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We hypothesized that the resident and migrating cold-water zooplankton in Lake Superior concentrate beneath the thermocline and elevate nutrient availability via mineralization in the deep chlorophyll layer (DCL). In August 2010 and 2011, diel vertical net tows and incubation experiments were conducted in the western arm of Lake Superior to measure zooplankton distribution and excretion of dissolved nutrients. Limnocalanus macrurus showed the strongest spatial overlap with the DCL, and the broader crustacean community excreted P at 0.145 µg x [mg.sup.-1] x [h.sup.-1] and N at 0.617 µg x [mg.sup.-1] x [h.sup.-1] as soluble reactive phosphorus (SRP) and ammonia, respectively. Mysis diluviana displayed strong diel vertical migration into the DCL and excreted P at 0.013 µg x [mg.sup.-1] x [h.sup.-1] and N at 0.116 µg x [mg.sup.-1] x [h.sup.-1] as SRP and ammonia, respectively. Based on primary productivity estimates, the zooplankton community has the potential to meet the daily phosphorus demand by phytoplankton in the DCL during lateseason stratification. Our excretion estimates indicate a possible coupling between the cold-water zooplankton community and production in the DCL of Lake Superior. Nous postulons que les communautes de zooplancton d'eau froide residente et migratrice dans le lac Superieur se concentrent sous la thermocline et rehaussent la disponibilite de nutriments par l'intermediaire de la mineralisation dans la couche profonde de chlorophylle (CPC). En aout 2010 et 2011, des traits verticaux nycthemeraux au filet et des experiences d'incubation ont ete employes dans le bras ouest du lac Superieur pour mesurer la repartition du zooplancton et l'excretion de nutriments dissous. Limnocalanus macrurus presentait le chevauchement spatial le plus marque avec la CPC, et la grande communaute de crustaces excretait 0,145 µg P x [mg.sup.-1] x [h.sup.-1] et 0,617 µg N x [mg.sup.-1] x [h.sup.-1] pour le phosphore reactif soluble (PRS) et l'ammoniaque, respectivement. Mysis diluviana presentait une forte migration verticale nycthemerale vers la CPC et excretait 0,013 µg P x [mg.sup.-1] x [h.sup.-1] et 0,116 µg N x [mg.sup.-1] x [h.sup.-1] pour le PRS et l'ammoniaque, respectivement. A la lumiere d'estimations de la productivite primaire, la communaute de zooplancton a le potentiel de repondre a la demande quotidienne de phosphore du phytoplancton dans la CPC durant la stratification saisonniere tardive. Nos estimations de l'excretion indiquent un couplage possible entre la communaute de zooplancton d'eau froide et la production dans la CPC du lac Superieur. [Traduit par la Redaction], Introduction Primary production in Lake Superior during stratification is phosphorus limited (Guildford et al. 2000; Sterner et al. 2004). Supplies of external phosphorus are low, only a small fraction of [...]

Deep learning (DL) models are increasingly used to make accurate hindcasts of management‐relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real‐time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process‐guided DL and DA approach to make 7‐day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1‐day‐ahead and 1.4 to 1.9°C for 7‐day‐ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process‐guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision‐making. [ABSTRACT FROM AUTHOR]

Watersheds of the Great Lakes Basin (USA/Canada) are highly modified and impacted by human activities including pesticide use. Despite labeling restrictions intended to minimize risks to nontarget organisms, concerns remain that environmental exposures to pesticides may be occurring at levels negatively impacting nontarget organisms. We used a combination of organismal‐level toxicity estimates (in vivo aquatic life benchmarks) and data from high‐throughput screening (HTS) assays (in vitro benchmarks) to prioritize pesticides and sites of concern in streams at 16 tributaries to the Great Lakes Basin. In vivo or in vitro benchmark values were exceeded at 15 sites, 10 of which had exceedances throughout the year. Pesticides had the greatest potential biological impact at the site with the greatest proportion of agricultural land use in its basin (the Maumee River, Toledo, OH, USA), with 72 parent compounds or transformation products being detected, 47 of which exceeded at least one benchmark value. Our risk‐based screening approach identified multiple pesticide parent compounds of concern in tributaries of the Great Lakes; these compounds included: eight herbicides (metolachlor, acetochlor, 2,4‐dichlorophenoxyacetic acid, diuron, atrazine, alachlor, triclopyr, and simazine), three fungicides (chlorothalonil, propiconazole, and carbendazim), and four insecticides (diazinon, fipronil, imidacloprid, and clothianidin). We present methods for reducing the volume and complexity of potential biological effects data that result from combining contaminant surveillance with HTS (in vitro) and traditional (in vivo) toxicity estimates. Environ Toxicol Chem 2023;42:367–384. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

To help meet the objectives of the Great Lakes Restoration Initiative with regard to increasing knowledge about toxic substances, 223 pesticides and pesticide transformation products were monitored in 15 Great Lakes tributaries using polar organic chemical integrative samplers. A screening‐level assessment of their potential for biological effects was conducted by computing toxicity quotients (TQs) for chemicals with available US Environmental Protection Agency (USEPA) Aquatic Life Benchmark values. In addition, exposure activity ratios (EAR) were calculated using information from the USEPA ToxCast database. Between 16 and 81 chemicals were detected per site, with 97 unique compounds detected overall, for which 64 could be assessed using TQs or EARs. Ten chemicals exceeded TQ or EAR levels of concern at two or more sites. Chemicals exceeding thresholds included seven herbicides (2,4‐dichlorophenoxyacetic acid, diuron, metolachlor, acetochlor, atrazine, simazine, and sulfentrazone), a transformation product (deisopropylatrazine), and two insecticides (fipronil and imidacloprid). Watersheds draining agricultural and urban areas had more detections and higher concentrations of pesticides compared with other land uses. Chemical mixtures analysis for ToxCast assays associated with common modes of action defined by gene targets and adverse outcome pathways (AOP) indicated potential activity on biological pathways related to a range of cellular processes, including xenobiotic metabolism, extracellular signaling, endocrine function, and protection against oxidative stress. Use of gene ontology databases and the AOP knowledgebase within the R‐package ToxMixtures highlighted the utility of ToxCast data for identifying and evaluating potential biological effects and adverse outcomes of chemicals and mixtures. Results have provided a list of high‐priority chemicals for future monitoring and potential biological effects warranting further evaluation in laboratory and field environments. Environ Toxicol Chem 2023;42:340–366. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

