Matzig DN, Marwick B, Riede F, Warnock R (2024)
Publication Type: Journal article
Publication year: 2024
Book Volume: 11
Article Number: 240321
Journal Issue: 8
DOI: 10.1098/rsos.240321
Phylogenetic models are commonly used in palaeobiology to study the patterns and processes of organismal evolution. In the human sciences, phylogenetic methods have been deployed for reconstructing ancestor–descendant relationships using linguistic and material culture data. Within evolutionary archaeology specifically, phylogenetic analyses based on maximum parsimony and discrete traits dominate, which sets limitations for the downstream role cultural phylogenies, once derived, can play in more elaborate analytical pipelines. Recent methodological advances in Bayesian phylogenetics, however, now allow us to infer evolutionary dynamics using continuous characters. Capitalizing on these developments, we here present an exploratory analysis of cultural macroevolution of projectile point shape evolution in the European Final Palaeolithic and earliest Mesolithic (approx. 15 000–11 000 BP) using a Bayesian phylodynamic approach and the fossilized birth–death process model. This model-based approach leaps far beyond the application of parsimony, in that it not only produces a tree, but also divergence times, and diversification rates while incorporating uncertainties. This allows us to compare rates to the pronounced climatic changes that occurred during our time frame. While common in cultural evolutionary analyses of language, the extension of Bayesian phylodynamic models to archaeology arguably represents a major methodological breakthrough.
APA:
Matzig, D.N., Marwick, B., Riede, F., & Warnock, R. (2024). A macroevolutionary analysis of European Late Upper Palaeolithic stone tool shape using a Bayesian phylodynamic framework. Royal Society Open Science, 11(8). https://doi.org/10.1098/rsos.240321
MLA:
Matzig, David N., et al. "A macroevolutionary analysis of European Late Upper Palaeolithic stone tool shape using a Bayesian phylodynamic framework." Royal Society Open Science 11.8 (2024).
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