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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Analysis of an optical imaging system prototype for autonomously monitoring zooplankton in an aquaculture facility

Traditional approaches to biomonitoring in aquatic systems, such as sample collection, sorting, and identification, require significant time and effort, thereby limiting the spatiotemporal resolution of sample collection. Additionally, collection and preservation of samples for subsequent taxonomic identification and enumeration leads to mortality of organisms. Recent advances in technologies that utilize optical imaging and machine learning have provided new opportunities to expedite biomonitoring and lead to significant cost savings. These technologies can be advantageous to scientists or managers that conduct routine biomonitoring to inform operations, as in the case of aquaculture facilities. The Small Aquatic Organism optical imaging system (SAO) is a high-throughput optical imaging and classification prototype system that relies on computer vision and machine learning (Support Vector Machines, or SVMs) to autonomously identify and enumerate aquatic organisms. The SAO provides a more sustainable method of collecting large volumes of data and has the benefit of being used in situ. In this study, we tested the performance of the SAO in providing comparable results to manual zooplankton community monitoring in ten ponds at an aquaculture facility. We performed a side-by-side study comparing the sampling methods of plankton tow nets, where major zooplankton taxonomic classes were manually identified and enumerated, to sampling with the SAO. Vouchered samples were used to develop a training library for the SAO, where classes consisted of water boatman and zooplankton groups: cladocerans, copepod adults, copepod nauplii, and rotifers. SAO imagery was manually classified and compared with predicted results for validation. Accuracy for the SVM classifier of the SAO was 37.4 %. Convolutional Neural Networks (CNN) and Random Forest classifiers were also applied to SAO imagery and image features for comparison. The best CNN model and our Random Forest model had accuracies of 80.4 % and 46.6 % respectively. Challenges faced included the small size of copepod nauplii and rotifers and the limited resolution of the imaging camera, although there are tradeoffs between imaging resolution and the sample processing rate. Furthermore, our comparison shows that advancement in both optical imaging and ML are needed in order for the SAO prototype to yield comparable results to manual community monitoring in an aquaculture facility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

The 2017-2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a "Designated Targeted Observable" (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380 - 2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3-5 µm; TIR: 8-12 µm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. Finally, this effort synthesizes the findings of more than 130 scientists.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An approach to urban waterway assessment using holistic values and reciprocity

Current aquatic ecosystem assessment methods and tools often focus on physical, chemical, and biological indicators of ecosystem health. This approach to ecosystem assessment is not always straightforward to execute in urban environments and ignores potential connectivity between social and environmental outcomes. During a workshop at the Symposium on Urbanization and Stream Ecology in Brisbane, Australia in 2023 (SUSE6), we developed an approach to urban aquatic ecosystem assessment that incorporates a holistic perspective. Specifically, our approach considers both environmental (biological, chemical, and physical integrity) and social (community connection, human safety, resource use) values of urban waterways. This approach is inclusive of Indigenous perspectives, such as the concept of reciprocity, whereby consideration of both the environment and society leads to a healthy ecosystem. Here, to highlight how this holistic assessment approach could be used, we present real-world examples that included assessing both environmental and societal values informed by reciprocity or balanced perspectives. This approach can be broadly applied and adapted to specific aquatic ecosystem conditions and projects, providing an inclusive, community-centered approach for assessing the health of waterways in urban environments.

Indigenous knowledge↗
DOE OSTI2023

Seasonal drivers of dissolved oxygen across a tidal creek–marsh interface revealed by machine learning

Abstract Dissolved oxygen (DO) is a key biogeochemical control in coastal systems, and its concentration and drivers vary markedly through time and space. This makes it difficult to accurately represent coastal DO and associated biogeochemical processes in models, limiting our ability to predict how these systems will respond to global change. We obtained high‐frequency (5‐min) in situ measurements of DO collected at three locations across the interface of a tidal creek and coastal marsh in the Pacific Northwest, USA. Random Forest machine learning models quantified the importance of three categories of environmental drivers (Aquatic, Climatic, and Terrestrial) of DO variability across the creek–marsh interface. We selected two 4‐month datasets representing Summer and Winter seasonal periods to test two hypotheses on the dominant drivers of DO at the coastal interface. We found that the Terrestrial driver—characterized by long periods of anaerobic conditions and episodic pulses in DO after floods—was most important during the Winter, whereas the Aquatic driver—characterized by variability over tidal, diel, and lunar cycles—was most important during the Summer. We explored how future climate change scenarios could alter the drivers of DO variability using a cumulative sums driver–response framework. Our results suggest that under climate change, Aquatic and Climatic drivers may increase in importance during the Summer, potentially linked to changing metabolic regimes and sea level, with Terrestrial driver importance potentially increasing during the Winter. Our approach highlights useful methods for understanding the spatiotemporal complexity of oxygen across coastal interfaces and quantifying the relative importance of distinct environmental drivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effects of random forest modeling decisions on biogeochemical time series predictions

