ¼ 0.192, df ¼ 94, p ¼ 0.85). This is also the case with Elveden (chert) and Kariandusi (lava) (t ¼ 0.394, df ¼ 94, p ¼ 0.69). 2) Selection (natural and/or cultural). In contrast to neutral genetic data employed in analyses testing hypotheses of human genetic diversity (e.g. Prugnolle et al., 2005; Ramachandran et al., 2005), the artefactual variation under consideration here may not be selectively neutral (cf. Bentley et al., 2004; O’Brien and Lyman, 2003; Shennan and Wilkinson, 2001). It has been suggested that attributes of handaxe form may affect their functional utility as cutting and chopping tools (Jones, 1980; Machin et al., 2007; Vaughan, 2001), be culturally selected for aesthetic reasons (Clark, 1975; Wynn, 2000), or result from sexual selection (Kohn and Mithen, 1999). Selection of any kind would have the effect of directing artefactual variation in a manner that would not conform directly to the assumptions of the iterative founder effect model. Conformist bias, whereby individuals imitate the most common behavioural pattern in a given population (Boyd and Richerson, 1985; Whiten et al., 2005) constitutes an additional example of (frequency dependent) cultural selection that could exacerbate this. 3) Inter-group cultural transmission between different groups and regions. The iterative founder effect model does not assume horizontal transmission between different dispersing populations. If, however, hominin populations came into sufficiently close contact that cultural transmission between regions took place, this would provide a source of variability that may confound the predictions of the iterative founder effect model. 4) Incorrect calculation of dispersal routes and geographic distances. Our results are clearly dependent upon the estimates of geographic distances employed. In this regard it is important to note that recent debates regarding hominin dispersals out of Africa have contrasted a potential crossing of the Bab al Mandab strait into the Arabian peninsula (amongst others) with the north African-Sinai dispersal route (e.g. Bar-Yosef and BelferCohen, 2001; Beyin, 2006; Derricourt, 2005; Field and Lahr, 2005; Petraglia, 2003; Whalen et al., 1989), although the former route, if used, would likely have involved the crossing of a waterway by the time of the earliest known handaxe traditions in Africa (Fernandes et al., 2006). While (as noted above) the minimum-spanning network distances are a more reasonable approximation of the distances covered in a hypothetical dispersal route compared with the ‘as-the-crow-flies’ distances,

558

S.J. Lycett, N. von Cramon-Taubadel / Journal of Archaeological Science 35 (2008) 553e562

Raw material, Selection, Time/innovation, Between-group transmission

Subsequent migration back toward Africa

Demographic point of origin

Fig. 5. Potential factors that may lead to deviations from the predictions of the iterative founder effect model (as shown in Fig. 1), and weaken the relationship between within-assemblage variance and distance from East Africa. Raw material variations, selection, between-group transmission and innovations, may all operate and lead to within-assemblage variances greater than those predicted by the model. Migrations of hominin populations back toward origin (Africa) may lead to variances less than predicted by the model (compare this with the idealised model depicted in Fig. 1).

the exact routes and distances covered by hominins are presently unknown. More accurate estimations of route(s) and distances would potentially lead to a better fit between artefact within-group variance and geographic distance than shown in our results. 5) Lithic sample(s) do not accurately reflect variance. That is, variance may be under-represented in certain samples closer to East Africa. For example, the Kharga Oasis assemblage is an excavated sample that has been interpreted as a possible incidence of artefact caching (Caton-Thompson, 1952: 57). Indeed, the various artefact samples employed here may reflect different activities and behaviours at various scales, which themselves have a structuring effect on artefact variance. Surface collections further away from Africa (e.g. Morgah and Attirampakkam) may have greater than expected variances due to the potential of extended chronological usage of palimpsest surface sites. Sample size is also a concern here, although as with raw material, comparison of Table 1 with Figs. 3 and 4 does not immediately support a clear pattern in this regard. For instance, Olduvai is the smallest assemblage in the data set (n ¼ 13) and exhibits the highest variance, although the Lewa assemblage has the second highest variance yet this contains the maximum number of 30 artefacts. Likewise, Kariandusi has the lowest variance of any of the African assemblages yet is equal in sample size to Lewa. Moreover, a regression of sample size against within-group variance values does not evince a significant relationship (r2 ¼ 0.235, p ¼ 0.156). 6) Accumulation of cultural mutations through time. Differential longevity of hominin populations in each region also requires consideration. It has been noted that not all hominin

