Point Pattern Analysis (PPA) as a tool for reproducible archaeological site distribution analyses and location processes in early iron age south-west Germany

PLoS One. 2024 Mar 13;19(3):e0297931. doi: 10.1371/journal.pone.0297931. eCollection 2024.

Abstract

Point Pattern Analysis (PPA) has gained momentum in archaeological research, particularly in site distribution pattern recognition compared to supra-regional environmental variables. While PPA is now a statistically well-established method, most of the data necessary for the analyses are not freely accessible, complicating reproducibility and transparency. In this article, we present a fully reproducible methodical framework to PPA using an open access database of archaeological sites located in south-west Germany and open source explanatory covariates to understand site location processes and patterning. The workflow and research question are tailored to a regional case study, but the code underlying the analysis is provided as an R Markdown file and can be adjusted and manipulated to fit any archaeological database across the globe. The Early Iron Age north of the Alps and particularly in south-west Germany is marked by numerous social and cultural changes that reflect the use and inhabitation of the landscape. In this work we show that the use of quantitative methods in the study of site distribution processes is essential for a more complete understanding of archaeological and environmental dynamics. Furthermore, the use of a completely transparent and easily adaptable approach can fuel the understanding of large-scale site location preferences and catchment compositions in archaeological, geographical and ecological research.

MeSH terms

  • Archaeology*
  • Germany
  • Reproducibility of Results

Grants and funding

GB, LS and ON research is supported by the CRC1266 “Scales of Transformations” and the German research Foundation (DFG) under grant number 2901391021-SFB 1266. MK research is supported by the Quaternary Geology, Department of Environmental Sciences of the University of Basel, the Environmental Systems Analysis, Department of Geography of the University of Cambridge and received a grant from the European Union and the Masaryk University at Brno under grant number: CZ.02.2.69/0.0/0./18_053/0016952; Postdoc2MUNIm order number 21 0053, which supported this paper in the initial state. EO research is supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 896044. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.