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SFS Annual Meeting

Tuesday, June 4, 2024
10:30 - 12:00

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S08 Algal taxonomic Data: Embracing New Protocols and Analyses

10:30 - 10:45 | Salon 5/6 | USING COLLECTIONS AND DATA GENERATED BY LARGE-SCALE ENVIRONMENTAL SURVEYS TO ADVANCE DIATOM TAXONOMY, ECOLOGY, AND IMPROVING CONSISTENCY OF IDENTIFICATION.

6/04/2024  |   10:30 - 10:45   |  Salon 5/6

Using collections and data generated by large-scale environmental surveys to advance diatom taxonomy, ecology, and improving consistency of identification. Traditionally, morphological diversity of diatoms has been captured in printed floras focused on specific geographic areas and habitats. These publications have been instrumental for promoting the use of diatoms as environmental indicators and crucial as a starting point for research in diatom systematics. Commonly cited limitations of historic floras are the insufficient representation of morphological variation within taxa impeding interpretation of species boundaries and incomplete or biased taxonomic coverage. Both limitations could be overcome by adopting the” voucher flora” approach, which in conjunction with dense geographic sampling is an objective way of representing diatom diversity of a geographic area of interest. Federal and state-level aquatic surveys are exceptional sources of data and specimens for objectively capturing morphological diversity of diatoms in a systematic way and for inferring their ecological characteristics. Surveys with comprehensive spatial coverage provide unique opportunities for in-depth taxonomic revisions of ecologically important diatoms. Using our current studies of the diatom genus Pinnularia in the Eastern US as an example, we show how the EPA National Lake Assessment projects data and collections were instrumental for revealing the morphological diversity within several groups of Pinnularia species previously either lumped together or confused with each other or misidentified. A voucher flora constructed for a notoriously difficult group of Pinnularia subgibba-like species led to its taxonomic revision including the discovery of several new species. Most importantly, these studies revealed considerable differences in ecology of morphologically similar Pinnularia species with consequences for their use as environmental indicators.

Laura Aycock (Primary Presenter/Author), Academy of Natural Sciences of Drexel University, lla32@drexel.edu;

Marina Potapova (Co-Presenter/Co-Author), Academy of Natural Sciences of Drexel University, mp895@drexel.edu;

10:45 - 11:00 | Salon 5/6 | BUILDING PENNSYLVANIA'S DIATOM VOUCHER FLORA

6/04/2024  |   10:45 - 11:00   |  Salon 5/6

BUILDING PENNSYLVANIA'S DIATOM VOUCHER FLORA Diatoms are known to be good bioindicators, but effectively using them in water quality monitoring requires consistent and reliable identification. Ever-changing nomenclatural treatments, lack of accessible and comprehensive literature, and high species diversity and endemism burden even the most accomplished taxonomists. Large, long-term studies especially suffer from so-called ‘analyst bias’. Post-hoc data harmonization, while effective, is labor intensive and reduces taxonomic resolution. Aiming to improve water quality monitoring outcomes, The Pennsylvania Department of Environmental Protection is developing a diatom voucher flora to document taxa richness and diversity across the state. EnviroScience, Inc., in partnership with the Academy of Natural Sciences of Drexel University (ANS), is building an extensive photo reference library of specimens collected over the last decade. From these images, morphological operational taxonomic units (mOTUs) will be assigned and arranged in a publicly available reference guide, with permanent microscope slides deposited in the ANS Diatom Herbarium. This voucher flora will provide analysts with a coordinated, living document and the potential to improve bioassessment performance.

