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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Pyrogenic Organic Matter Laboratory Experiment: Aerobic Respiration and Geochemistry from Variably Inundated Stream Sediments (v3)

This dataset supports a broader study examining the effects of variable inundation and pyrogenic organic matter on ecosystem respiration. The dataset provides data generated from a laboratory batch experiment investigating the interaction between variable inundation conditions (wet and dry sediment) and pyrogenic organic matter (burned and unburned treatments). The contents include time series dissolved oxygen, sediment geochemistry data, and field metadata (including qualitative information on instream and river corridor characteristics). This data package was originally published in November 2025. It was updated in April 2026 (v2; new and modified files) and May 2026 (v3; modified files). See the change history section in the readme for more details For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) international generic sample number (IGSN) mapping file; (5) readme; (6) field protocol; (7) sample name metadata; (8) an environmental context picture for the dry and inundated sampling locations; and (9) a subfolder with sample data from the sediment incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) gravimetric moisture; (4) partial pressure and production rates of carbon dioxide, methane, and nitrous oxide; (5) field wet sediment mass, dry sediment mass, water mass, and field wet sediment volume in incubation and sediment NPOC/TN vials; (6) methods codes; (7) respiration rates, pH, and temperature from after the incubation, raw time series dissolved oxygen and temperature, and a subfolder containing associated plots and scripts; (8) ions; (9) FTICR-MS methods; and (10) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains the CoreMS processed data and three subfolders, one containing the .xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, or .jpg.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Evaluating Composite Sampling Methods of Bacillus Spores at Low Concentrations

Restoring facility operations after the 2001 Amerithrax attacks took over three months to complete, highlighting the need to reduce remediation time. The most time intensive tasks were environmental sampling and sample analyses. Composite sampling allows disparate samples to be combined, with only a single analysis needed, making it a promising method to reduce response times. We developed a statistical experimental design to test three different composite sampling methods: 1) single medium single pass composite: a single cellulose sponge samples multiple coupons; 2) single medium multi-pass composite: a single cellulose sponge is used to sample multiple coupons; and 3) multi-medium post-sample composite: a single cellulose sponge samples a single surface, and then multiple sponges are combined during sample extraction. Five spore concentrations of Bacillus atrophaeus Nakamura spores were tested; concentrations ranged from 5 to 100 CFU/coupon (0.00775 to 0.155CFU/cm 2 , respectively). Study variables included four clean surface materials (stainless steel, vinyl tile, ceramic tile, and painted wallboard) and three grime coated/dirty materials (stainless steel, vinyl tile, and ceramic tile). Analysis of variance for the clean study showed two significant factors: composite method (p-value < 0.0001) and coupon material (p-value = 0.0008). Recovery efficiency (RE) was higher overall using the post-sample composite (PSC) method compared to single medium composite from both clean and grime coated materials. RE with the PSC method for concentrations tested (10 to 100 CFU/coupon) was similar for ceramic tile, painted wall board, and stainless steel for clean materials. RE was lowest for vinyl tile with both composite methods. Statistical tests for the dirty study showed RE was significantly higher for vinyl and stainless steel materials, but significantly lower for ceramic tile. These results suggest post-sample compositing can be used to reduce sample analysis time when responding to a Bacillus anthracis contamination event of clean or dirty surfaces.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

HadISDH land surface multi-variable humidity and temperature record for climate monitoring

HadISDH.2.0.0 is the first gridded, multi-variable humidity and temperature in situ observations-only climate-data product that is homogenised and annually updated. It provides physically consistent estimates for specific humidity, vapour pressure, relative humidity, dew point temperature, wet bulb temperature, dew point depression and temperature. It is a monthly mean gridded (5° by 5°) product with uncertainty estimates that account for spatio-temporal sampling, climatology calculation, homogenisation and irreducible random measurement effects. It provides a tool for the long-term monitoring of a variety of humidity-related variables which have different impacts and implications for society. It is also useful for climate model evaluation and reanalyses validation. HadISDH.2.0.0 is shown to be in good agreement both with other estimates and with theoretical understanding. The data set is available from 1973 to the present. The theme common to all variables is of a warming world with more water vapour present in the atmosphere. The largest increases in water vapour are found over the tropics and the Mediterranean. Over the tropics and high northern latitudes the surface air over land is becoming more saturated. However, despite increasing water vapour over the mid-latitudes and Mediterranean, the surface air over land is becoming less saturated. These observed features may be due to atmospheric circulation changes, land–sea warming disparities and reduced water availability or changed land surface properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang–Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Simultaneous isotopic analysis of fission product Sr, Mo, and Ru in spent nuclear fuel particles by resonance ionization mass spectrometry

