Chlorophyll a in lakes and streams of the United States (2005-2022).

The concentration of chlorophyll a in phytoplankton and periphyton represents the amount of algal biomass. We compiled an 18-year record (2005-2022) of pigment data from water bodies across the United States (US) to support efforts to develop process-based, machine learning, and remote sensing models for prediction of harmful algal blooms (HABs). To our knowledge, this dataset of nearly 84,000 sites and over 1,374,000 pigment measurements is the largest compilation of harmonized discrete, laboratory-extracted chlorophyll data for the US. These data were compiled from the Water Quality Portal (WQP) and previously unpublished U.S. Geological Survey's National Water Quality Laboratory (NWQL) data. Data were harmonized for reporting units, pigment type, duplicate values, collection depth, site name, negative values, and some extreme values. Across the country, data show great variation by state in sampling frequency, distribution, and methods. Uses for such data include the calibration of models, calibration of field sensors, examination of relationship to nutrients and other drivers, evaluation of temporal trends, and other applications addressing local to national scale concerns.

A web-based tool for assessing the condition of benthic diatom assemblages in streams and rivers of the conterminous United States.

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.

A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States.

Sediment diatoms are widely used to track environmental histories of lakes and their watersheds, but merging datasets generated by different researchers for further large-scale studies is challenging because of taxonomic discrepancies caused by rapidly evolving diatom nomenclature and taxonomic concepts. We collated five datasets of lake sediment diatoms from the Northeastern USA using a harmonization process which included updating synonyms, tracking the identity of inconsistently identified taxa, and grouping those that could not be resolved taxonomically. Each harmonization step led to an increase in variation explained by environmental variables and a parallel reduction of variation attributable to taxonomic inconsistency. To maximize future use of the data and underlying specimens we provide the original and harmonized counts for 1327 core samples from 607 lakes, name translation schemes, sample metadata, specimen museum locations, and the Northeast Lakes Voucher Flora, which is a set of light microscope images grouped into 1154 morphological operational taxonomic units. Post-hoc harmonization enables data quality control when other approaches (e.g., upfront management of taxonomic consistency) are not possible.

Diatoms.org: supporting taxonomists, connecting communities.

Consistent identification of diatoms is a prerequisite for studying their ecology, biogeography, and successful application as environmental indicators. However, taxonomic consistency among observers has been difficult to achieve, because taxonomic information is scattered across numerous literature sources, presenting challenges to the diatomist. First, literature is often inaccessible because of cost, or its location in journals that are not widely circulated. Second, taxonomic revisions of diatoms are taking place faster than floras can be updated. Finally, taxonomic information is often contradictory across literature sources. These issues can be addressed by developing a content creation community dedicated to making taxonomic, ecological, and image-based data freely available for diatom researchers. Diatoms.org represents such a content curation community, providing open, online access to a vast amount of recent and historical information on North American diatom taxonomy and ecology. The content curation community aggregates existing taxonomic information, creates new content, and provides feedback in the form of corrections and notice of literature with nomenclatural changes. The website not only addresses the needs of experienced diatom scientists for consistent identification, but is also designed to meet users at their level of expertise, including engaging the lay public in the importance of diatom science. The website now contains over 1000 species pages contributed by over 100 content contributors, from students to established scientists. The project began with the intent to provide accurate information on diatom identification, ecology, and distribution using an approach that incorporates engaging design, user feedback, and advanced data access technology. In retrospect, the project that began as an "extended electronic book" has emerged not only as a means to support taxonomists, but for practitioners to communicate and collaborate, expanding the size of and benefits to the content curation community. In this paper, we outline the development of diatoms.org, document key elements of the project, examine ongoing challenges, and consider the unexpected emergent properties, including the value of diatoms.org as a source of data. Ultimately, if the field of diatom taxonomy, ecology, and biodiversity is to be relevant, a new generation of taxonomists needs to be trained and employed using new tools. We propose that diatoms.org is in a key position to serve as a hub of training and continuity for the study of diatom biodiversity and aquatic conditions.

Natural and anthropogenic influences on benthic cyanobacteria in streams of the northeastern United States.

