Multiple Discriminant Analysis of Marine Sediment Data

A multivariate statistical approach was used in the analysis of inter-relationships among marine benthic infaunal structure, physical and chemical characteristics of sediment samples and toxicity data derived from laboratory tests at 16 locations in shallow, inshore waters of Hong Kong. The method involved classification (cluster analysis using the Bray–Curtis similarity index) and ordination (multi-dimensional scaling) of infaunal patterns and the use of multiple discriminant analysis to relate groupings of the locations to the selected environmental and toxicity data. Analysis of the combined sediment physical, biological, chemical and toxicity dataset by stepwise multiple discriminant analysis allowed identification of those variables most sensitive for discriminating location groups. The use of multiple discriminant analysis in sediment quality characterization was evaluated against the Sediment Quality Triad approach and other statistical techniques.