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Indicators based on nutrient-biota relationships in streams can inform water quality restoration and protection programs. Bacterial assemblages could be particularly useful indicators of nutrient effects because they are species-rich, important contributors to ecosystem processes in streams, and responsive to rapidly changing conditions. Here, we sampled 25 streams weekly (12–14 times each) and used 16S rRNA gene metabarcoding of periphyton-associated bacteria to quantify the effects of total phosphorus (TP) and total nitrogen (TN). Threshold indicator taxa analysis identified assemblage-level changes and amplicon sequence variants (ASVs) that increased or decreased with increasing TP and TN concentrations (i.e., low P, high P, low N, and high N ASVs). Boosted regression trees confirmed that relative abundances of gene sequence reads for these four indicator groups were associated with nutrient concentrations. Gradient forest analysis complemented these results by using multiple predictors and random forest models for each ASV to identify portions of TP and TN gradients at which the greatest changes in assemblage structure occurred. Synthesized statistical results showed bacterial assemblage structure began changing at 24 µg TP/L with the greatest changes occurring from 110 to 195 µg/L. Changes in the bacterial assemblages associated with TN gradually occurred from 275 to 855 µg/L. Taxonomic and phylogenetic analyses showed that low nutrient ASVs were commonly Firmicutes, Verrucomicrobiota, Flavobacteriales, and Caulobacterales, Pseudomonadales, and Rhodobacterales of Proteobacteria, whereas other groups, such as Chitinophagales of Bacteroidota, and Burkholderiales, Rhizobiales, Sphingomonadales, and Steroidobacterales of Proteobacteria comprised the high nutrient ASVs. Overall, the responses of bacterial ASV indicators in this study highlight the utility of metabarcoding periphyton-associated bacteria for quantifying biotic responses to nutrient inputs in streams.

A data-driven approach to characterizing the risk of cyanobacteria-based harmful algal blooms (cyanoHABs) was undertaken for the Ohio River. Twenty-five years of river discharge data were used to develop Bayesian regression models that are currently applicable to 20 sites spread-out along the entire 1579 km of the river’s length. Two site-level prediction models were developed based on the antecedent flow conditions of the two blooms that occurred on the river in 2015 and 2019: one predicts if the current year will have a bloom (the occurrence model), and another predicts bloom persistence (the persistence model). Predictors for both models were based on time-lagged average flow exceedances and a site’s characteristic residence time under low flow conditions. Model results are presented in terms of probabilities of occurrence or persistence with uncertainty. Although the occurrence of the 2019 bloom was well predicted with the modeling approach, the limited number of events constrained formal model validation. However, as a measure of performance, leave-one-out cross validation returned low misclassification rates, suggesting that future years with flow time series like the previous bloom years will be correctly predicted and characterized for persistence potential. The prediction probabilities are served in real time as a component of a risk characterization tool/web application. In addition to presenting the model’s results, the tool was designed with visualization options for studying water quality trends among eight river sites currently collecting data that could be associated with or indicative of bloom conditions. The tool is made accessible to river water quality professionals to support risk communication to stakeholders, as well as serving as a real-time water data monitoring utility.

Recent studies suggest that photophysiological parameters for intact substrates with depth (e.g., periphytic biofilms, microphytobenthos) are overestimated by pulse-amplitude modulated (PAM) fluorometry. This overestimation results from depth-integration effects, following the activation of deeper photosynthesizing layers by an attenuated light signal. To mitigate this error, we propose a novel slide-based thin-film technique in which fluorescence is measured on a vertically representative subsample of the biofilm, spread evenly on a microscope slide. We compared bias and precision for photosynthetic parameters estimated through conventional PAM fluorometry on intact biofilms and through our novel slide-based technique, both theoretically and empirically. Numerical simulations confirmed the consistent overestimation of key parameters for intact biofilms, with relative errors up to 145%, compared to, at most, 52% on thin films. Paired empirical observations likewise demonstrated that estimates based on intact biofilms were consistently higher (up to 248%, p<0.001) than estimates from thin films. Numerical simulation suggested greater precision with the slide-based technique for homogeneous biofilms, but potentially less precision for heterogeneous biofilms with improper subsampling. Our empirical comparison, however, demonstrated some improvement in precision with the slide-based technique (e.g., the coefficient of variation for the maximum electron transport rate was reduced 30%, p=0.009). We recommend the use of the slide-based technique, particularly for biofilms that are thick or have small light attenuation coefficients. Care should be taken, however, to obtain vertically representative subsamples of the biofilm for measurement.