Abstract Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important parameterization decisions for appropriate use and optimal model fit. We explored the role that parameter decisions, including training/testing data splitting strategies, variable selection, and hyperparameters play on RF goodness‐of‐fit by constructing models using 1296 unique parameter combinations to predict concentrations of nitrate, a key nutrient for biogeochemical cycling in aquatic ecosystems. Models were built on long‐term, publicly available water quality and meteorology time series collected by the National Estuarine Research Reserve monitoring network for two contrasting ecosystems representing freshwater and brackish estuaries. We found that accounting for temporal dependence when splitting data into training and testing subsets was key for avoiding over‐estimation of model predictive power. In addition, variable selection, the ratio of training to testing data, and to a lesser degree, variables per split and number of trees, were significant parameters for optimizing RF goodness‐of‐fit. We also explored how model parameter decisions influenced interpretation of the relative importance of predictors to the model, and model predictor‐dependent variable relationships, with results suggesting that both data structure and model parameterization influence these factors. Because much of the current RF literature is written for the computational and statistical science communities, the primary goal of this study is to provide guidelines for aquatic scientists new to machine learning to apply RF techniques appropriately to aquatic biogeochemical datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Native bee Pollination Ecosystem Services in Agricultural Wetlands and Riparian Protected Lands

Abstract Many freshwater wetlands and riparian systems are protected within agricultural landscapes. Yet, pollinator ecosystem services are seldom considered key ecosystem services provided by these conservation easements. The purpose of this study is to explore the extent of protected aquatic lands to provide pollination ecosystem services by assessing pollinator abundances, crop yield changes, and value estimations of increased soybean yields from a subset of common native solitary bees. We created a novel geodatabase of United States Department of Agriculture (USDA) conservation easements and used this database in the InVEST crop pollination model to model wild solitary bee pollination. We then estimated the monetary value of yield increases provided by pollinators. We found that wetland uplands provided the greatest potential for pollination services for ground nesting bees, followed by herbaceous and forested riparian respectively. Stem nesters preferred forested riparian, then upland habitats. In soybeans fields, we found wild pollinators can provide up to 5.5% yield response from current private aquatic conservation lands. The current landscape is not optimized to use wetlands and riparian conservation lands as pollinator habitat, but these results suggest protected aquatic lands can sustainably increase wild pollination services to agricultural crops if landscapes are managed, protected, and optimized with pollinator services as co-benefit.

Hinson, Audra L. (ORCID:0000000242314820)↗
DOE OSTI2020

The direct and indirect effects of copper on vector-borne disease dynamics

Metal pollution is a growing concern that affects the health of humans and animals globally. Copper is an essential insect micronutrient required for respiration, pigmentation and oxidative stress protection but can also act as a potentially toxic trace element. While several studies have focused on the negative fitness effects of copper on the aquatic larvae of mosquitoes, the effects of larval copper exposure on adult mosquito fitness (i.e., survival and fecundity) and their ability to transmit parasites (i.e., vector competence) remains unclear. Here, using a well-studied model vector-parasite system, the mosquito Aedes aegypti and parasite Dirofilaria immitis, we show that sublethal copper exposure in larval mosquitoes alters adult female fecundity and vector competence. Specifically, mosquitoes exposed to copper had a hormetic fecundity response and mosquitoes exposed to 600 μg/L of copper had significantly fewer infective parasite larvae than control mosquitoes not exposed to copper. Therefore, exposure of mosquito larvae to copper levels far below EPA-mandated safe drinking water limits (1300 μg/L) can impact vector-borne disease dynamics not only by reducing mosquito abundance (through increased larval mortality), but also by reducing parasite transmission risk. Our results also demonstrated that larval copper is retained through metamorphosis to adulthood in mosquitoes, indicating that these insects could transfer copper from aquatic to terrestrial foodwebs, especially in urban areas where they are abundant. To our knowledge this is the first study to directly link metal exposure with vector competence (i.e., ability to transmit parasites) in any vector-parasite system. Additionally, it also demonstrates unequivocally that mosquitoes can transfer contaminants from aquatic to terrestrial ecosystems. These results have broad implications for public health because they directly linking contaminants and vector-borne disease dynamics, as well as linking mosquitoes and contaminant dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multi-decadal trends in mercury and methylmercury concentrations in the brown watersnake (Nerodia taxispilota)