Abstract Fission product Sr, Mo, and Ru isotopes in six 10-μm particles of spent fuel from a pressurized water reactor were analyzed by resonance ionization mass spectrometry (RIMS) and evaluated for utility in nuclear material characterization. Previous measurements on these same samples showed widely varying U, Pu, and Am isotopic compositions owing to the samples’ differing irradiation environments within the reactor. This is also seen in Mo and Ru isotopes, which have the added complication of exsolution from the UO 2 fuel matrix. This variability is a hindrance to interpreting data from a collection of particles with incomplete provenance since it is not always possible to assign particles to the same batch of fuel based on isotopic analyses alone. In contrast, the measured 90 Sr/ 88 Sr ratios were indistinguishable across all samples. Strontium isotopic analysis can therefore be used to connect samples with otherwise disparate isotopic compositions, allowing them to be grouped appropriately for interpretation. Strontium isotopic analysis also provides a robust chronometer for determining the time since fuel irradiation. Because of the very high sensitivity of RIMS, only a small fraction of material in each of the 10 μm samples was consumed, leaving the vast majority still available for other analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Wildfire Mapping in Interior Alaska Using Deep Neural Networks on Imbalanced Datasets

Wildfires are the dominant disturbance impacting many regions in Alaska and is expected to intensify due to climate change. Accurate tracking and quantification of wildfires are important for climate modeling and ecological studies in this region. Remote sensing platforms (e.g., MODIS, Landsat) are an important tool for mapping wildfires in Alaska at varying spatial and temporal scales. Deep neural networks (DNN) have shown superior performance in many classification problems such as high-dimensional remote sensing data. Detection of wildfires is an imbalanced classification problem where one class contains a much smaller or larger sample size and DNNs performance can decline. We take a known weight-selection strategy during DNN training and apply them to MODIS variables (e.g., NDVI, surface reflectance) for a binary classification (i.e., wildfire or no-wildfire) across Alaska during the 2004 wildfire year, which is one of the largest on record. The method splits the input training data into sets, one for training the DNN to update weights and the other that splits into a validation set that is equally balanced between the wildfire and no-wildfire class. The performance is monitored on the validation set to select the weights based on the best validation-loss score. This approach was applied to two sampled datasets, such as where the no-wildfire class can significantly outweigh the wildfire class. The normal DNN training strategy was unable to map wildfires for the highly imbalanced dataset, however, the weight-selection strategy was able to map wildfires very accurately (0.96 recall score for 78,702 wildfire pixels (500×500 m)).

Langford, Zach↗
DOE OSTI2026

Soil nitrogen mineralization rates, nutrient stocks, stable isotopes, and water volumetric measurements across terrestrial-aquatic interfaces from three wetlands at the Tanglewood Biological Station, Alabama

This dataset supports a broader study investigating wetland hydrologic and biogeochemical responses to inundation events. Soil samples were collected across four sampling events along terrestrial-aquatic gradients at three wetland sites located within the Tanglewood Biological Station in Alabama from April 2024 to June 2025. The contents in this data package include soil in-situ nitrogen mineralization rates (measurements of net nitrification, net ammonification, and net mineralization), nutrient stocks (total carbon, total nitrogen, and organic matter), stable isotopes (carbon and nitrogen), and water volumetric measurements (water-filled pore space). Water level data related to each wetland location can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/2530253 (Kirker et al., 2024), related water geochemistry data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3001967 (Forbes et al., 2025), and related surface water sediment chemistry data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3377325 (Molina Serpas et al., 2026). In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata and international generic sample numbers (IGSNs); (4) readme; (5) the field protocol; and (6) a subfolder with sample data. The sample data subfolder contains (1) net nitrification rate, (2) net ammonification rate, (3) areal net mineralization rate, (4) percent organic matter, (5) water-filled pore space, (6) total carbon content, (7) total nitrogen content, (8) stable carbon isotope (delta carbon-13), and (9) stable nitrogen isotope (delta nitrogen-15), and (10) methods codes. All files are .csv or .pdf.