Benthic cyanobacteria are widespread in streams and rivers and have the potential to release toxins. In large numbers, these microorganisms and their toxins present a risk to human health. Cyanobacterial abundance in stream biofilms is typically related to single or a limited set of environmental factors, mainly light availability, water temperature, and nutrient concentrations. However, these factors may act synergistically with watershed characteristics and other stressors, such as anthropogenic pollutants, to affect cyanobacteria. We investigated the influence of multiple regional and local variables on the abundance of benthic cyanobacterial genera in streams using all subsets generalized additive modeling. We examined watershed factors (topography, geology, and climate) alongside in-stream factors (geomorphology, hydrology, pH, specific conductance, nutrients, organic contaminants, and dissolved metals) from 76 sites along an urban gradient in the northeast United States. Each genus responded to a distinct combination of environmental variables, demonstrating strong intergeneric variation in environmental selection of realized niches. Four of the 7 potentially toxigenic genera that we modeled were positively influenced by water temperature or nutrients. Nonetheless, watershed characteristics, streamflow, and/or other water quality pollutants were equally or more influential for the potentially toxigenic genera. Additionally, the relationships between cyanobacterial abundance and environmental factors varied in shape and direction across many genera. In particular, with increasing concentrations of herbicides, polychlorinated biphenyls, or metals, the abundance of roughly half of the affected genera decreased, while the others increased. These results likely demonstrate novel toxic effects of the pollutants on cyanobacterial genera in the environment, while indicating that unmeasured biotic interactions may lead to positive responses for other genera. Our results emphasize the need to consider variables beyond those that are most frequently measured or implicated (e.g., water temperature and nutrients) to more fully understand the environmental conditions that influence the distributions and abundance of potentially harmful cyanobacteria.

Resources and Practices to Improve Diatom Data Quality.

Environmental programs in the United States face technical challenges that inhibit the ability to use diatoms in water quality monitoring and assessment projects. Specifically, inconsistent taxonomy can obscure diatom responses to environmental variables. Problems are the result of (1) limited access to a common set of taxonomic references, especially those that are geographically relevant, (2) inefficient enumeration protocols, (3) lack of complete and transparent documentation of taxa, and (4) limited opportunities for continued education, training, and knowledge sharing. However, robust resources and practices are available to improve diatom data quality and interpretation. Several resources improve diatom data quality, including a publicly accessible taxonomic reference (diatoms.org) and recommended practices. These practices include adoption of the voucher floras, random sample assignment, replicate microscope slides, and improved quality control. Finally, the Society for Freshwater Science Diatom Taxonomic Certification Committee is developing educational materials and certification exams to support practitioner training and to increase the diatom research knowledge base. The resources and practices in this article are broadly applicable to improving basic and applied research on diatoms worldwide.

Nutrients and warming interact to force mountain lakes into unprecedented ecological states.

While deposition of reactive nitrogen (N) in the twentieth century has been strongly linked to changes in diatom assemblages in high-elevation lakes, pronounced and contemporaneous changes in other algal groups suggest additional drivers. We explored the origin and magnitude of changes in two mountain lakes from the end of the Little Ice Age at ca 1850, to ca 2010, using lake sediments. We found dramatic changes in algal community abundance and composition. While diatoms remain the most abundant photosynthetic organisms, concentrations of diatom pigments decreased while pigments representing chlorophytes increased 200-300% since ca 1950 and total algal biomass more than doubled. Some algal changes began ca 1900 but shifts in most sedimentary proxies accelerated ca 1950 commensurate with many human-caused changes to the Earth System. In addition to N deposition, aeolian dust deposition may have contributed phosphorus. Strong increases in summer air and surface water temperatures since 1983 have direct and indirect consequences for high-elevation ecosystems. Such warming could have directly enhanced nutrient use and primary production. Indirect consequences of warming include enhanced leaching of nutrients from geologic and cryosphere sources, particularly as glaciers ablate. While we infer causal mechanisms, changes in primary producer communities appear to be without historical precedent and are commensurate with the post-1950 acceleration of global change.

Reduction of taxonomic bias in diatom species data.

