Abstract
The identification of material culture variability remains an important goal in archaeology, as such variability is commonly coupled with interpretations of cultural transmission and adaptation. While most archaeological cultures are defined on the basis of typology and research tradition, cultural evolutionary reasoning combined with computer-aided methods such as geometric morphometrics (GMM) can shed new light on the validity of many such entrenched groupings, especially in regard to European Upper Palaeolithic projectile points and their classification. Little methodological consistency, however, makes it difficult to compare the conclusions of such studies. Here, we present an effort towards a benchmarked, case-transferrable toolkit that comparatively explores relevant techniques centred on outline-based GMM. First, we re-analyse two previously conducted landmark-based analyses of stone artefacts using our whole-outline approach, demonstrating that outlines can offer an efficient and reliable alternative. We then show how a careful application of clustering algorithms to GMM outline data is able to successfully discriminate between distinctive tool shapes and suggest that such data can also be used to infer cultural evolutionary histories matching already observed typo-chronological patterns. Building on this baseline work, we apply the same methods to a dataset of large tanged points from the European Final Palaeolithic (ca. 15,000–11,000 cal BP). Exploratively comparing the structure of design space within and between the datasets analysed here, our results indicate that Final Palaeolithic tanged point shapes do not fall into meaningful regional or cultural evolutionary groupings but exhibit an internal outline variance comparable to spatiotemporally much closer confined artefact groups of post-Palaeolithic age. We discuss these contrasting results in relation to the architecture of lithic tool design spaces and technological differences in blank production and tool manufacture.
Highlights
The robust identification of material culture variability remains an important goal in Palaeolithic archaeology, given that such variability is commonly coupled with interpretations of culture change, demography and adaptation
In the Final Palaeolithic of Europe and the Paleoindian period of North America — what Williams and Madsen (2019) collectively refer to as the ‘Late Upper Palaeolithic’ — most such archaeological units are diagnosed, characterised and interpreted on the basis of artefact typology, that of lithic projectile points. Critiques of such type-centred approaches abound (Bisson, 2000; Monnier & Missal, 2014), and recent applications of cultural evolutionary reasoning combined with computer-aided methods such as geometric morphometrics (GMM) have raised doubts as to the validity of many such entrenched groupings (Buchanan et al, 2020; Ivanovaitė et al, 2020; MacLeod, 2018; Serwatka & Riede, 2016)
We show that our clustering protocol successfully replicates traditional techno-typological groupings and that the archaeological typo-chronology for this period, especially in North-West France, can be retrieved in a phenogram inferred from outline data using the neighbour joining (NJ) algorithm
Summary
The robust identification of material culture variability remains an important goal in Palaeolithic archaeology, given that such variability is commonly coupled with interpretations of culture change, demography and adaptation. In the Final Palaeolithic of Europe and the Paleoindian period of North America — what Williams and Madsen (2019) collectively refer to as the ‘Late Upper Palaeolithic’ — most such archaeological units are diagnosed, characterised and interpreted on the basis of artefact typology, that of lithic projectile points Critiques of such type-centred approaches abound (Bisson, 2000; Monnier & Missal, 2014), and recent applications of cultural evolutionary reasoning combined with computer-aided methods such as geometric morphometrics (GMM) have raised doubts as to the validity of many such entrenched groupings (Buchanan et al, 2020; Ivanovaitė et al, 2020; MacLeod, 2018; Serwatka & Riede, 2016). It has further been argued that the purported ‘cultural’ differences perpetuated through many traditional artefact typologies are more often than not the products of contingent disciplinary histories, rather than reflecting robust empirical realities (cf. Clark and Riel-Salvatore, 2006; Reynolds & Riede, 2019)
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