The potential of chironomid larvae-based metrics in the bioassessment of non-wadeable rivers

Abstract

The chironomid community in non-wadeable lotic systems was tested as a source of information in the construction of biological metrics which could be used into the bioassessment protocols of large rivers. In order to achieve this, we simultaneously patterned the chironomid community structure and environmental factors along the catchment of the Danube and Sava River. The Self organizing map (SOM) recognized and visualized three different structural types of chironomid community for different environmental properties, described by means of 7 significant abiotic factors (a multi-stressor gradient). Indicator species analysis revealed that the chironomid taxa most responsible for structural changes significantly varied in their abundance and frequency along the established environmental gradients. Out of 40 biological metrics based on the chironomid community, the multilayer perceptron (MLP), an supervised type of artificial neural network, derived 5 models in which the abundance of Paratrichocladius rufiventis, Orthocladiinae, Cricotopus spp., Cricotopus triannulatus agg. and Cricotopus/Orthocladius ratio achieved a significant relationship (the r Pearson's linear correlation coefficient>0.7) with the multi stressor environment. The sensitivity analysis "partial derivatives" (PaD) method showed that all 5 biological metrics within the multi-stressor gradient were mostly influenced by dissolved organic carbon (DOC). Despite short and monotonous environmental gradients and the absence of reference conditions, the chironomid community structure and biological metrics predictably changed along the multistress range, showing a great potential for the bioassessment of large rivers.

Keywords: Artificial neural network; Bioassessment; Biological metric; Chironomidae; Large rivers.