Despite their small spatial extent, fluvial ecosystems play a significant role in processing and transporting carbon in aquatic networks, which results in substantial emission of methane (CH4) to the atmosphere. For this reason, considerable effort has been put into identifying patterns and drivers of CH4 concentrations in streams and rivers and estimating fluxes to the atmosphere across broad spatial scales. Yet progress toward these ends has been slow because of pronounced spatial and temporal variability of lotic CH4 concentrations and fluxes and by limited data availability across diverse habitats and physicochemical conditions. To address these challenges, we present the first comprehensive database of CH4 concentrations and fluxes for fluvial ecosystems along with broadly relevant and concurrent physical and chemical data. The Global River Methane database (GriMeDB; https://doi.org/10.6073/pasta/b7d1fba4f9a3e365c9861ac3b58b4a90) includes 24,024 records of CH4 concentration and 8,205 flux measurements from 5,037 unique sites that were extracted from publications, reports, data repositories, and other outlets published between 1973 and 2021. GriMeDB also includes 17,655 and 8,409 concurrent measurements of concentrations and 4,444 and 1,521 of fluxes for CO2 and nitrous oxide (N2O) respectively. Most observations are date-specific (i.e., not site averages) and many are supported by data for 12 physicochemical variables and 6 site variables. Site variables include codes to characterize marginal channel types (e.g., springs, ditches) and/or presence of human disturbance (e.g., point source inputs, upstream dams). Overall, observations in GRiMeDB encompass a broad range of the climatic, biological, and physical conditions that occur among world river basins, although some geographic gaps remain (e.g., arid regions, tropical regions, high latitudes and altitude systems). The global median CH4 concentration (0.20 μmol L-1) and diffusive flux (0.44 mmol m-2 d-1) in GRiMeDB are lower than estimates from past, site-averaged compilations, although ranges and standard deviations are greater from this larger and more temporally-resolved database. Available flux data are dominated by diffusive measurements despite the recognized importance of ebullitive and plant-mediated CH4 fluxes. Despite these limitations, GriMeDB provides a comprehensive and cohesive resource for examining relationships between CH4 and environmental drivers, estimating the contribution of fluvial ecosystems to CH4 emissions, and to contextualize site-based investigations. [ABSTRACT FROM AUTHOR]

Lakes process both terrestrial and aquatic organic matter, and the relative contribution from each source is often measured via ecosystem metabolism and terrestrial resource use in the food web (i.e., consumer allochthony). Yet, ecosystem metabolism and consumer allochthony are rarely considered together, despite possible interactions and potential for them to respond to the same lake characteristics. In this study, we compiled global datasets of lake gross primary production (GPP), ecosystem respiration (ER), and zooplankton allochthony to compare the strength and shape of relationships with physicochemical characteristics across a broad set of lakes. GPP was positively related to total phosphorus (TP) in lakes with intermediate TP concentrations (11–75 μg L−1) and was highest in lakes with intermediate dissolved organic carbon (DOC) concentrations. While ER and GPP were strongly positively correlated, decoupling occurred at high DOC concentrations. Lastly, allochthony had a unimodal relationship with TP and related variably to DOC. By integrating metabolism and allochthony, we identified similar change points in GPP and zooplankton allochthony at intermediate DOC (4.5–10 mg L−1) and TP (8–20 μg L−1) concentrations, indicating that allochthony and GPP may be coupled and inversely related. The ratio of DOC:nutrients also helped to identify conditions where lake organic matter processing responded more to autochthonous or allochthonous organic matter sources. As lakes globally face eutrophication and browning, predicting how lake organic matter processing will respond requires an updated paradigm that incorporates nonlinear dynamics and interactions. [ABSTRACT FROM AUTHOR]

Abstract: Nitrogen (N) and phosphorus (P) commonly stimulate phytoplankton production in lakes, but recent observations from lakes from an agricultural region suggest that nitrate may have a subsidy‐stress effect on chlorophyll a (Chl a). It is unclear, however, how generalizable this effect might be. Here, we analyzed a large water quality dataset of 2385 lakes spanning 60 regions across 17 states in the Northeastern and Midwestern U.S. to determine if N subsidy‐stress effects on phytoplankton are common and to identify regional landscape characteristics promoting N stress effects in lakes. We used a Bayesian hierarchical modeling framework to test our hypothesis that Chl a–total N (TN) threshold relationships would be common across the central agricultural region of the U.S. (“the Corn Belt”), where lake N and P concentrations are high. Data aggregated across all regions indicated that high TN concentrations had a negative effect on Chl a in lakes with concurrent high total P. This large‐scale pattern was driven by relationships within only a subset of regions, however. Eight regions were identified as having Chl a–TN threshold relationships, but only two of these regions located within the Corn Belt clearly demonstrated this subsidy‐stress relationship. N stress effects were not consistent across other intense agricultural regions, as we hypothesized. These findings suggest that interactions among regional land use and land cover, climate, and hydrogeology may be important in determining the synergistic conditions leading to N subsidy‐stress effects on lake phytoplankton. [ABSTRACT FROM AUTHOR]