Mercury (Hg) is an environmental contaminant that poses a threat to aquatic systems globally. Temporal evaluations of Hg contamination have increased in recent years, with studies focusing on how anthropogenic activities impact Hg bioavailability in a variety of aquatic systems. While it is common for these studies and ecological risk assessments to evaluate Hg bioaccumulation and effects in wildlife, there is a paucity of information regarding Hg dynamics in reptiles. The goal of this study was to investigate temporal patterns in total mercury (THg) and methylmercury (MeHg) concentrations across a 36-year period, as well as evaluate relationships among and between destructive (kidney, liver, muscle) and non-destructive (blood, tail) tissue types in a common watersnake species. To accomplish this, we measured THg and MeHg concentrations in multiple tissues from brown watersnakes (Nerodia taxispilota) collected from Steel Creek on the Savannah River Site (SRS; Aiken, SC, USA) from two time periods (1983–1986 and 2019). We discovered significant and positive relationships between tail tips and destructive tissues. In both time periods, THg concentrations varied significantly by tissue type, and destructive tissues exhibited higher but predictable THg values relative to tail tissue. Methylmercury concentrations did not differ among tissues from the 1980s but was significantly higher in muscle compared to other tissues from snakes collected in 2019. Percent MeHg of THg in N. taxispilota tissues mirrored patterns reported in other reptiles, although the range of % MeHg in liver and kidney differed between time periods. Both THg and MeHg concentrations in N. taxispilota declined significantly from the 1980s to 2019, with average values 1.6 to 4-fold lower in contemporary samples. Overall, our data add further evidence to the utility of watersnakes to monitor Hg pollution in aquatic environments and suggest attenuation of this contaminant in watersnakes in our study system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Water acidification aggravates lithium-induced toxicity represented by energy supply, oxidative stress, and cell fate in Daphnia magna neonates

Lithium is extensively utilized in industrial energy production, particularly in lithium-ion batteries, and in pharmaceuticals for the treating clinical mood disorders. Consequently, lithium is frequently detected in various environmental matrices. It has been reported to cause a range of toxic effects on aquatic organisms including oxidative stress, neurological disorders, and reproductive suppression. Water acidification is a global issue with numerous negative impacts on aquatic organisms. It can alter the physio-chemical properties and bioavailability of metal ions. The acidic leaching process during lithium battery treatment and global water acidification both suggest that lithium contamination often occurs in acidic environments. In the present study, Daphnia magna neonates were exposed to four treatments (control, lithium alone, low pH, and combined) to investigate whether an acidic environment exacerbates the toxic effects of lithium on aquatic organisms and to explore potential toxic action mechanisms. The results indicated that low pH posed a significant threat to the growth and reproduction of D. magna. When exposed to both lithium and low pH, there was increased lithium accumulation and an energy trade-off response, leading to increased energy allocation to reproduction and reduced energy for growth. Lithium exposure stimulated D. magna activity, while low pH inhibited it, suggesting that an imbalance in energy consumption and supply. Combined exposure to lithium and low pH resulted in severe oxidative stress due to mitochondrial dysfunction, under-utilization of energy substances, and increased ionic homeostasis disturbances. Consequently, the exposed organism altered apoptosis and autophagy processes to maintain homeostasis. In conclusion, the present study demonstrated that lithium and water acidification posed a population-level threat to D. magna, and their combined exposure significantly largely exacerbated the toxic effects.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Mercury Reduction, Uptake, and Species Transformation by Freshwater Alga Chlorella vulgaris under Sunlit and Dark Conditions

