Description: Taxonomic inconsistency in diatom datasets can constrain use of diatoms as biological indicators in aquatic assessments. This talk addresses this problem by developing diatom multimetric indices (MMIs) using genus-level taxonomy and trait-based autecological information. The MMIs are designed to assess river and stream condition across the conterminous United States. In contrast to traditional species-level approaches, trait-based approaches can use genus-level data, which is simpler and less-expensive to obtain. For large-scale assessment programs that require multiple taxonomic laboratories to process samples, such as the United States Environmental Protection Agency’s (U.S. EPA’s) National Rivers and Streams Assessment (NRSA), the trait approach can eliminate discrepancies in species-level identification or nomenclature that can render diatom data unreliable. We apply our trait-based MMI within three large ecoregions used by NRSA. We show that trait-based diatom indices constructed on genus-level taxonomy can be effective for large-scale assessments, and may allow programs such as NRSA to retrospectively assess trends in freshwater condition by revisiting older diatom datasets. While the level of taxonomic resolution required for diatom-based assessments is still under debate, our results are supported by other studies that show genus-level identification can provide a robust biotic assessment. Importantly, we do not suggest that species-based approaches should be replaced by genus-level approaches; instead our research shows that trait-based MMI’s offer a suitable alternative when reliable species-level data are not available. Future work will assess the performance of the regional-scale MMIs on state-level datasets.

Target audience: Those interested in incorporating diatoms in freshwater biological assessments, and applying genus-level taxonomy, and trait-based approaches in bioassessments.