dispersal events need necessarily have resulted in the permanent colonisation of a given area (Dennell, 2003). Therefore, it is possible that assemblages do not represent the same length of hominin population duration. All other things being equal, population longevity will result in higher levels of assemblage variation due to the accumulation of cultural innovations through time. This is analogous to the situation in population genetics, where genetic diversity increases as a function of time alone due to the accumulation of mutations (Neiman, 1995). Assessing the influence of such factors in Palaeolithic data presents considerable challenges. However, it has been argued that twisted ovate handaxes from Elveden (UK) represent a specific cultural variant of biface manufacture (ca. late Marine Isotope Stage 11 e early MIS 10) (White, 1998b). In our analysis this assemblage (33% of which exhibit a twisted ovate profile) exhibits higher within-group variance than would be predicted by the model (Figs. 3 and 4). 7) Subsequent hominin migrations may involve a movement back toward Africa. Just as recent migrations of modern humans are known to obscure patterns in genetic data (Relethford, 2003), dispersal of hominin populations back toward Africa would lead to patterns of variance that do not fit the iterative founder effect model. Note that this need not even require inter-group transmission (see point 3, above), to exert an effect contrary to the geographic distance assumptions of the model (Fig. 5). Given that any or all of these factors (and indeed others) may be in operation with regard to the data under consideration here (Fig. 5), the fact that our results indicate that as much as 50% of the within-group variance in the handaxe samples can be explained by geographic distance from East Africa, is

S.J. Lycett, N. von Cramon-Taubadel / Journal of Archaeological Science 35 (2008) 553e562

noteworthy. Under such circumstances these results demand further exploration via an increased morphometric and artefactual database. 4.1. Potential implications for the absence of the Acheulean at certain points in time and space The results of our analyses have potential implications for debates concerning the differing geographical and chronological representation of Mode 1 (i.e. ‘handaxe’ free core, ‘chopper’ and flake-tool assemblages) versus Mode 2 (i.e. Acheulean) Lower Palaeolithic technological traditions (e.g. Keates, 2002; Mithen, 1994; Schick, 1994; White, 2000). In particular, our results may lend credence to an hypothesis that instances of Lower Palaeolithic Mode 1 lithic production east of the so-called ‘Movius Line’, and in other regions (such as some ‘Clactonian’ assemblages in Britain), are a reflection of lower demographic levels in colonising or peripheral hominin (Acheulean) populations. As Neiman (1995) and Shennan (2000) have outlined, when populations are small, chance plays a greater role in determining which cultural elements will be transmitted to subsequent generations. In other words, drift will tend to have greater effect upon cultural evolutionary outcomes in small populations. Conversely, when population sizes are relatively large, there is greater potential for different cultural practices to be compared, and adaptive traits are more likely to be a maintained within the population rather than lost through stochastic processes or swamped by drift (Shennan, 2000: 815). As Shennan (2000) has pointed out, such factors place greater emphasis on the role of population increases, crashes, fluctuations and localised extinctions in shaping not only biological evolution, but also cultural evolution. Henrich (2004) has also shown via modelling that a decrease in effective population size (Ne) may lead to a loss of pre-existing cultural elements. This effect is due to the fact that in each instance of cultural transmission, copying will be imperfect leading to a variation around a mean in terms of population skill level. The greater the number of models, the more choice is available for selecting the best (i.e. most skilled) model to copy. Hence, the chances of copying the most skilled elements of a given practice, correlates directly with the number of models from which to copy. As Henrich (2004: 203) states, ‘‘cultural learning becomes cumulatively adaptive when the effect of having a larger set of models from which to pick the most skilled, exceeds the losses from imperfect copying’’. Moreover, Henrich (2004: 197) avers that under such circumstances, the importance of demography is a reflection of three inter-related factors: population size, density and interconnectedness. In this regard, it is interesting to note that Van Schaik et al. (2003) have shown that in the case of orangutan cultural behaviours, increased opportunity for social associations beyond those of close kin (within a group) directly correlates with the size of cultural repertoire exhibited by different groups. Perhaps pertinently, major barriers to dispersal from the Indian subcontinent (i.e. the eastern extent of Mode 2 Acheulean industries) into eastern Asia exist in the form the Himalayan Mountains and the Ganges-Brahmaputra Delta, which could

