Benthic diatom assemblages are known to be indicative of water quality but have yet to be widely adopted in biological assessments in the United States due to several limitations. Our goal was to address some of these limitations by developing regional multi-metric indices (MMIs) that are robust to inter-laboratory taxonomic inconsistency, adjusted for natural covariates, and sensitive to a wide range of anthropogenic stressors. We aggregated bioassessment data from two national-scale federal programs and used a data-driven analysis in which all-possible combinations of 2-7 metrics were compared for three measures of performance. After ranking the best-performing MMIs, we selected the final MMIs by evaluating stress-response relations in independent regional datasets of diatom samples paired with measures of several water-quality stressors, including herbicides and streamflow flashiness. Each regional MMI performed well at calibration sites and represented diverse aspects of the structure and function of diatom communities. Most metrics included in the best MMIs were modeled to account for natural variation including climate, topography, soil characteristics, lithology, and groundwater influence on streamflow. MMI performance improved with higher numbers of component metrics, but this effect diminished beyond six metrics. Component metrics of MMIs were associated with a broad suite of measured stressors in every region, including salinity, nutrients, herbicides, and streamflow flashiness. We provide a web based software application that allows users in the conterminous United States to apply our MMIs to their own datasets and compare MMI scores from their sites to a broader regional context.

Inconsistency in taxonomic identification and analyst bias impede the effective use of diatom data in regional and national stream and lake surveys. In this study, we evaluated the effect of existing protocols and a revised protocol on the precision of diatom species counts. The revised protocol adjusts four elements of sample preparation, taxon identification and enumeration, and quality control (QC). We used six independent data sets to assess the effect of the adjustments on analytical outcomes. The first data set was produced by three laboratories with a total of five analysts following established protocols (Charles et al., Protocols for the analysis of algal samples collected as part of the U.S. Geological Survey National Water‐Quality Assessment, 2002) or their slight variations. The remaining data sets were produced by one to three laboratories with a total of two to three analysts following a revised protocol. The revised protocol included the following modifications: (1) development of coordinated precount voucher floras based on morphological operational taxonomic units, (2) random assignment of samples to analysts, (3) postcount identification and documentation of taxa (as opposed to an approach in which analysts assign names while they enumerate), and (4) increased use of QC samples. The revised protocol reduced taxonomic bias, as measured by reduction in analyst signal, and improved similarity among QC samples. Reduced taxonomic bias improves the performance of biological assessments, facilitates transparency across studies, and refines estimates of diatom species distributions.

Current fixed-count enumeration methods for benthic diatoms are likely inadequate for most research and monitoring objectives. These methods underestimate taxa richness and may fail to detect losses of species caused by human impacts. Consequently, the full potential of diatoms is not realized in current assessments of biological integrity or species diversity. In this study, we hypothesize that alternative enumeration methods differ in their ability to quantify species composition. Furthermore, we hypothesize that an alternative to the traditional fixed-count method will improve both performance of observed/expected (O/E) indices derived from River Invertebrate Prediction and Classification System models and the discrimination of reference-quality and human-modified sites by other standard metrics used in biological assessments. To test these hypotheses, we assessed 1) how well 3 counting methods characterized species richness in a subset of 15 samples of stream benthic diatoms and 2) how counting method affected the performance of O/E indices and metrics by comparing the traditional fixed-count method against the best-performing alternative method. These latter comparisons were based on samples collected from 68 reference-quality streams and 20 streams located along an urban disturbance gradient. We demonstrate that traditional fixed counts failed to detect >½ of species present in most of the 68 reference-quality sites. Instead, timed-presence data produced the O/E index with the best performance and a level of precision similar to published invertebrate O/E indices. Furthermore, the O/E index based on the timed-presence data allowed us to determine which species are most often lost with urbanization. We found that traditional fixed-count and alternative timed-presence data produce metrics that are nearly equally able to discriminate between reference and disturbed sites. This study demonstrates that alternative counting methods improve species detection and require up to ∼30% less effort.

This flora is intended to serve as an image voucher for samples analyzed for the U.S. Geological Survey Southeast Stream Quality Assessment (SESQA). The SESQA study included measurement of watershed and water quality parameters to determine the factors that have the greatest potential to alter biotic condition. Algal samples were collected at 108 sites in 2014, from streams representing gradients in chemical and physical alteration across the southeast region. More than 375 taxa were identified during analysis for species composition and abundance. This manuscript documents the flora with light micrographs of specimens representative of their morphologic range. We define "voucher flora" as images of specimens and the names applied to those specimens for a given project. Taxonomic vouchers from federal programs have generally not been made public, yet they are a salient element of a well-documented species dataset, particularly for long-term studies. This study is part of a broader effort to improve and encourage taxonomic consistency in federal, state and local programs by accessible identification resources and inter-lab comparisons.