PREDICTION OF THE SHANNON WIENER DIVERSITY INDEX FROM TRACE-ELEMENT PROFILES IN SEDIMENTS AROUND THE STATFJORD PLATFORMS

A strategy for building multivariate models capable of predicting chan ges in community structure from environmental data is presented This i ncludes five important elements in the process of model building and v alidation concerned with pollution surveys; i) quality control of chem ical replicates, ii) data exploration with the purpose of detecting di fferent distribution profiles of pollutants, iii) transformation to ac hieve constant variance of the environmental data in order to improve the models' predictive ability, iv) validation of the models in time a nd space, and, v) multivariate testing for outliers among new samples prior to prediction by the model. This methodology is applied to the s ediments around the three Statfjord fields in the North Sea, Three ind ependent models based on the trace element concentrations of selected training samples, explain in average 86% of the variation of the Shann on Wiener diversity index. Accurate predictions of the diversity index were achieved on test samples beyond distances included in the traini ng set, and on samples collected two years later. High concentrations of selected trace elements, in particular Cu, correlate strongly with low diversity.