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.
Geometric morphometric methods (GMM) in archaeology are experiencing a sharp increase in application and popularity since the last decade or so and seem to be more popular now than ever. In general, they constitute a major advance vis-à-vis earlier qualitative descriptions, typological assessment, or linear measurements of artefacts. GMM approaches can be divided into methods that use landmarks, and those that use trigonometric descriptions of whole outlines. The bulk of archaeological applications of GMM have so far relied on landmark-based approaches, although a surge of recent studies is demonstrating the utility of whole-outline approaches using so-called elliptical Fourier analysis and cognate approaches. There currently exist various standalone software applications as well as some R-packages for the extraction and analysis of landmarks and whole-outlines. However, the extraction step always involves a considerable amount of manual processing and manual tracking of either the landmarks or whole-outlines, which proves to be the definite bottleneck of many studies. In this protocoll I introduce the R-package outlineR (Matzig 2021) that allows a fast and efficient extraction of whole-outlines from multiple artefacts on images, as well as all necessary preparatory steps that lead up to it. References Barthelme et al. 2020: Barthelme, S., Tschumperle, D., Wijffels, J., Assemlal, H. E., & Ochi, S. (2020). imager: Image Processing Library Based on “CImg” (0.42.3) [Computer software]. https://CRAN.R-project.org/package=imager Bonhomme et al. 2014: Bonhomme, V., Picq, S., Gaucherel, C., & Claude, J. (2014). Momocs: Outline Analysis Using R. Journal of Statistical Software, 56(13). https://doi.org/10.18637/jss.v056.i13 Matzig 2021: outlineR: An R package to derive outline shapes from (multiple) artefacts on JPEG images. Zenodo. https://doi.org/10.5281/ZENODO.4527469 Pau et al. 2010: Pau, G., Fuchs, F., Sklyar, O., Boutros, M., & Huber, W. (2010). EBImage—An R package for image processing with applications to cellular phenotypes. Bioinformatics, 26(7), 979–981. https://doi.org/10.1093/bioinformatics/btq046
Benchmarking methods and data for the whole-outline geometric morphometric analysis of lithic tools | INTRODUCTIONOriginally developed for the quantitative analysis of organismal shapes, both two-dimensional (2D) and 3D geometric morphometric methods (GMMs) have recently gained some prominence in archaeology for the analysis of stone tools 1-3 -unquestionably the primary deep-time data source for the earliest periods of human cultural evolution. 4 The key strength of GMM rests in its ability to statistically quantify and hence qualify complex shapes, which in turn can be used to infer social interaction, 5 function, 6,7 reduction, 8 as well as to assess classification systems and cultural relatedness. [9][10][11]
Bibliometrics offers powerful means of visualising and understanding trends within research domains. We here present a first exploratory bibliometric analysis of cultural evolutionary theory and attendant methods as applied specifically within archaeology across the last four decades (1981–2021). Bibliographic coupling network analysis shows that there exists a broadly successive series of author clusters making up the core of this research domain. A broader vernacular version of cultural evolution is also commonly used in thematic or regional research traditions that fall outside of cultural evolutionary studies in the strict sense. Our bibliometric networks trace the development of evolutionary archaeology over the last four decades and while they demonstrate the centrality of computational models, they also suggest a stagnation in the application of precisely that suite of methods—phylogenetics—that is central to evolutionary archaeology’s biological counterpart palaeontology. Recent methodological innovations in palaeobiology are, however, offering new ways of integrating artefact shape data directly with phylogenetic applications. This development may usher in a renaissance in artefact phylogenetics and appropriately marco-scale applications of cultural evolutionary theory in archaeology.
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