Assessment of interannual variability of benthic macroinvertebrate assemblages in the Athabasca River

Abstract

Interannual variability refers to the year-to-year changes in ecological conditions, which can alter niche availability and influence aquatic biota. Benthic macroinvertebrate (BMI) assemblages in riverine ecosystems have been shown to exhibit interannual variability in response to yearly variations in environmental conditions, in particular, large-scale fluctuations involving climate and hydrology. However, knowledge of interannual variation among BMI assemblages in cold region rivers is limited, highlighting the need to better understand year-to-year changes in BMI assemblages and how these changes are associated with environmental variability. To reduce this knowledge gap, this study quantified interannual changes in BMI assemblages and identified potential associations between hydroclimatic variables and assemblage composition along a cold region river. Benthic macroinvertebrates were collected annually over a range of 6 – 11 years from three reference locations on the mainstem of the Athabasca River, Alberta, Canada. Interannual variability of BMI assemblages was quantified by measuring change in assemblage abundance and taxonomic turnover, along with calculating change values in biological metrics between consecutive years. BMI interannual variability was then related to hydroclimatic variables (climate oscillations, temperature, and discharge) to determine potential environmental drivers. Results showed that interannual variability of BMI assemblages along the Athabasca River was similar to other studies conducted in cold region streams, and that four taxonomic groups (i.e., Chironomidae, Ephemeroptera, Plecoptera, and Trichoptera) were predominately responsible for yearly changes at all locations. The trajectory of interannual variability and the strength of environmental associations were inconsistent between locations. These results suggest that larger datasets are more likely to provide more reliable quantification of natural variability of BMI assemblages, and other unmeasured factors may influence interannual variability, thus confounding relationships with large-scale environmental drivers. Future studies should consider local-scale variability and finer-resolution environmental predictors to improve our understanding of the drivers of interannual variability.