559

further accentuate reduction of effective population sizes resulting from dispersal(s). The Himalaya-Karakoram ranges are the world’s most elevated mountain chain. Extending across five modern countries (Bhutan, China, India, Nepal, and Pakistan) such a ‘feature’ perhaps requires little discussion as an impediment to dispersal. The Ganges-Brahmaputra Delta derives from the confluence of three rivers: the Lower Ganges, the Lower Brahmaputra and the Meghna (Agarwal and Mitra, 1991). As Field and Lahr (2005: 22) have noted recently, the size of the Ganges-Brahmaputra river system is likely to have been an impediment to hominin dispersals. Paucity of lithic raw material may also have inhibited movement of hominins in this region (Dennell, 2007). Interestingly, Ayres and Clutton-Brock (1992) have previously shown that rivers play a key role in constraining the dispersal of Amazonian primate taxa. Rivers also appear to have some effect in the restricting the dispersal of chimpanzee (Pan troglodytes) populations, and have played a role in structuring resulting patterns of genetic diversity (Gagneux et al., 2001; Gonder et al., 2006). If rivers had a similar constraining effect on hominin dispersals in the area around the Bay of Bengal, it is plausible that hominin dispersals into East Asia from the subcontinent involved relatively low numbers into what is a large geographic region. Shennan (2001: 15) has suggested that stasis in Mode 2 technologies during the Pleistocene may be due to small populations. However, note that according to the hypothesis presented here, the maintenance of such stasis required certain demographic thresholds (in terms of population size, density, clustering and interconnectedness) that were not matched by those populations east of the Movius Line, and perhaps at certain periods in northern latitudes, leading to the periodic appearance of Mode 1 technologies such as some of those assemblages from Britain currently referred to as ‘Clactonian’ (Wenban-Smith, 1998; White, 2000). It should also be noted that Henrich (2004) has argued that the effects of smaller populations leading to loss of cultural elements due to imperfect copying, will be exacerbated when the skill level required to replicate a given task is relatively more complex. Such factors may be particularly important when considering the relative skills required in the manufacture of Mode 1 versus Mode 2 artefacts (Mithen, 1994; Schick, 1994; Schick and Toth, 1993; Wenban-Smith, 1998). Mithen (1994) has previously presented a model based on putative inter-relationships between environmental factors, group size and social learning to explain the occurrence of Mode 1 (Clactonian) and Mode 2 (Acheulean) assemblages at different Lower Palaeolithic sites in southern Britain. Mithen argued that Clactonian assemblages were consistently linked with wooded environments associated with interglacial conditions, while Acheulean assemblages were associated with sites from more open glacial conditions. Moreover, Mithen posited that hominin group sizes would be larger in more open environments, facilitating greater social learning. Conversely, it was argued that more wooded closed habitats would lead to a reduction of social group size and, as a result, capacity for social learning would be more restricted. Mithen did not make a clear distinction between ‘group size’ (a key

560

S.J. Lycett, N. von Cramon-Taubadel / Journal of Archaeological Science 35 (2008) 553e562

variable is his model) and effective population size (Ne) that is an important element of more recent debates (e.g. Neiman, 1995; Shennan, 2000, 2001). Moreover, Mithen’s (1994) specific model and case study have been criticised on theoretical and empirical grounds. The assertion that wooded environments will lead to smaller hominin group sizes and ultimately constrain incidences of social learning has been challenged by Wenban-Smith (1996), who notes that other workers (e.g. Gamble, 1986) have reached directly contrasting conclusions. The tight association of Mode 1 and Mode 2 assemblages with specific environmental conditions (i.e. inter-glacialclosed and glacialopen) has also been questioned (e.g. McNabb and Ashton, 1995; Roe, 1994; White, 2000: 48e49). Note that, unlike Mithen’s (1994) model, the hypothesis presented here is not predicated upon tight links between demography and particular environments, nor between particular technologies and specific environmental conditions. It states simply that dispersing Acheulean hominin populations will have lower effective population sizes at the extremities of their range, and this may lead to a loss of technological diversity and complexity (i.e. cessation of handaxe production). Some workers (e.g. Gamble and Marshall, 2001; Hou et al., 2000; Yi and Clark, 1983) have argued that occasional occurrences of handaxe-like technologies in East Asia mitigate against a strict Mode 1 versus Mode 2 distribution straddling the Movius Line. However, the morphology of such ‘handaxes’ in terms of an affinity with genuine Acheulean examples has been questioned (e.g. Corvinus, 2004; Schick, 1994; Schick and Zhuan, 1993), as have issues regarding the chronological integrity of such specimens (e.g. Dennell, 2003; Schick, 1994). Indeed, Norton et al. (2006) found statistically significant differences in the thickness of handaxe-like artefacts from the Imjin/Hantan River basins (Korea) compared with bifaces from the Acheulean sites of Hungsi-Baichbal Valleys (India) and Olorgesailie (Kenya). Issues of dating and identification aside, however, it should be noted that the model presented here is consistent with the possibility that Acheuleanlike technological elements may have occurred sporadically in East Asia (or indeed the production of ‘non-classic’ bifaces in Clactonian assemblages [Ashton and McNabb, 1994]), yet never reached the proliferation of the Acheulean phenomenon seen in many other regions west of the Movius Line due to small effective population sizes. 5. Conclusions Our analyses support the hypothesis that Acheulean handaxe technologies evolved in Africa and dispersed with migrating hominin populations into northern and western Eurasia, under the assumptions of an iterative founder effect (repeated bottlenecking) model. We emphasise that our results should be seen as preliminary and require further testing with an increased morphometric and artefactual data set. It may be particularly beneficial if further studies investigate more fully than we have attempted here, the strength of any potential relationship between chronology and within-assemblage variance (which is not, in itself, inconsistent with the African