Wastewaters and leachates from various inland resource extraction activities contain high ionic concentrations and differ in ionic composition, which complicates the understanding and effective management of their relative risks to stream ecosystems. To this end, we conducted a stream mesocosm dose–response experiment using two dosing recipes prepared from industrial salts. One recipe was designed to generally reflect the major ion composition of deep well brines (DWB) produced from gas wells (primarily Na+, Ca2+, and Cl−) and the other, the major ion composition of mountaintop mining (MTM) leachates from coal extraction operations (using salts dissociating to Ca2+, Mg2+, Na+, SO42− and HCO3−)—both sources being extensive in the Central Appalachians of the USA. The recipes were dosed at environmentally relevant nominal concentrations of total dissolved solids (TDS) spanning 100 to 2000 mg/L for 43 d under continuous flow-through conditions. The colonizing native algal periphyton and benthic invertebrates comprising the mesocosm ecology were assessed with response sensitivity distributions (RSDs) and hazard concentrations (HCs) at the taxa, community (as assemblages), and system (as primary and secondary production) levels. Single-species toxicity tests were run with the same recipes. Dosing the MTM recipe resulted in a significant loss of secondary production and invertebrate taxa assemblages that diverged from the control at all concentrations tested. Comparatively, intermediate doses of the DWB recipe had little consequence or increased secondary production (for emergence only) and had assemblages less different from the control. Only the highest dose of the DWB recipe had a negative impact on certain ecologies. The MTM recipe appeared more toxic, but overall, for both types of resource extraction wastewaters, the mesocosm responses suggested significant changes in stream ecology would not be expected for specific conductivity below 300 µS/cm, a published aquatic life benchmark suggested for the region.

Low Impact Development (LID) is an alternative to conventional urban stormwater management practices, which aims at mitigating the impacts of urbanization on water quantity and quality. Plot and local scale studies provide evidence of LID effectiveness; however, little is known about the overall watershed scale influence of LID practices. This is particularly true in watersheds with a land cover that is more diverse than that of urban or suburban classifications alone. We address this watershed-scale gap by assessing the effects of three common LID practices (rain gardens, permeable pavement, and riparian buffers) on the hydrology of a 0.94 km2 mixed land cover watershed. We used a spatially-explicit ecohydrological model, called Visualizing Ecosystems for Land Management Assessments (VELMA), to compare changes in watershed hydrologic responses before and after the implementation of LID practices. For the LID scenarios, we examined different spatial configurations, using 25%, 50%, 75% and 100% implementation extents, to convert sidewalks into rain gardens, and parking lots and driveways into permeable pavement. We further applied 20 m and 40 m riparian buffers along streams that were adjacent to agricultural land cover. The results showed overall increases in shallow subsurface runoff and infiltration, as well as evapotranspiration, and decreases in peak flows and surface runoff across all types and configurations of LID. Among individual LID practices, rain gardens had the greatest influence on each component of the overall watershed water balance. As anticipated, the combination of LID practices at the highest implementation level resulted in the most substantial changes to the overall watershed hydrology. It is notable that all hydrological changes from the LID implementation, ranging from 0.01 to 0.06 km2 across the study watershed, were modest, which suggests a potentially limited efficacy of LID practices in mixed land cover watersheds.

