Compositional data analysis of regional geochemical data in the Lhasa area of Tibet, China. (December 2021)

• Record Type: Journal Article
• Authors: Wang, Lu; Liu, Bingli; McKinley, Jennifer M.; Cooper, Mark R.; Li, Cheng; Kong, Yunhui; Shan, Mingxia
• Is Part Of: Applied geochemistry. Volume 135(2021)
• Publication Date: 2021-12
• Subjects: Compositional data analysis -- Log-ratio -- SBP -- Compositional balance -- Biplot -- Lhasa; Environmental geochemistry -- Periodicals; Water chemistry -- Periodicals; Geochemistry -- Social aspects -- Periodicals; Geochemistry -- Periodicals; 551.9
• DOI: 10.1016/j.apgeochem.2021.105108
• Languages: English
• ISSNs: 0883-2927

Abstract

Abstract: It is now widely recognized that geochemical survey data are compositional in nature, with each component having relative importance as part of a whole. Compositional data analysis (CoDA) based on log-ratio transformations can be used to deal with the 'sum to one' data constraint. This study explored the use of two data-driven CoDA approaches, centered log-ratio (clr)-biplot analysis and a compositional-balance approach, to investigate associations between elements for potential mineral exploration in the Lhasa area of Tibet, China. Results revealed that (1) the compositional-balance approach, based on a hierarchical cluster and sequential binary partition (SBP) technique, well reflects the range of rocks and metal deposits in the area; (2) the clr-biplot indicates associated relationships between elements, and a consistency is found between principal component (PC1 and PC2) and key compositional balances (Balance 1 and 4); and (3) comparison with traditional integrated geochemical mapping, a knowledge-driven method, proves the validity of the compositional-balance and clr-biplot methods. These results provided metallogenic and petrogenetic information and crucial evidence supporting further geological and geochemical exploration. The improved knowledge demonstrates the importance of using a CoDA approach for geochemical data before performing further statistical analysis. Highlights: Compositional balances reflects the range of rocks and metal deposits. The clr-biplot indicates the consistency between PCs and compositional balances. Comparison with traditional approach supports the validity of CoDA approaches.