Article ID Journal Published Year Pages File Type
4429472 Science of The Total Environment 2012 15 Pages PDF
Abstract

Applied geochemistry and environmental sciences invariably deal with compositional data. Classically, the original or log-transformed absolute element concentrations are studied. However, compositional data do not vary independently, and a concentration based approach to data analysis can lead to faulty conclusions. For this reason a better statistical approach was introduced in the 1980s, exclusively based on relative information. Because the difference between the two methods should be most pronounced in large-scale, and therefore highly variable, datasets, here a new dataset of agricultural soils, covering all of Europe (5.6 million km2) at an average sampling density of 1 site/2500 km2, is used to demonstrate and compare both approaches. Absolute element concentrations are certainly of interest in a variety of applications and can be provided in tabulations or concentration maps. Maps for the opened data (ratios to other elements) provide more specific additional information. For compositional data XY plots for raw or log-transformed data should only be used with care in an exploratory data analysis (EDA) sense, to detect unusual data behaviour, candidate subgroups of samples, or to compare pre-defined groups of samples. Correlation analysis and the Euclidean distance are not mathematically meaningful concepts for this data type. Element relationships have to be investigated via a stability measure of the (log-)ratios of elements. Logratios are also the key ingredient for an appropriate multivariate analysis of compositional data.

► Major element concentrations in agricultural soils of Europe are presented. ► Results of classical data analysis versus compositional data analysis are compared. ► Both approaches deliver important and complementary results. ► With compositional data XY diagrams should not be used to discuss correlation. ► Multivariate data analysis of compositional data should be based on logratio-transformed data.

Related Topics
Life Sciences Environmental Science Environmental Chemistry
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