Quartzite complexities: Non-destructive analysis of bifacial points from Vasterbotten, Sweden

Northern Fennoscandia is a geologically complex region affected by both glacial and postglacial processes. Quartzite was a key material type utilized by hunter-gatherers in Northern Sweden around the period 4 000 - 2 000 BP, and is thus critical to the understanding of raw material procurement and m...

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Bibliographic Details
Main Author: Geladi, Paul
Format: Article in Journal/Newspaper
Language:Swedish
English
Published: 2024
Subjects:
Online Access:https://pub.epsilon.slu.se/33176/
https://pub.epsilon.slu.se/33176/1/sjolander-m-et-al-20240318.pdf
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Summary:Northern Fennoscandia is a geologically complex region affected by both glacial and postglacial processes. Quartzite was a key material type utilized by hunter-gatherers in Northern Sweden around the period 4 000 - 2 000 BP, and is thus critical to the understanding of raw material procurement and material flow within the region. However, there is a severe lack of methodological development in the characterization of these materials, and provenance of locally available geological material is complex and fraught with uncertainty. 126 quartz/ quartzite points and preforms were sampled from 47 archaeological sites along the upper angstrom ngerman river valley in Va center dot sterbotten, Sweden. The material has been analysed non-destructively using three separate portable spectroscopic instrumentations (Near-infrared, Raman, X -Ray Fluorescence). Evaluation of the spectra and exploratory data analysis using Principal Component Analysis demonstrates detectable differences in the material that likely stem from diagenetic/paragenetic origin. The presence of graphite, muscovite and biotite could likewise provide information on the material's metamorphic grade. In addition to reaffirming the potential of field -based screening instrumentation, these results will benefit future surveys of geological sources in the region. They also indicate potential for the construction of a predictive model that could classify the quartzite based on its chemical characteristic. Such a model would prove useful in future spatial analysis and testing of models of raw material management.