Alison Frohn (Primary Presenter/Author), EnviroScience, Inc., afrohn@enviroscienceinc.com;

Brad Bartelme (Co-Presenter/Co-Author), EnviroScience, Inc., bbartelme@enviroscienceinc.com;

Melissa Vaccarino (Co-Presenter/Co-Author), EnviroScience, Inc., mvaccarino@enviroscienceinc.com;

Kyle Scotese (Co-Presenter/Co-Author), EnviroScience, Inc., kscotese@enviroscienceinc.com;

Jeffery Butt (Co-Presenter/Co-Author), Pennsylvania Department of Environmental Protection, jbutt@pa.gov;

Will Brown (Co-Presenter/Co-Author), Pennsylvania Department of Environmental Protection, willbrown@pa.gov;

Mariena Hurley (Co-Presenter/Co-Author), Academy of Natural Sciences of Drexel University, mkh96@drexel.edu;

11:00 - 11:15 | Salon 5/6 | USING AN IMAGE VOUCHER APPROACH FOR TAXONOMIC CONSISTENCY AND NOMENCLATURAL ACCURACY IN A LARGE-SCALE, LONG-TERM DATASET. NEXT STEPS.

6/04/2024  |   11:00 - 11:15   |  Salon 5/6

Using an image voucher approach for taxonomic consistency and nomenclatural accuracy in a large-scale, long-term dataset. Next Steps. Difficulty in morphological species identification, evolving and varying taxon concepts, and morphological references based on non-regional specimens can lead to significant inconsistencies in taxonomic datasets across analysts and through time. This is particularly true for diatom taxonomy and even highly trained taxonomists can contribute to analyst bias. For the 2018/19 U.S. Environmental Protection Agency National Rivers and Streams Assessment (NRSA) diatom analysis, involving over 1,900 samples from across the contiguous U.S., we used an image voucher approach. Pre-analysis, images were taken of specimens from 80% of the diatom samples, sorted into likely morphological species, assigned operational taxonomic units (OTUs), and organized into genus groups to create searchable taxonomic vouchers. These vouchers were used as the sole taxonomic reference for NRSA data collection. This large-scale effort produced nine diatom reference vouchers based on the nine aggregate NRSA ecoregions as well as a “living” taxonomy table that tracks all taxonomic changes through time and is traceable back to the original OTU image sets. As the 2023/24 data collection commences, we are considering how best to make this voucher set and the supporting taxonomy table a useful, publicly available tool for other North American-based projects.

Julianne Heinlein (Primary Presenter/Author), Great Lakes Environmental Center, jheinlein@glec.com;

11:15 - 11:30 | Salon 5/6 | UNCERTAINTY-FREQUENCY CLASSES FOR FRESHWATER BENTHIC MACROINVERTEBRATE TAXONOMIC IDENTIFICATIONS

6/04/2024  |   11:15 - 11:30   |  Salon 5/6

Uncertainty-Frequency Classes for Freshwater Benthic Macroinvertebrate Taxonomic Identifications Biological nomenclature provides direct access to information associated with living entities, and the risks of error in taxonomic identifications vary based on intended uses of the data. We designed and executed sample-based quality control analysis of benthic macroinvertebrate taxonomic identifications for 10 moderate to large freshwater biological monitoring programs, performing inter-laboratory comparisons on >900 samples taken from rivers, streams, and lakes across the U.S., including the Great Lakes. This approach for secondary use of QC results for developing taxonomic uncertainty ratings is suggested as a model for similar analyses of diatoms, or other organism groups. Samples used by each of the programs for QC analyses were randomly selected from the full sample load of the program, typically at a rate of approximately 10%, thus results reported here are representative of more than 9,000 samples. We compiled QC results from the 10 programs, used them to investigate taxon-specific probability of misidentifications of freshwater benthic macroinvertebrates. Using cumulative error rates in combination with frequency of observation (freq, as a surrogate for rarity), we developed six uncertainty/frequency classes (UFC) for approximately 1,000 taxa, primarily genus level. The six classes are UFC1, high confidence, common; UFC2, high confidence, moderately common; UFC3, high confidence, rare; UFC4, moderate confidence, rare; UFC5, low confidence, rare; and UFC6, outliers, mixed. From the 1,003 taxa, the percentage falling within each UFC are 3.0, 4.0, 60.4, 7.9, 24.1, and 0.6, respectively. The UFC, error rates, and freq each are potentially useful for additional analyses related to interpreting biological assessment results.

