Using genus-level taxonomy and traits for efficient ecological assessments of diatom condition.
Citation:
Riato, L., R. Hill, A. Herlihy, Dave Peck, Phil Kaufmann, J. Stoddard, AND Steve Paulsen. Using genus-level taxonomy and traits for efficient ecological assessments of diatom condition. Society for Freshwater Science (SFS), Philadelphia, PA, June 02 - 06, 2024.
Impact/Purpose:
For large-scale and long-term assessment programs that require multiple taxonomic laboratories to process samples, such as the United StatesEnvironmental Protection Agency's (U.S. EPA's) National Rivers and Streams Assessment (NRSA), discrepancies in species-level identification or nomenclature can preclude the use of diatom data in regional and national assessments. To address this problem, ORISE post-doctoral associate Luisa Riato, and Ryan Hill, Alan Herlihy, David Peck, Philip Kaufmann, John Stoddard and Steven Paulsen of EPA-ORD-PESD, developed diatom multimetric indices (MMIs) using genus-level diatom taxonomy and trait-based autecological information, effectively circumventing the problem of taxonomic inconsistencies in the National River and Stream Assessment diatom datasets from 2008-2009 and 2013-2014. The MMIs are designed to assess river and stream ecological condition in three large ecoregions 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, and can eliminate discrepancies in species-level identification or nomenclature that can reduce confidence and defensibility of the datasets. The authors applied their trait-based MMI to NRSA data collected within three large ecoregions within the U.S. - the East, Plains and West. The MMI for the East had the greatest ability to discriminate reference from disturbed sites, followed by MMIs for the Plains and West, respectively. MMI performance was comparable to that observed in existing NRSA fish and macroinvertebrate MMIs. The authors also demonstrate that trait-based MMI's can be effective for large-scale assessments, and may allow programs such as NRSA toassess historical trends in freshwater condition by revisiting older diatom datasets, where inconsistencies in species-level identification, and recent advances in standardization of identification may have rendered historical datasets unreliable and inconsistent with current standards. The approach developed in this study requires less labor, and could allow the inclusion of diatoms in state or regional programs with limited time and financial resources .
Description:
Develop genus level, trait based multimetric diatom index (MMI) to assess ecological condition of rivers/streams across U.S. Compliment NRSA Macroinvertebrate/Fish MMIs.