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Genus-level, trait-based multimetric indices for diatom assessment of rivers and streams across the conterminous U.S.
Citation:
Riato, L., J. Stoddard, Phil Kaufmann, Dave Peck, Ryan A Hill, A. Herlihy, AND Steve Paulsen. Genus-level, trait-based multimetric indices for diatom assessment of rivers and streams across the conterminous U.S. To be Presented at Diatom Web Academy Seminar Series, N/A, Virtual, October 26, 2021.
Impact/Purpose:
Taxonomic inconsistency in diatom datasets can constrain use of diatoms as biological indicators in rivers and streams assessments in the United States (US). For projects like the USEPA’s National Rivers and Streams Assessment (NRSA), differences in species identification or nomenclature among multiple taxonomy laboratories can render diatom data unusable in large-scale assessments. We address this problem by developing trait-based diatom multimetric indices (MMIs) to assess river and stream condition across the conterminous US, using a separate MMI for the East, Plains, and West ecoregions. Diatom data from the 2008-2009 NRSA were used to develop candidate metrics by assigning taxa to morphological and functional traits based on genus-level attributes. Other metrics were developed from diatom genera. The final trait-based MMI for the East had the greatest precision and ability to discriminate reference from disturbed sites, followed by MMIs for the Plains and West. MMI performances were comparable with NRSA MMIs for other biological assemblages for these ecoregions. Our work shows trait-based diatom indices are effective for large-scale assessments, and because they are less labor-intensive and more immune to taxonomic inconsistencies than species-based indices, they are also more practical and reliable.
Description:
Taxonomic inconsistency in diatom datasets can constrain use of diatoms as biological indicators in aquatic assessments. This talk addresses this problem by developing genus-level, trait-based diatom multimetric indices (MMIs) 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 (USEPA’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.