Global estimates of methane (CH₄) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra-reservoir spatial variability. Reservoir-scale emission rates are often estimated by extrapolating from measurement made at a few locations; however, error and bias associated with this approach can be large and difficult to quantify. Here, we use a generalized random tessellation survey (GRTS) design to generate unbiased estimates of reservoir-CH₄ emissions rates (± 95% CI) for areas below tributary inflows, open-waters, and at the whole-reservoir scale. Total CH₄ emission rates (i.e., sum of ebullition and diffusive emissions) were 4.8 (± 2.1), 33.0 (± 10.7), and 8.3 (± 2.2) mg CH₄ m-2 h-1 in open-waters, tributary-associated areas, and the whole-reservoir for the period in August 2014 during which 115 sites were sampled across an 7.98 km² reservoir in Southwestern, Ohio, U.S.A. Tributary areas occupy 12% of the reservoir surface, but were the source of 41% of total CH₄ emissions, highlighting the importance of riverinelacustrine transition zones. Ebullition accounted for > 90% of CH₄ emission at all spatial scales. Overall, CH₄ emission rates were high for a temperate zone reservoir, possibly because earlier studies underestimated ebullition or did not include emission hot spots. Confidence interval estimates that incorporated spatial pattern in CH₄ emissions were up to 29% narrower than when spatial independence is assumed among sites. The use of GRTS, or other probabilistic survey designs, can improve the accuracy and precision of reservoir emission rate estimates, which is needed to better constrain uncertainty in global scale emission estimates.

Nutrient pollution from human activities remains a common problem facing stream ecosystems. Identifying ecological responses to phosphorus and nitrogen can inform decisions affecting the protection and management of streams and their watersheds. Diatoms are particularly useful because they are a highly diverse group of unicellular algae found in nearly all aquatic environments and are sensitive responders to increased nutrient concentrations. Here, we used DNA metabarcoding of stream diatoms as an approach to quantifying effects of total phosphorus (TP) and total nitrogen (TN). Threshold indicator taxa analysis (TITAN) identified operational taxonomic units (OTUs) that increased or decreased along TP and TN gradients along with nutrient concentrations at which assemblages had substantial changes in the occurrences and relative abundances of OTUs. Boosted regression trees showed that relative abundances of gene sequence reads for OTUs identified by TITAN as low P, high P, low N, or high N diatoms had strong relationships with nutrient concentrations, which provided support for potentially using these groups of diatoms as metrics in monitoring programs. Gradient forest analysis provided complementary information by characterizing multi-taxa assemblage change using multiple predictors and results from random forest models for each OTU. Collectively, these analyses showed that notable changes in diatom assemblage structure and OTUs began around 20 μg TP/L, low P diatoms decreased substantially and community change points occurred from 75 to 150 μg/L, and high P diatoms became increasingly dominant from 150 to 300 μg/L. Diatoms also responded to TN with large decreases in low N diatoms occurring from 280 to 525 μg TN/L and a transition to dominance by high N diatoms from 525–850 μg/L. These diatom responses to TP and TN could be used to inform protection efforts (i.e., antidegradation) and management goals (i.e., nutrient reduction) in streams and watersheds. Our results add to the growing support for using diatom metabarcoding in monitoring programs.