dispersal hypothesis given that the oldest currently known assemblages are from Africa). Further work should also aim to assess more clearly the relative influence of the seven factors identified here that may be leading to deviations from the predictions of the dispersal model. However, we believe that within the context of current debates these results require discussion, and that the demographic model-bound approach to artefactual variation described here will prove useful in future studies, not only in regard to Acheulean dispersals, but also in a range of archaeological situations. Moreover, these results imply that when differences in Acheulean biface form are found in different regions, such differences may not entirely be due to the more traditionally discussed factors such as raw material, cognitive/biomechanical differences, functional differences, nor even the existence of different ‘target forms’ or ‘mental templates’. Some of the variation may be attributable to the process of random cultural drift, mediated by demographic factors. We are also cautiously optimistic that these results hint at the potential for archaeological data to provide an estimation of demographic parameters and hominin dispersals in situations where fossil evidence is inadequate. Finally, based on our results we suggest that the occurrence of Mode 1 techno-complexes such as the Clactonian of Britain, or the non-Acheulean (Mode 1) assemblages east of the Movius Line, plausibly represent instances where Ne dropped below a demographic threshold such that Acheulean Mode 2 techniques of lithic production could not be maintained (Henrich, 2004). A demographic model would also explain the ephemeral occurrence of ‘Acheulean-like’ elements in Clactonian (Ashton and McNabb, 1994) and East Asian assemblages (Hou et al., 2000; Norton et al., 2006), with demography acting as a source of constraint upon technological evolution in those regions. Acknowledgements We are indebted to Parth Chauhan, Mark Collard, Robin Dennell and Robert Foley for productive discussions, comments and encouragement. We are also grateful to the anonymous reviewers for their thoughtful and constructive comments, which were extremely helpful when revisiting the draft. Needless to say, any remaining errors or omissions are entirely our own. Access to lithic material and hospitability during data collection were gratefully received from Anne Taylor, Assistant Curator, Cambridge University Museum of Archaeology and Anthropology. SJL’s work on this project was funded by Trinity College, University of Cambridge. NvCT is funded by St John’s College, University of Cambridge and a Gates Trust Scholarship. References Agarwal, R.P., Mitra, D.S., 1991. Paleogeographic reconstruction of Bengal Delta during Quaternary period. (Special Volume: Quaternary Deltas of India, Vaidyannadhan, R., Ed.). Memoirs Geological Society of India 22, 13e24.