As a major entry point of mercury (Hg) to aquatic food webs, algae play an important role in taking up and transforming Hg species in aquatic ecosystems. However, little is known how and to what extent Hg reduction, uptake, and species transformations are mediated by algal cells and their exudates, algal organic matter (AOM), under either sunlit or dark conditions. In this study, using Chlorella vulgaris (CV) as one of the most prevalent freshwater model algal species, we show that solar irradiation could enhance the reduction of mercuric Hg(II) to elemental Hg(0) by both CV cells and AOM. AOM reduced more Hg(II) than algal cells themselves due to cell surface adsorption and uptake of Hg(II) inside the cells under solar irradiation. Synchrotron radiation X-ray absorption near-edge spectroscopy (SR-XANES) analyses indicate that sunlight facilitated the transformation of Hg to less bioavailable species, such as β-HgS and Hg-phytochelatins, compared to Hg(Cysteine) 2 -like species formed in algal cells in the dark. These findings highlight important functional roles and potential mechanisms of algae in Hg reduction and immobilization under varying lighting conditions and how these processes may modulate Hg cycling and bioavailability in the aquatic environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Carbon Dioxide Fluxes to the Atmosphere From Waters Within Flooded Forests in the Amazon Basin

Aquatic habitats in the lowland Amazon emit large quantities of carbon dioxide (CO 2 ). However, information on CO 2 fluxes from seasonally flooded forests that constitute 80% of the surface area of aquatic environments in the lowland Amazon basin is sparse. We provide the first multi-year measurements of CO 2 exchanges within flooded forests of the central Amazon basin. Our approach combines measurement of dissolved CO 2 concentrations and fluxes between the water and atmosphere and ecological data. Although the rates of CO 2 emission by flooded forests are lower than other aquatic habitats, such as open waters in rivers and lakes, the combination of high CO 2 concentrations and a large area results in an appreciable regional out gassing of carbon dioxide from flooded forests. These fluxes can represent about half of the net primary production of flooded forests in the central Amazon basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Chlorophyll- a dynamics in the lower Amazon River: insights from in situ and hyperspectral remote sensing using OCI-PACE

Chlorophyll-a concentration (Chla) is a key indicator of phytoplankton biomass and aquatic trophic status. However, satellite-derived Chla in sediment-rich waters, such as those found in the Lower Amazon River, remains challenging. The present study characterizes in situ Chla levels and their relationships with geographic, physical, and biogeochemical parameters in the Lower Amazon. Data collected between 2014 and 2017 across four hydrological seasons included measurements of Chla, remote sensing reflectance, and water quality parameters such as total suspended sediment, conductivity, water surface temperature, dissolved oxygen, pH, dissolved organic carbon and coloured dissolved organic matter. An empirical model was developed to estimate Chla using simulated hyperspectral bands from NASA’s PACE mission, achieving high performance (R 2 = 0.76; RMSE = 0.11 μg·L −1 ). Red bands proved particularly effective for Chla retrieval, while the addition of ultraviolet bands further enhanced model accuracy. The application of the developed model to satellite imagery yielded results consistent with in situ observations for the same hydrologic season. Seasonal variation and geographic location were major factors influencing Chla dynamics. This study provides a novel contribution to Chla estimation in optically complex, highly turbid waters and highlights the potential of the PACE mission to enhance global aquatic ecosystem monitoring. In conclusion, by offering freely available hyperspectral data with high radiometric resolution, PACE represents a significant advancement in the realm of remote sensing of aquatic environments.

Amazon River↗
DOE OSTI2025

Enantioselective ecotoxicity of promethazine in two freshwater organisms: daphnia (Daphnia magna) and zebrafish ( Danio rerio )

