A method for environmental monitoring using benthic species profiles as input is developed in this work. The method, referred to as projective 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 between 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 community 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 surveys to define the permissible variation in species communities, i.e. the limit of the natural variation. In addition, the method is dynamic, in a sense that the sampling locations may vary from survey to survey. Furthermore, our analysis shows that the customary number of replicate samples per station can be reduced. Modelling with only four randomly chosen replicates out of the complete set of five for each sampling location, does not affect the model significantly. On the other hand, taking only 3 replicates into account leads to significant divergences. A model based on the 1990 and 1993 surveys at the Statfjord field is presented as an example of the technique.