S.J. Lycett, N. von Cramon-Taubadel / Journal of Archaeological Science 35 (2008) 553e562 Anto´n, S.C., Swisher, C.C., 2004. Early dispersals of Homo from Africa. Annual Review of Anthropology 33, 271e296. Asfaw, B., Beyene, Y., Suwa, G., Walter, R.C., White, T.D., WoldeGabriel, G., Yemane, T., 1992. The earliest Acheulean from Konso-Gardula. Nature 360, 732e735. Ashton, N., McNabb, J., 1994. Bifaces in perspective. In: Ashton, N., David, A. (Eds.), Stories in Stone: Lithic Studies Society Occasional Paper No. 4. Lithic Studies Society, London, pp. 182e191. Ayres, J.M., Clutton-Brock, T.H., 1992. River boundaries and species range size in Amazonian primates. American Naturalist 140, 531e537. Bar-Yosef, O., Belfer-Cohen, A., 2001. From Africa to Eurasia e early dispersals. Quaternary International 75, 19e28. Beyin, A., 2006. The Bab al Mandab vs the Nile-Levant: an appraisal of the two dispersal routes for early modern humans out of Africa. African Archaeological Review 23, 5e30. Biro, D., 2003. Cultural innovation and transmission of tool use in wild chimpanzees: evidence from field experiments. Animal Cognition 6, 213e223. Bentley, R.A., Hahn, M.W., Shennan, S., 2004. Random drift and culture change. Proceedings of the Royal Society of London B 271, 1443e1450. Bonnie, K.E., Horner, V., Whiten, A., de Waal, F.B.M., 2007. Spread of arbitrary conventions among chimpanzees: a controlled experiment. Proceedings of the Royal Society of London B 274, 367e372. Boyd, R., Richerson, P.J., 1985. Culture and the Evolutionary Process. University of Chicago Press, Chicago. Callow, P., 1986. A comparison of British and French Acheulian bifaces. In: Collcutt, S.N. (Ed.), The Palaeolithic of Britain and its Nearest Neighbours: Recent Trends. University of Sheffield, Sheffield, pp. 3e7. Carbonell, E., Mosquera, M., Xose, P.R., Sala, R., 1999. Out of Africa: the dispersal of the earliest technical systems reconsidered. Journal of Anthropological Archaeology 18, 119e136. Caton-Thompson, G., 1952. Kharga Oasis in Prehistory. Athlone Press, London. Clark, J.D., 1975. Africa in prehistory: peripheral or paramount? Man (NS) 10, 175e198. Clark, J.D., 1994. The Acheulian industrial complex in Africa and elsewhere. In: Corruccini, R.S., Ciochon, R.L. (Eds.), Integrative Paths to the Past. Prentice Hall, Englewood Cliffs, NJ, pp. 451e469. Clark, J.D., 1998. The Early Palaeolithic of the eastern region of the Old World in comparison to the west. In: Korisettar, R., Petraglia, M.D. (Eds.), Early Human Behaviour in Global Context: The Rise and Diversity of the Lower Palaeolithic Record. Routledge, London, pp. 437e450. Clark, J.D., 2001. Variability in primary and secondary technologies of the Later Acheulian in Africa. In: Milliken, S., Cook, J. (Eds.), A Very Remote Period Indeed: Papers on the Palaeolithic Presented to Derek Roe. Oxbow Books, Oxford, pp. 1e18. Clegg, J.K., 1977. The four dimensions of artefactual variation. In: Wright, R.V.S. (Ed.), Stone Tools as Cultural Markers: Change, Evolution and Complexity. Australian Institute of Aboriginal Studies, Canberra, pp. 60e66. Corvinus, G., 2004. Homo erectus in East and Southeast Asia, and the questions of the age of the species and its association with stone artifacts, with special reference to handaxe-like tools. Quaternary International 117, 141e151. Crompton, R.H., Gowlett, J.A.J., 1993. Allometry and multidimensional form in Acheulean bifaces from Kilombe, Kenya. Journal of Human Evolution 25, 175e199. Dennell, R.W., 2003. Dispersal and colonisation, long and short chronologies: how continuous is the Early Pleistocene record for hominids outside East Africa. Journal of Human Evolution 45, 421e440. Dennell, R.W., 2007. ‘‘Resource-rich, stone poor’’: early hominin land use in large river systems of northern India and Pakistan. In: Petraglia, M.D., Allchin, B. (Eds.), The Evolution and History of Human Populations in South Asia. Springer, Berlin, pp. 41e68. Dennell, R.W., Roebroeks, W., 2005. An Asian perspective on early human dispersal from Africa. Nature 438, 1099e1104. Derricourt, R., 2005. Getting ‘‘out of Africa’’: sea crossings, land crossings and culture in the hominin migrations. Journal of World Prehistory 19, 119e132.