Abstract Chiral pharmaceuticals, racemic or enantiomerically pure forms and their metabolites, can reach aquatic ecosystems via wastewater effluents (inefficient treatment operations) or by direct human disposal. They may negatively affect nontarget organisms even at low environmental concentrations. To make an accurate risk evaluation, the (eco)toxicity of both enantiomers needs to be assessed. Promethazine (PMZ) is a chiral antihistamine that has been detected in aquatic ecosystems owing to its high consumption. Promethazine undergoes metabolism in the liver, producing chiral metabolites such as promethazine sulfoxide (PMZSO) and N-desmethylpromethazine (DMPMZ) that reach water bodies. However, knowledge regarding the enantioselective toxicity of PMZ and its metabolites on aquatic organisms is missing. This study aimed to explore the potential enantioselective toxicity of PMZ and its metabolites on two relevant freshwater organisms, daphniid and fish, representing different trophic levels. The half maximal effect concentrations (EC50s) in Daphnia magna of PMZ, DMPMZ, and PMZSO were 2.33, 2.31, > 4 mg L−1, respectively, > 4 and 2.50 mg L−1 for (R) and (S)-PMZ, respectively, and > 4 mg L−1 for the enantiomers of DMPMZ and PMZSO. In studies involving zebrafish, Danio rerio, (R, S)-PMZ showed a median lethal concentration (LC50) of .72 mg L−1, and specific assays revealed that (R)-PMZ exhibited more pronounced adverse effects on larvae at the embryonic, morphological, and biochemical level than the racemate and (S)-PMZ. Toxicity and potential bioaccumulation of these compounds in daphniids and fish were also conducted using in silico tests through proprietary software. The results revealed a concordance between the experimental and predicted EC50 and LC50 values in both species.

Coelho, Maria Miguel↗
DOE OSTI2022

A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Biogeochemical Changes in Estuaries

The biogeochemical composition of materials suspended and dissolved in estuarine waters is substantially transformed by biological and abiotic processes as water from rivers and subterranean aquifers travels through estuaries to the coastal ocean, influencing the rate of storage and/or exchange of carbon with the atmosphere. Biogeochemical signatures in the upper reaches of estuaries (e.g., low salinity) generally reflect characteristics of the rivers and groundwater draining into the estuary. The composition of organic matter (OM) where rivers meet estuaries is a mixture of terrigenous signatures dependent on watershed landscape features, aquatic signatures dependent on the prominence of freshwater primary productivity, and intermediate metabolites (i.e., byproducts of in situ transformation) of these terrigenous and aquatic OM sources. The prominence of aquatic primary production-derived OM and products of microbial decomposition generally increases towards the lower reaches of estuaries where they meet the coastal ocean (i.e.., continental shelf). The nature of biogeochemical transformations occurring along estuarine gradients is closely coupled with factors that are poised to change under multiple compounding disturbances and stress factors related to both climate change and other anthropogenic global changes. This chapter describes the fundamental mechanisms that drive the transport, transformation, and storage of OM in estuaries and how these dynamics have and may continue to change in response to key disturbances and stressors related to climate change and other anthropogenic global changes including warming, intensifying hydrological extremes (e.g., droughts and floods), sea level rise, and acidification.

Ward, Nicholas D.↗
DOE OSTI2022

Role of copper in nitrous oxide accumulation in wetland soils from Illinois and South Carolina and stream sediments from Tennessee

Denitrification is microbially-mediated through enzymes containing metal cofactors. Laboratory studies of pure cultures have highlighted that the availability of copper (Cu), required for the multicopper enzyme nitrous oxide reductase, can limit nitrous oxide (N2O) reduction. However, in natural aquatic systems, such as wetlands and hyporheic zones in stream beds, the role of Cu in controlling denitrification remains incompletely understood. In this study, we collected soils and sediments from three natural environments -- riparian wetlands, marsh wetlands, and a stream -- to investigate their nitrogen species transformation activity at background Cu levels and different supplemented Cu loadings. All of the systems contained solid-phase associated Cu below or around geological levels (40–280 nmol g-1) and exhibited low dissolved Cu (3–50 nM), which made them appropriate sites for evaluating the effect of limited Cu availability on denitrification.The dataset contains the variation in the nutrient (nitrate (NO3-), nitrite (NO2-), and ammonium (NH4+)) and N2O concentrations during the incubation experiments to evaluate the effect of Cu. We have also reported the variation in metal concentrations (Cu, iron(Fe) and manganese (Mn)) and dissolved organic carbon (DOC) concentrations during the incubations. The parameters obtained using a kinetic model to quantitatively report the effect of Cu on nitrogen species conversion in natural aquatic systems are also added in the dataset. The dataset also contains the labile concentration of Cu estimated using a speciation model in MINTEQ. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units.Our study suggests that high concentrations of N2O accumulated in all microcosms lacking Cu amendment except for one stream sediment sample. With Cu added to provide dissolved concentrations at trace levels (10–300 nM), the reduction rate of N2O to N2 in the wetland soils and stream sediments was enhanced. A kinetic model could account for the trends in nitrogen species by combining the reactions for microbial reduction of NO3- to NO2-/N2O/N2 and abiotic reduction of NO2 to nitrogen (N2_. The model revealed that the rate of N2O to N2 conversion increased significantly in the presence of Cu. For riparian wetland soils and stream sediments, the kinetic model also suggested that overall denitrification is driven by abiotic reduction of NO2- in the presence of inorganic electron donors. This study demonstrated that natural aquatic systems containing Cu at concentrations less than or equal to crustal abundances may display incomplete reduction of N2O to N2 that would cause N2O accumulation and release to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Uptake and speciation of trace metal inputs to Wetland Soils from Illinois and South Carolina and Stream Sediments from Tennessee

