1. Early versions of the river invertebrate prediction and classification system (RIVPACS) used TWINSPAN to classify reference sites based on the macro-invertebrate fauna, followed by multiple discriminant analysis (MDA) for prediction of the fauna to be expected at new sites from environmental variables. This paper examines some alternative methods for the initial site classification and a different technique for prediction.
2. A data set of 410 sites from RIVPACS II was used for initial screening of seventeen alternative methods of site classification. Multiple discriminant analysis was used to predict classification group from environmental variables.
3. Five of the classification–prediction systems which showed promise were developed further to facilitate prediction of taxa at species and at Biological Monitoring Working Party (BMWP) family level.
4. The predictive capability of these new systems, plus RIVPACS II, was tested on an independent data set of 101 sites from locations throughout Great Britain.
5. Differences between the methods were often marginal but two gave the most consistently reliable outputs: the original TWINSPAN method, and the ordination method semi-strong hybrid multidimensional scaling (SSH) followed by K-means clustering.
6. Logistic regression, an alternative approach to prediction which does not require the prior development of a classification system, was also examined. Although its performance fell within the range offered by the other five systems tested, it conveyed no advantages over them.
7. This study demonstrated that several different multivariate methods were suitable for developing a reliable system for predicting expected probability of occurrence of taxa. This is because the prediction system involves a weighted average smoothing across site groupings.
8. Hence, the two most promising procedures for site classification, coupled to MDA, were both used in the exploratory analyses for RIVPACS III development, which utilized over 600 reference sites.