Heavy Metal (PTE) Ecotoxicology, Data Review: Traditional vs. a Compositional Approach

Abstract Potentially Toxic Elements (PTEs) otherwise known as heavy metals are ubiquitous in soils and can have a range of negative health and environmental impacts. In terrestrial systems understanding how PTEs move in the environment is made challenging by the complex interactions within soil and the wider environment and the compositional nature of PTEs. PTEs are compositional because data of individual PTEs within in a sample are ratios which may be under a sum constraint, where individual components sum up to a whole. In this study three different scenarios were considered, one using the centred log ratio transformation (clr) a compositional transformation, the more “traditional” log10 transformation (log10) and untransformed data acting as a comparison (unt) were applied to four different datasets. Three were the Liver, Muscle and Kidney tissue of Eurasian Badgers (Meles meles) and the fourth was soil and data were extracted from a regional geospatial survey. Cluster analysis demonstrated that the clr and log10 transformation were able to resolve compositional trends at the point of the individual sample, whilst unt could not and did not meet the preconditions for the next phase of analysis. At the level of compositional trends between PTEs complex heatmaps demonstrated that clr was able to isolate PTE relationships and highlight commonalities between different datasets, whilst log10 could not. In the final phase, principal component analysis (PCA) of the clr transformation showed similarities between the signals in the soft tissues and the disparities they had with soil, whilst the log10 transformation was unable to achieve this. Overall, the clr transformation was shown to perform more consistently under a variety of analytical scenarios and the compositional approach will provide more realistic interpretations about PTEs in both soil and animal soft tissue than the log10 or unt conditions.