Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Statistical analysis of major element patterns in basalts

Pearce, Julian A. 1975. Statistical analysis of major element patterns in basalts. Journal of Petrology 17 (1) , pp. 15-43. 10.1093/petrology/17.1.15

Full text not available from this repository.

Abstract

Discriminant analysis enables basalts from different tectonic settings to be identified on the basis of their complete major element patterns. By using discriminant functions it is possible to represent visually the separation of six tectonically-defined magma types in three dimensions instead of the original eight. Analysis of variance confirms that this separation is highly significant. Numerical classification is possible by applying Bayes' decision rule, using either normal distribution functions or empirical discriminant functions. Tests on known samples showed that ocean-floor basalts, low-potassium tholeiites (from island arcs), calc-alkali basalts and shoshonites (from volcanic arcs) and within-plate basalts could be correctly classified about 90 per cent of the time by all these methods. A subdivision of within plate basalts into ocean island and continental basalts could not however be achieved chemically with any great success. Classification of weathered and metamorphosed ocean-floor basalts showed that alteration can greatly reduce the success rate of the classification. Application of the numerical and visual methods to lavas of 'unknown' tectonic settings (Archaean greenstones and high-potash basalts) mostly gave geologically consistent results.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Earth and Ocean Sciences
Subjects: Q Science > QE Geology
Publisher: Oxford University Press
ISSN: 1460-2415
Last Modified: 04 Jun 2017 02:05
URI: http://orca.cf.ac.uk/id/eprint/8622

Citation Data

Cited 348 times in Google Scholar. View in Google Scholar

Cited 262 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item