561

Falsetti, A.B., Jungers, W.L., Cole III, T.M., 1993. Morphometrics of the Callitrichid forelimb: a case study in size and shape. International Journal of Primatology 14, 551e572. Fernandes, C.A., Rohling, E.J., Siddall, M., 2006. Absence of post-Miocene Red Sea land bridges: biogeographic implications. Journal of Biogeography 33, 961e966. Field, J.S., Lahr, M.M., 2005. Assessment of the southern dispersal: GIS-based analyses of potential routes at Oxygen Isotopic Stage 4. Journal of World Prehistory 19, 1e45. Gagneux, P., Gonder, M.K., Goldberg, T.L., Morin, P.A., 2001. Gene flow in wild chimpanzee populations: what genetic data tell us about chimpanzee movement over space and time. Philosophical Transactions of the Royal Society of London B 356, 889e897. Gamble, C., 1986. The Palaeolithic Settlement of Europe. Cambridge University Press, Cambridge. Gamble, C., 1993. Timewalkers: The Prehistory of Global Colonization. Penguin, London. Gamble, C., Marshall, G., 2001. The shape of handaxes, the structure of the Acheulian world. In: Milliken, S., Cook, J. (Eds.), A Very Remote Period Indeed: Papers on the Palaeolithic Presented to Derek Roe. Oxbow Books, Oxford, pp. 19e27. Gonder, M.K., Disotell, T.R., Oates, J.F., 2006. New genetic evidence on the evolution of chimpanzee populations and implications for taxonomy. International Journal of Primatology 27, 1103e1127. Goodman, M.E., 1944. The physical properties of stone tool materials. American Antiquity 9, 415e433. Goren-Inbar, N., Feibel, C.S., Verosub, K.L., Melamed, Y., Kislev, M.E., Tchernov, E., Saragusti, I., 2000. Pleistocene milestones on the out-ofAfrica corridor at Gesher Benot Ya’aqov, Israel. Science 289, 944e947. Gowlett, J.A.J., Crompton, R.H., 1994. Kariandusi: Acheulean morphology and the question of allometry. The African Archaeological Review 12, 3e42. Harpending, H., Rogers, A., 2000. Genetic perspectives on human origins and differentiation. Annual Review of Genomics and Human Genetics 1, 361e385. Henrich, J., 2004. Demography and cultural evolution: how adaptive cultural processes can produce maladaptive losses e the Tasmanian case. American Antiquity 69, 197e214. Holmes, K.M., 2007. Using Pliocene palaeoclimatic data to postulate dispersal pathways of early hominins. Palaeogeography, Palaeoclimatology, Palaeoecology 248, 96e108. Hou, Y., Potts, R., Baoyin, Y., Zhengtang, G., Deino, A., Wei, W., Clark, J., Guangmao, X., Weiwen, H., 2000. Mid-Pleistocene Acheulean-like stone technology of the Bose Basin, South China. Science 287, 1622e1626. Jones, P.R., 1980. Experimental butchery with modern stone tools and its relevance for Palaeolithic archaeology. World Archaeology 12, 153e165. Jungers, W.L., Falsetti, A.B., Wall, C.E., 1995. Shape, relative size, and size adjustments in morphometrics. Yearbook of Physical Anthropology 38, 137e161. Keates, S.G., 2002. The Movius Line: fact or fiction? Bulletin of the IndoPacific Prehistory Association 22, 17e24. Kohn, M., Mithen, S., 1999. Handaxes: products of sexual selection? Antiquity 73, 518e526. Kuman, K., Clarke, R.J., 2000. Stratigraphy, artefact industries and hominid associations for Sterkfontein, Member 5. Journal of Human Evolution 38, 827e847. Lahr, M.M., Foley, R., 1994. Multiple dispersals and modern human origins. Evolutionary Anthropology 3, 48e60. Leakey, M.D., 1971. Olduvai Gorge: Excavations in Beds I and II, 1960e 1963, Vol. 3. Cambridge University Press, Cambridge. Linz, B., Balloux, F., Moodley, Y., Manica, A., Liu, H., Roumagnac, P., Falush, D., Stamer, C., Prugnolle, F., van der Merwe, S.W., Yamaoka, Y., Graham, D.Y., Perez-Trallero, E., Wadstrom, T., Suerbaum, S., Achtman, M., 2007. An African origin for the intimate association between humans and Helicobacter pylori. Nature 445, 915e918. Lycett, S.J., 2007. Is the Soanian techno-complex a Mode 1 or Mode 3 phenomenon? A morphometric assessment. Journal of Archaeological Science 34, 1434e1440.

