Assessing anthropogenic pressure in the St. Lawrence River using traits of benthic macroinvertebrates.

This study aims to evaluate the anthropogenic pressure in the St. Lawrence River by assessing the relationships between chemical contamination of sediments and benthic community structure with the trait-based approach. Organic and inorganic contaminants as well as other sediment variables (sediment grain size, total organic carbon, nutrients, etc.) and benthic invertebrate assemblages were determined in 59 sites along the river. Biological and ecological traits of taxa were coded, taking into account regional climate and ecosystem conditions. The aims of this study were to (1) describe the relationships between traits and macroinvertebrate taxa and identify homogeneous clusters of taxa with the same combinations of functional traits, (2) describe spatial patterns in traits of macroinvertebrates in the St. Lawrence River, (3) link trait-based metrics and site groups to sediment quality and (4) define a trait-based strategy for diagnosing the ecological quality of the St. Lawrence River. Seven groups of taxa sharing similar trait-category attributes were defined. Moreover, four groups of sites were identified using the 'K-mean' non-hierarchical clustering approach. The 'IndVal' method enabled us to specifically defined trait categories corresponding to site groups on the basis of their indicator value. The relative abundances of taxa from five functional groups significantly varied among site groups. For example, some indicator traits such as multivoltine cycle, long life span, fixed clutches, tegumental respiration, asexual reproduction, and collector/gatherer feeding habit were associated to the most heavily polluted sites located in the Montreal harbour which showed the highest sediment concentrations in Pb, Zn and Cu. Three trait-based pressure-specific models were built, based on the random forest approach, for respectively (1) heavy metals, (2) BPCs and PAHs, and (3) TBTs occurring in the environment. These models could be applied to assess sediment quality using macroinvertebrate assemblages in a large Canadian river.