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 five elements of sample preparation, taxon identification and enumeration, and quality control (QC) samples. We used six independent datasets to assess the effect of the adjustments on analytical outcomes. The first dataset was produced by five analysts from three laboratories following a standard protocol (Charles et al. 2002). The remaining datasets were produced by 2-3 analysts in 1-3 laboratories following a revised protocol. The revised protocol included the following modifications: 1) use of Battarbee settling chambers to prepare coverslips, 2) development of coordinated pre-count voucher floras based on morphological operational taxonomic units (mOTUs), 3) random assignment of samples to analysts, 4) post-count identification and documentation of taxa, and 5) increased 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.

Taxonomic harmonization may reveal a stronger association between diatom assemblages and total phosphorus in large datasets.

Diatom data have been collected in large-scale biological assessments in the United States, such as the U.S. Environmental Protection Agency's National Rivers and Streams Assessment (NRSA). However, the effectiveness of diatoms as indicators may suffer if inconsistent taxon identifications across different analysts obscure the relationships between assemblage composition and environmental variables. To reduce these inconsistencies, we harmonized the 2008-2009 NRSA data from nine analysts by updating names to current synonyms and by statistically identifying taxa with high analyst signal (taxa with more variation in relative abundance explained by the analyst factor, relative to environmental variables). We then screened a subset of samples with QA/QC data and combined taxa with mismatching identifications by the primary and secondary analysts. When these combined "slash groups" did not reduce analyst signal, we elevated taxa to the genus level or omitted taxa in difficult species complexes. We examined the variation explained by analyst in the original and revised datasets. Further, we examined how revising the datasets to reduce analyst signal can reduce inconsistency, thereby uncovering the variation in assemblage composition explained by total phosphorus (TP), an environmental variable of high priority for water managers. To produce a revised dataset with the greatest taxonomic consistency, we ultimately made 124 slash groups, omitted 7 taxa in the small naviculoid (e.g., Sellaphora atomoides) species complex, and elevated Nitzschia, Diploneis, and Tryblionella taxa to the genus level. Relative to the original dataset, the revised dataset had more overlap among samples grouped by analyst in ordination space, less variation explained by the analyst factor, and more than double the variation in assemblage composition explained by TP. Elevating all taxa to the genus level did not eliminate analyst signal completely, and analyst remained the most important predictor for the genera Sellaphora, Mayamaea, and Psammodictyon, indicating that these taxa present the greatest obstacle to consistent identification in this dataset. Although our process did not completely remove analyst signal, this work provides a method to minimize analyst signal and improve detection of diatom association with TP in large datasets involving multiple analysts. Examination of variation in assemblage data explained by analyst and taxonomic harmonization may be necessary steps for improving data quality and the utility of diatoms as indicators of environmental variables.

Life cycle size dynamics in Didymosphenia geminata (Bacillariophyceae).

Didymosphenia geminata has received a great deal of attention in the last 25 years, and considerable effort has gone into determining the origin, ecological impact, and economic consequences of its invasive behavior. While environmental conditions are a controlling influence in distribution, the extreme success of the species may be tied to its basic biology and life history. Little is known, however, about population dynamics, size restoration and reproduction of D. geminata. The objective of this study was to determine the temporal patterns in cell size frequency, size restoration strategy, and synchronization of life cycles between populations in close proximity. We implemented FlowCam technology to measure the length of more than 100,000 D. geminata cells from two sites in South Boulder Creek, Colorado over 1 year. We applied finite mixture modeling to uncover temporal patterns in size distribution. Our results show that collections of D. geminata exhibited a complex, multimodal size distribution, almost always containing four overlapping age cohorts. We failed to observe direct visual evidence of the sexual phase. Multiple abrupt and directional shifts in size distribution, however, were documented providing conclusive evidence of cell size restoration. Lastly, nodules in close proximity were asynchronous with respect to size frequency profiles and size diminution, highlighting the relevance of spatial heterogeneity in in situ diatom size dynamics. This study is the first to document the complexity of diatom cell size distribution in a lotic system, size restoration in D. geminata, and the variability in rates of size reduction at microhabitat spatial scales.