562

S.J. Lycett, N. von Cramon-Taubadel / Journal of Archaeological Science 35 (2008) 553e562

Lycett, S.J., von Cramon-Taubadel, N., Foley, R.A., 2006. A crossbeam co-ordinate caliper for the morphometric analysis of lithic nuclei: a description, test and empirical examples of application. Journal of Archaeological Science 33, 847e861. Machin, A.J., Hosfield, R.T., Mithen, S.J., 2007. Why are some handaxes symmetrical? Testing the influence of handaxe morphology on butchery effectiveness. Journal of Archaeological Science 34, 883e893. McGrew, W.C., 1992. Chimpanzee Material Culture: Implications for Human Evolution. Cambridge University Press, Cambridge. McGrew, W.C., 2004. The Cultured Chimpanzee: Reflections on Cultural Primatology. Cambridge University Press, Cambridge. McNabb, J., Ashton, N., 1995. Thoughtful flakers. Cambridge Archaeological Journal 5, 289e301. McNabb, J., Binyon, F., Hazelwood, L., 2004. The large cutting tools from the South African Acheulean and the question of social traditions. Current Anthropology 45, 653e677. McPherron, S.P., 1999. Ovate and pointed handaxe assemblages: two points make a line. Pre´histoire Europe´enne 14, 9e32. McPherron, S.P., 2000. Handaxes as a measure of the mental capabilities of early hominids. Journal of Archaeological Science 27, 655e663. Mellars, P., 2006. Going east: new genetic and archaeological perspectives on the modern human colonization of Eurasia. Science 313, 796e800. Mithen, S., 1994. Technology and society during the Middle Pleistocene: hominid group size, social learning and industrial variability. Cambridge Archaeological Journal 4, 3e32. Mithen, S., 1999. Imitation and cultural change: a view from the Stone Age, with specific reference to the manufacture of handaxes. In: Box, H.O., Gibson, K.R. (Eds.), Mammalian Social Learning: Comparative and Ecological Perspectives. Cambridge University Press, Cambridge, pp. 389e399. Mithen, S., Reed, M., 2002. Stepping out: a computer simulation of hominid dispersal from Africa. Journal of Human Evolution 43, 433e462. Movius, H.L., 1948. The Lower Palaeolithic cultures of southern and eastern Asia. Transactions of the American Philosophical Society 38, 329e426. Neiman, F.D., 1995. Stylistic variation in evolutionary perspective: inferences from decorative diversity and interassemblage distance in Illinois Woodland ceramic assemblages. American Antiquity 60, 7e36. Norton, C.J., Bae, K., Harris, J.W.K., Lee, H., 2006. Middle Pleistocene handaxes from the Korean Peninsula. Journal of Human Evolution 51, 527e536. O’Brien, M.J., Lyman, R.L., 2003. Style, function, transmission; an introduction. In: O’Brien, M.J., Lyman, R.L. (Eds.), Style, Function, Transmission. University of Utah Press, Salt Lake City, pp. 1e32. Petraglia, M.D., 2003. The Lower Palaeolithic of the Arabian Peninsula: occupations, adaptations, and dispersals. Journal of World Prehistory 17, 141e179. Prugnolle, F., Mancia, A., Balloux, F., 2005. Geography predicts neutral genetic diversity of human populations. Current Biology 15, 159e160. Ramachandran, S., Deshpande, O., Roseman, C.C., Rosenberg, N.A., Feldman, M.W., Cavalli-Sforza, L.L., 2005. Support from the relationship of genetic and geographic distance in human populations for serial founder effect originating in Africa. Proceedings of the National Academy of Sciences USA 102, 15942e15947. Relethford, J.H., 2003. Reflections of Our Past: How Human History is Revealed in Our Genes. Westview Press, Oxford. Roe, D., 1976. Typology and the trouble with handaxes. In: de Sieveking, G., Longworth, I.H., Wilson, K.E. (Eds.), Problems in Economic and Social Archaeology. Duckworth, London, pp. 61e70. Roe, D., 1994. Comment on Mithen 1994. Cambridge Archaeological Journal 4, 18e19. Roebroeks, W., 2006. The human colonisation of Europe: where are we? Journal of Quaternary Science 21, 425e435. Saragusti, I., Goren-Inbar, N., 2001. The biface assemblage from Gesher Benot Ya’aqov, Israel: illuminating patterns in ‘out of Africa’ dispersal. Quaternary International 75, 85e89.

