Algae-based Biomonitoring: Predicting Diatom Reference Communities in Unpolluted Streams using Classification Trees, Random Forests, and Artificial Neural Networks (original) (raw)

The Eastern Canadian Diatom Index (IDEC) was developed to evaluate the ecological integrity of streams along a pollution gradient, as a function of the dissimilarity between current diatom communities and suitable reference communities. Distinguishing natural variations in community structure from those induced by human activities is essential for proper assessment of dissimilarity. To account for the effect of the natural variation in pH on this assessment, two IDEC subindices were used: one for sites with diatom reference communities typical of naturally alkaline water pH, and another for sites with communities typical of naturally circumneutral water pH. This study used three statistical models, namely classification trees (CT), random forests (RF), and artificial neural networks (ANN) to: (i) identify the environmental variables discriminating between alkaline and neutral reference communities (“biotypes”), and (ii) compare their predictive capacities. Models identified clay roc...