Urban stormwater runoff quantity and quality are strongly dependent upon catchment properties. Models are used to simulate the runoff characteristics, but the output from a stormwater management model is dependent on how the catchment area is subdivided and represented as spatial elements. For green infrastructure modeling, we suggest a discretization method that distinguishes directly connected impervious area (DCIA) from the total impervious area (TIA). Pervious buffers, which receive runoff from upgradient impervious areas should also be identified as a separate subset of the entire pervious area (PA). This separation provides an improved model representation of the runoff process. With these criteria in mind, an approach to spatial discretization for projects using the US Environmental Protection Agency's Storm Water Management Model (SWMM) is demonstrated for the Shayler Crossing watershed (SHC), a well-monitored, residential suburban area occupying 100 ha, east of Cincinnati, Ohio. The model relies on a highly resolved spatial database of urban land cover, stormwater drainage features, and topography. To verify the spatial discretization approach, a hypothetical analysis was conducted. Six different representations of a common urbanscape that discharges runoff to a single storm inlet were evaluated with eight 24 h synthetic storms. This analysis allowed us to select a discretization scheme that balances complexity in model setup with presumed accuracy of the output with respect to the most complex discretization option considered. The balanced approach delineates directly and indirectly connected impervious areas (ICIA), buffering pervious area (BPA) receiving impervious runoff, and the other pervious area within a SWMM subcatchment. It performed well at the watershed scale with minimal calibration effort (Nash–Sutcliffe coefficient  = 0.852; R2 = 0.871). The approach accommodates the distribution of runoff contributions from different spatial components and flow pathways that would impact green infrastructure performance. A developed SWMM model using the discretization approach is calibrated by adjusting parameters per land cover component, instead of per subcatchment and, therefore, can be applied to relatively large watersheds if the land cover components are relatively homogeneous and/or categorized appropriately in the GIS that supports the model parameterization. Finally, with a few model adjustments, we show how the simulated stream hydrograph can be separated into the relative contributions from different land cover types and subsurface sources, adding insight to the potential effectiveness of planned green infrastructure scenarios at the watershed scale.

Reservoirs are a globally significant source of methane (CH 4 ) to the atmosphere. However, emission rate estimates may be biased low due to inadequate monitoring during brief periods of elevated emission rates (that is, hot moments). Here we investigate CH 4 bubbling (that is, ebullition) during periods of falling water levels in a eutrophic reservoir in the Midwestern USA. We hypothesized that periods of water-level decline trigger the release of CH 4 -rich bubbles from the sediments and that these emissions constitute a substantial fraction of the annual CH 4 flux. We explored this hypothesis by monitoring CH 4 ebullition in a eutrophic reservoir over a 7-month period, which included an experimental water-level drawdown. We found that the ebullitive CH 4 flux rate was among the highest ever reported for a reservoir (mean = 32.3 mg CH 4 m −2 h −1 ). The already high ebullitive flux rates increased by factors of 1.4–77 across the nine monitoring sites during the 24-h experimental water-level drawdown, but these emissions constituted only 3% of the CH 4 flux during the 7-month monitoring period due to the naturally high ebullitive CH 4 flux rates that persist throughout the warm weather season. Although drawdown emissions were found to be a minor component of annual CH 4 emissions in this reservoir, our findings demonstrate a link between water-level change and CH 4 ebullition, suggesting that CH 4 emissions may be mitigated through water-level management in some reservoirs.

Nitrogen loading from developed watersheds to aquatic ecosystems can stimulate microbial denitrification, a process that reduces nitrate ( NO 3 − ) to dinitrogen (N₂) or nitrous oxide (N₂O), the latter a potent greenhouse gas. While aquatic ecosystems are a globally significant source of N₂O to the atmosphere, the relationship between denitrification and N₂O production is not well known. Until recently, this field of research has been limited by the technical challenges of simultaneously measuring denitrification and N₂O production or consumption in situ at the ecosystem scale. Here we use membrane inlet mass spectrometry, an analytical method providing precise and accurate measurements of dissolved N₂, and gas chromatography to directly measure N₂ and N₂O concentrations in the hypolimnion of a stratified reservoir draining an agricultural watershed. Denitrification resulted in a consistent increase in dissolved N₂ and decrease in NO 3 − concentrations in the hypolimnion during the 5 month period of stratification, though temporal patterns in dissolved N₂O concentrations were less consistent. Denitrification alternated between an N₂O source and sink, with the N₂O yield, defined as the relative production of N₂O to N₂ via denitrification, ranging from −3.4% (i.e., net N₂O consumption) to 19.5% (mean = −0.03%). Whereas denitrification in the hypolimnion functioned as a small N₂O sink during the stratified period, the reservoir was an N₂O source on an annual time scale. Additional studies across reservoirs of different sizes, trophic status, and ages are needed to resolve the role of reservoirs in the global N₂O budget.