James Stribling (Primary Presenter/Author), Tetra Tech, Inc., james.stribling@tetratech.com;

Erik Leppo (Co-Presenter/Co-Author), Tetra Tech, Inc., erik.leppo@tetratech.com;

11:30 - 11:45 | Salon 5/6 | ALGAL TAXONOMIC DATA QUALITY ACROSS NEON: CHALLENGES AND OPPORTUNITIES FOR OPTIMIZATION

6/04/2024  |   11:30 - 11:45   |  Salon 5/6

ALGAL TAXONOMIC DATA QUALITY ACROSS NEON: CHALLENGES AND OPPORTUNITIES FOR OPTIMIZATION The National Ecological Observatory Network (NEON) is a research platform designed to assess the effects of climate, land-use change, and invasive species across North America. NEON’s aquatic program consists of 24 stream, 7 lake, and 3 river sites across 19 eco-climatic domains. Periphyton and phytoplankton communities, in particular, have been cited as difficult to identify due to their small size, high diversity, and limited taxonomic references. NEON observed a significant effect of laboratory and/or taxonomist on algal community identifications, similar to Bishop et al. 2017. Analyses of NEON algal taxonomy data showed that samples collected across different types of habitats (riffles, runs, and pools) were not significantly different, likely due to the high variation between samples. However, substratum type (e.g., cobbles, sand, plant surface), which is closely related to habitat type, were correlated with community structure. Discussions with NEON technical working groups and the user community resulted in a multi-part plan for optimization of the Periphyton, seston, and phytoplankton collection data product (DP1.20166.001). First, implement voucher flora and taxonomic harmonization. Next, align field sampling more closely with that of the NRSA program by compositing multiple samples within habitat types at each NEON aquatic site. NEON has also reduced laboratory analysis time by discontinuing soft algae analysis for stream periphyton, similar to NRSA, while archiving permanent diatom slides. Finally, a filter for future metabarcode analysis will be archived at the NEON Biorepository to be requested by users. Changes to the NEON data product were implemented starting in January 2024.

Stephanie Parker (Primary Presenter/Author), Battelle, National Ecological Observatory Network (NEON), sparker@battelleecology.org;

11:45 - 12:00 | Salon 5/6 | METADATA AND MEASUREMENT QUALITY OBJECTIVES AS KEY TO DATA-MINING IN LARGE SPATIAL SCALE ANALYSES

6/04/2024  |   11:45 - 12:00   |  Salon 5/6

Metadata and Measurement Quality Objectives as Key to Data-Mining in Large Spatial Scale Analyses The ubiquity of monitoring and assessment programs using algal community composition as a tool for biological assessment, human health indicators, and evaluating ecological response to stressors is well-known. In the United States, national programs such as the National Aquatic Resource Survey (NARS), North American Water Quality Assessment (NAQWA), and more recently the National Ecological Observation Network (NEON) have collected periphyton and/or phytoplankton samples simultaneous with smaller scale efforts by several regional, state, and local programs. Cumulatively, data from these programs present an enhanced opportunity to further the role algal-based indicators can play in assessing ecological and environmental conditions across multiple spatial scales. As programs have evolved, field sampling, laboratory processing, and data analysis methods often have been updated or otherwise changed bringing questions to the validity of combining data from different programs. Identification and enumeration of algal samples has depended almost exclusively on morphological taxonomic analysis using a host of microscopy techniques necessary to reliably attain prescribed taxonomic targets. Significant efforts have already been made to increase the precision and consistency of taxonomic data in diatoms, with similar efforts beginning for other algal groups. Here we propose a series of potential data quality, performance measures, and measurement quality objectives to be incorporated into metadata requirements for precision of field sampling, precision and consistency of taxonomic identifications, and metric and index responsiveness. Ultimately, these would allow secondary data users to determine suitability and reliability of a dataset for combining with others, and could be established as routine features of monitoring datasets.

Sean Sullivan (Primary Presenter/Author), Rhithron Associates, Inc, ssullivan@rhithron.com;

James Stribling (Co-Presenter/Co-Author), Tetra Tech, Inc., james.stribling@tetratech.com;