Degree of Geochemical Similarity (DOGS): a simple statistical method to quantify and map affinity between samples from multi-element geochemical data sets. Issue 1 (2nd January 2016)

• Record Type: Journal Article
• Authors: Mann, A.; de Caritat, P.; Sylvester, G.
• Is Part Of: Australian journal of earth sciences. Volume 63:Issue 1(2016)
• Page Start: 111
• Page End: 122
• Publication Date: 2016-01-02
• Subjects: Geochemical signature -- linear regression analysis -- geochemical similarity -- Mobile Metal Ion analysis -- National Geochemical Survey of Australia; Earth sciences -- Australia -- Periodicals; Earth sciences -- Periodicals; Geology -- Australia -- Periodicals; Geology -- Periodicals; 559.405
• DOI: 10.1080/08120099.2016.1130744
• Languages: English
• ISSNs: 0812-0099

Abstract

ABSTRACT: The 42 element, 1190 sample Mobile Metal Ion subset of the National Geochemical Survey of Australia database was used to develop and illustrate the concept of Degree of Geochemical Similarity of soil samples. Element concentrations were unified to parts per million units and log(10)-transformed. The degree of similarity of pairs of samples of known provenance in the Yilgarn Craton was obtained using least-squares linear regression analysis and demonstrated that the method successfully assessed the degree of similarity of soils related to granitoid and greenstone lithologies. Exploratory Data Analysis symbol maps of all remaining samples in the database against various reference samples were used to obtain correlation maps not only for granitoid- and greenstone-related soil types but also to distinguish between, for example, samples derived from marine vs regolith carbonate. Likewise, the distribution of soil samples having a geochemical fingerprint similar to mineralised provinces (e.g. Mount Isa) can be mapped, and this can be used as a first-order prospection tool.