Metals occur in all ecosystems, although their concentrations vary depending on their natural geologic conditions and surrounding human activities. In addition to metals intrinsically present from the geology of a particular system, metals can enter environmental systems from a wide variety of natural and anthropogenic sources, such as sediment re-suspension, mining operations, industrial processes, agricultural activities, and atmospheric deposition. While metals can be toxic at high concentrations, some metals serve as essential micronutrients for biogeochemical processes. Metal transport and availability in engineered and natural water systems depend on processes of adsorption/desorption, oxidation/reduction, dissolution/precipitation, and ligand complexation. Insights into the speciation of metals and their bioavailability will also help advance understanding of the roles of metals in the biogeochemical cycling of nutrients. We conducted batch experiments under anoxic conditions on soils and sediments collected from three different natural aquatic systems to understand their response to influxes of dissolved Cu, Ni and Zn. While soils and sediments from all sites could strongly bind added trace metals, there were substantial differences in trace metal uptake trends between different sites, especially for Cu. There was no distinct correlation between trace metal uptake and the total organic matter, iron, and sulfur content present in the samples. X-ray absorption spectroscopy indicated that the speciation of the freshly added metals taken up by the solids differs substantially from the speciation of the metals originally present in unamended samples. Cu sulfides dominated speciation at low loadings (1 µmol/g), whereas complexation to thiol groups and formation of metallic Cu governed speciation at high loadings (10 µmol/g). For Ni and Zn, adsorption to mineral surfaces and organic matter governed their speciation in materials from most sites. This study suggests that the background speciation of metals in natural aquatic systems is a poor predictor of the speciation and lability of metals introduced to terrestrial aquatic systems from anthropogenic or natural processes. Our findings imply that geochemical processes controlling trace metal speciation may vary considerably with metal loading in different natural systems. Data are provided for marsh wetland soils at Argonne National Laboratory (Marsh 1 and Marsh 2), riparian wetland soils (Riparian 1 and Riparian 2) in the Tims Branch watershed at Savannah River National Laboratory, and stream bed sediments (Stream 1 and Stream 2) from East Fork Poplar Creek near Oak Ridge National Laboratory. Data package includes the results of trace metal uptake experiments conducted on the selected sites for determining their capacity to immobilize metals under different loadings. XANES spectra for Cu, Ni, ad Zn at different loadings are included in the package. The abundance of different trace metal species obtained using linear combination fitting in ATHENA are also included in the data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for Machado-Silva et al. (2024), "Short-Term Groundwater Level Fluctuations Drive Subsurface Redox Variability"

This dataset contains the analytical data reported in Machado-Silva et al. (2024) as part of the COMPASS-FME project, which seeks to advance a scalable, predictive understanding of the fundamental biogeochemical processes, ecological structure, and ecosystem dynamics that distinguish coastal terrestrial-aquatic interfaces from the purely terrestrial or aquatic systems to which they are coupled. The dataset consists of water quality parameters as well as redox potential, water content, and electrical conductivity. These data were collected in 2022 in Crane Creek (CRC), Portage River (PTR), and Old Woman Creek (OWC). Each of these sites included uplands (UP), transitions (TR), wetland-transition edge (WTE), and wetland (W) zones. The sites represent replicates of the Lake Erie terrestrial-aquatic interface under fluctuating water levels and are located in well-preserved areas with natural or restored marsh and forest cover.This dataset consists of a single data file (Machado_Silva_et_al_2024_EST_data.csv) that is in comma-separated value (CSV) format. No special software is required to read it.This dataset uses the ESS-DIVE Hydrologic Monitoring Reporting Format 1.0.

54 ENVIRONMENTAL SCIENCES↗