Data transformation and standardization in the multivariate analysis of river water quality

Multivariate approaches are being increasingly applied to aquatic studies; however, their ecological relevance has not been adequately addressed. This paper examines the effects of data transformation and standardization on p rincipal-components analysis (PCA) of river water quality. Two currently po pular methods, log(x + 1) and standardizing to 0 mean and I variance, were evaluated. The choice of the data-handling methods substantially affected t he analytic output. However, both methods tested were found to be flawed, w ith the major problem being disregard for the biological/ecotoxicological s ignificance of water-quality variables and their ranges. We developed a new standardization model, which incorporates water quality standards into dat a standardization. This provides a mechanism to improve the biological rele vance of multivariate analysis. The new model-based PCA yields an assessmen t of water quality that is more ecologically meaningful than any others tes ted. We discuss the ecological implications of the new model and of the est ablished methods tested.