PROJECTIVE ORDINATION BY SIMCA - A DYNAMIC STRATEGY FOR COST-EFFICIENT ENVIRONMENTAL MONITORING AROUND OFFSHORE INSTALLATIONS

A method for environmental monitoring using benthic species profiles a s input is developed in this work. The method, referred to as projecti ve ordination, utilises local principal component modelling (SIMCA) to obtain a cross-validated model which spans the natural variation in a region around offshore oil-producing installations. The borderline be tween regions with disturbed and non-disturbed species communities is subsequently decided from the residual distribution. This distribution is used to design an approximate F-test for assessing whether a commu nity at a particular sampling location is disturbed or not. If so, the nature of the disturbance is determined by projecting the data on the PC model. Projective ordination utilises information from previous su rveys to define the permissible variation in species communities, i.e. the limit of the natural variation. In addition, the method is dynami c, in a sense that the sampling locations may vary from survey to surv ey. Furthermore, our analysis shows that the customary number of repli cate samples per station can be reduced. Modelling sith only four rand omly chosen replicates out of the complete set of five for each sampli ng location, does not affect the model significantly. On the other han d, taking only 3 replicates into account leads to significant divergen ces. A model based on the 1990 and 1993 surveys at the Statfjord field is presented as an example of the technique.