Design Space Constraints and the Cultural Taxonomy of European Final Palaeolithic Large Tanged Points: A Comparison of Typological, Landmark-Based and Whole-Outline Geometric Morphometric Approaches

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.

The contribution of integrated 3D model analysis to Protoaurignacian stone tool design

“…Nonparametric MANOVA (i.e., PERMANOVA) was preferred to its parametric counterpart because the Box’s Test of Equality of Covariance Matrices ran in SPSS showed in all cases a violation of the assumption of homogeneity of covariance. For the PERMANOVA, we used 10,000 repetitions and calculated pairwise distances using Euclidean distance following [ 59 ]. We used Holm–Bonferroni sequential corrections for all probability tests to reduce the likelihood of performing a type 1 error [ 89 ].…”

“…EFA is able to deconstruct the outline into a series of closed curves (harmonics) to accurately capture the outline shape of an object. Several studies have used this method in archaeology and proved its effectiveness [e.g., 47 , 59 , 92 – 98 ]. Various tools and software exist to automate the extraction of the outline coordinates [ 59 , 99 – 101 ].…”

“…Several studies have used this method in archaeology and proved its effectiveness [e.g., 47 , 59 , 92 – 98 ]. Various tools and software exist to automate the extraction of the outline coordinates [ 59 , 99 – 101 ]. To our knowledge, this is a novel approach in the use of EFA.…”

Testing inter-observer error under a collaborative research framework for studying lithic shape variability

“…Shape analyses are becoming an increasingly popular methodology for examining lithic variability in the archaeological record. As such, traditional linear metrics and geometric morphometrics (GMM) are often employed to capture morphological information on stone tools (Cardillo 2010;Lycett and von Cramon-Taubadel 2015;Matzig et al 2021). Combining morphological data from multiple observers is frequently necessary in studies of lithic assemblages, to increase sample size and/or to perform inter-site/inter-assemblage analyses, yet this can be problematic due to the possibility of introducing inter-observer error into the data (Lyman and VanPool 2009).…”

Testing inter-observer error under a collaborative research framework for studying lithic shape variability

“…Shape analyses are becoming an increasingly popular methodology for examining lithic variability in the archaeological record. As such, traditional linear metrics and geometric morphometrics (GMM) are often employed to capture morphological information on stone tools (Cardillo 2010; Lycett and von Cramon-Taubadel 2015; Matzig et al 2021). Combining morphological data from multiple observers is frequently necessary in studies of lithic assemblages, to increase sample size and/or to perform inter-site / inter-assemblage analyses, yet this can be problematic due to the possibility of introducing inter-observer error into the data (Lyman and VanPool 2009).…”