Schick, K.D., 1994. The Movius line reconsidered. In: Corruccini, R.S., Ciochon, R.L. (Eds.), Integrative Paths to the Past. Prentice Hall, Englewood Cliffs, NJ, pp. 569e596. Schick, K.D., Toth, N., 1993. Making Silent Stones Speak: Human Evolution and the Dawn of Human Technology. Weidenfeld and Nicolson, London. Schick, K.D., Zhuan, D., 1993. Early Paleolithic of China and Eastern Asia. Evolutionary Anthropology 2, 22e35. Shennan, S., 2000. Population, culture history, and the dynamics of culture change. Current Anthropology 41, 811e835. Shennan, S., 2001. Demography and cultural innovation: a model and its implications for the emergence of modern human culture. Cambridge Archaeological Journal 11, 5e16. Shennan, S.J., Steele, J., 1999. Cultural learning in hominids: a behavioural ecological approach. In: Box, H.O., Gibson, K.R. (Eds.), Mammalian Social Learning: Comparative and Ecological Perspectives. Cambridge University Press, Cambridge, pp. 367e388. Shennan, S.J., Wilkinson, J.R., 2001. Ceramic style change and neutral evolution: a case study from Neolithic Europe. American Antiquity 66, 577e593. Sinnott, R.W., 1984. Virtues of the haversine. Sky and Telescope 68, 159. Stout, D., 2002. Skill and cognition in stone tool production. Current Anthropology 43, 693e722. Van Schaik, C.P., Ancrenaz, M., Borgen, G., Galdikas, B., Knott, C.D., Singleton, I., Suzuki, A., Utami, S.S., Merrill, M., 2003. Orangutan cultures and the evolution of material culture. Science 299, 102e105. Vaughan, C.D., 2001. A million years of style and function: regional and temporal variation in Acheulean handaxes. In: Hurt, T.D., Rakita, G.F.M. (Eds.), Style and Function: Conceptual Issues in Evolutionary Archaeology. Bergin & Garvey, Westport, Connecticut, pp. 141e163. Wenban-Smith, F.F., 1996. Another one bites the dust. Lithics 16, 99e107. Wenban-Smith, F.F., 1998. Clactonian and Acheulian industries in Britain: their chronology and significance reconsidered. In: Ashton, N., Healy, F., Pettitt, P. (Eds.), Stone Age Archaeology: Essays in Honour of John Wymer. Oxbow Books, Oxford, pp. 90e97. Whalen, N.M., Davis, W.P., Pease, D.W., 1989. Early Pleistocene migrations into Saudi Arabia. Atlal 12, 59e75. White, M.J., 1998a. On the significance of Acheulean biface variability in southern Britain. Proceedings of the Prehistoric Society 64, 15e44. White, M.J., 1998b. Twisted ovate bifaces in the British Lower Palaeolithic: some observations and implications. In: Ashton, N., Healy, F., Pettitt, P. (Eds.), Stone Age Archaeology: Essays in Honour of John Wymer. Oxbow Books, Oxford, pp. 98e104. White, M.J., 2000. The Clactonian question: on the interpretation of core-andflake assemblages in the British Lower Palaeolithic. Journal of World Prehistory 14, 1e63. Whiten, A., 2005. The second inheritance system of chimpanzees and humans. Nature 437, 52e55. Whiten, A., Goodall, J., McGrew, W.C., Nishida, T., Reynolds, V., Sugiyama, Y., Tutin, C.E.G., Wrangham, R.W., Boesch, C., 2001. Charting cultural variation in chimpanzees. Behaviour 138, 1481e1516. Whiten, A., Horner, V., de Waal, F.B.M., 2005. Conformity to cultural norms of tool use in chimpanzees. Nature 437, 737e740. Wynn, T., 1979. The intelligence of later Acheulean hominids. Man (NS) 14, 371e391. Wynn, T., 1995. Handaxe enigmas. World Archaeology 27, 10e24. Wynn, T., 2000. Symmetry and the evolution of the modular linguistic mind. In: Carruthers, P., Chamberlain, A. (Eds.), Evolution and the Human Mind: Modularity, Language and Meta-Cognition. Cambridge University Press, Cambridge, pp. 113e139. Wynn, T., Tierson, F., 1990. Regional comparison of the shapes of later Acheulean handaxes. American Anthropologist 92, 73e84. Yi, S., Clark, G.A., 1983. Observations on the Lower Palaeolithic of Northeast Asia. Current Anthropology 24, 181e202.