Using genus-level taxonomy and traits to develop diatom multimetric indices to assess wetland condition across the conterminous United States

In large-extent assessment programs, such as the United States Environmental Protection Agency's (USEPA) National Wetland Condition Assessment (NWCA), the task of identifying diatom taxa in samples is spread out over several taxonomists and laboratories. This produces inconsistencies in the diatom data at the species-level that have proven difficult to reconcile. New approaches for using genus-level diatom data, and assigning traits to each genus, have shown promise for introducing diatoms into national assessments in rivers and streams. We developed diatom multimetric indices (MMIs) using genus-level taxonomy and trait information from the NWCA data to assess the ecological condition for 574 inland and estuarine wetland samples across the conterminous U.S. Genus-level, trait-based indices have several advantages over classic species-based indices, including less work-effort and expertise required. Using genus-level diatom data is also more reliable for bioassessment when there are data quality concerns because of taxonomic inconsistencies from using multiple analysts. Our study showed that the genus-level, trait MMIs responded well to increases in multiple stressors, and discriminated least-disturbed from most-disturbed wetland sites. Inland wetland MMIs discriminated better than the estuarine MMI. The performance of our MMIs was similar to that of other existing USEPA national aquatic monitoring MMIs, including the wetland vegetation MMI. This new indicator may allow for the use of diatoms in NWCA surveys, and our cost-effective approach may facilitate the use of diatoms in other aquatic programs with restricted resources. Moreover, our approach could be applied to older data previously set aside due to taxonomic challenges. • Genus-level, trait-based diatom indices were developed for U.S. wetlands. • Diatom indices could distinguish least- from most-disturbed sites. • Genus/trait-based indices require less labor and avoids taxonomic inconsistencies. • Genus taxonomy and traits can be used in large-extent, wetland assessments.