Using Fordisc software to assign obsidian artifacts to geological sources: Proof of concept. (June 2017)

• Record Type: Journal Article
• Authors: Pilloud, Marin A.; Reaux, Derek J.; Smith, Geoffrey M.; Wiggins, Kristina M.
• Is Part Of: Journal of archaeological science. Volume 13(2017)
• Page Start: 428
• Page End: 434
• Publication Date: 2017-06
• Subjects: Multivariate statistics -- Great Basin -- Provenance studies -- X-ray fluorescence; Archaeology -- Periodicals; Archaeology -- Research -- Periodicals; 930.1
• DOI: 10.1016/j.jasrep.2017.04.023
• Languages: English
• ISSNs: 2352-409X

Abstract

Abstract: In recent years, source provenance studies employing portable X-ray fluorescence (pXRF) technology have become commonplace in archaeology; however, they are not without critiques. Concerns center on the capability of instruments to produce valid results and researchers' abilities to accurately interpret those results and make correct source assignments. In this paper, we focus on the latter issue with a look towards statistical means of assigning artifacts to obsidian types using data provided by pXRF spectrometers. Using a sample of 677 obsidian artifacts from the northwestern Great Basin, we evaluate the ability of various approaches (principal components, cluster, and discriminant function analyses) to correctly assign artifacts to particular obsidian types. These multivariate methods generally work well to separate artifacts into different groups (i.e., obsidian types); however, they are less well-suited to assign individual artifacts to an obsidian source or type. We therefore tested the ability of the statistical program Fordisc, commonly used in forensic anthropology, to assign individual artifacts to specific geochemical obsidian sources or types. Our results indicate that Fordisc made accurate source assignments. Furthermore, because Fordisc provides probability values for different possible matches, it offers an advantage over other methods. Highlights: Statistical analyses of source provenance studies based on trace element data are discussed. A multivariate method of obsidian source assignment using the program Fordisc is tested. Source assignment is greatly improved through multivariate statistical analyses. Source provenance studies should employ multiple variables and careful analyses of statistical results.