13-C↗
DOE OSTI2025

Temporal Variability in Reservoir Surface Area Is an Important Source of Uncertainty in GHG Emission Estimates

Ebullitive methane (CH 4 ) emissions in lentic ecosystems tend to concentrate at river-lake interfaces and within shallow littoral zones. However, inconsistent definitions of the littoral zone and static representations of the lake or reservoir surface area contribute to major uncertainties in greenhouse gas (GHG) emissions estimates, particularly in reservoirs with large water-level fluctuations. This study examines temporal variation in littoral and total surface areas of US reservoirs and demonstrates how different methods and data sources lead to discrepencies in reservoir GHG emissions at large scales and over time. We also explore variability in remotely sensed water occurrence according to maximum surface area, reservoir purposes, and hydrologic regions. Notably, the largest relative variability in surface area is exhibited by small reservoirs with a maximum surface area <1 km 2 and non-hydroelectric reservoirs. Additionally, we use a case study of measured CH 4 emissions from the southeastern United States (Douglas Reservoir) to illustrate the effects of varying surface area on reservoir-wide GHG estimates. Upscaled CH 4 emissions in Douglas Reservoir differed by nearly two-fold depending on the source of total surface area data and whether estimates accounted for seasonal fluctuations in surface area. During seasonal drawdown in Douglas Reservoir, relative littoral area varies non-linearly; periods of lower pool elevation (and thus larger relative littoral area) likely contribute disproportionately high CH 4 emission rates compared to the commonly sampled summer season when water levels are at full-pool elevation. Improved GHG monitoring and upscaling techniques require accounting for temporal variability in reservoir surface extent and littoral area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Report on Status of Shipment of High Fluence Austenitic Steel Samples for Characterization and Stress Corrosion Crack Testing

The goal of the Mechanisms of Irradiation Assisted Stress Corrosion Cracking (IASCC) task in the LWRS Program is to conduct experimental research into understanding how multiple variables influence the crack initiation and crack growth in materials subjected to stress under corrosive conditions. This includes understanding the influences of alloy composition, radiation condition, water chemistry and metallurgical starting condition (i.e., previous cold work or heat treatments and the resulting microstructure) has on the behavior of materials. Testing involves crack initiation and growth testing on irradiated specimens of single-variable alloys in simulated Light Water Reactor (LWR) environments, tensile testing, hardness testing, microstructural and microchemical analysis, and detailed efforts to characterize localized deformation. Combined, these single-variable experiments will provide mechanistic understanding that can be used to identify key operational variables to mitigate or control IASCC, optimize inspection and maintenance schedules to the most susceptible materials/locations, and, in the long-term, design IASCC-resistant materials. In support of this research, efforts are currently underway to arrange shipment of “free” high fluence austenitic alloys available through Électricité de France (EDF) for post irradiation testing at the Oak Ridge National Laboratory (ORNL) and IASCC testing at the University of Michigan. These high fluence materials range in damage values from 45 to 125 displacements per atom (dpa). The samples identified for transport to the United States, which include nine, no-cost, 304, 308 and 316 tensile bars, were relocated from the Research Institute of Atomic Reactors (RIAR) in Dimitrovgrad, Ulyanovsk Oblast, Russia, and received at the Halden Reactor in Halden, Norway, on August 23, 2016. ORNL has been notified that a significant amount of work is required to prepare the samples for further shipment to Oak Ridge, Tennessee. The preliminary work for sample shipment between Halden and Oak Ridge includes fabrication of an inner cask sample container, decontamination and preparation of a Type A container, preparation of new activity calculations, all necessary paperwork, and handling. ORNL will continue to work to track progress of sample preparation and shipment status, and to work toward an agreement that covers material shipping costs between the Halden Reactor and the Oak Ridge National Laboratory.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Characterization of the VVV Survey RR Lyrae Population across the Southern Galactic Plane

Deep near-IR images from the VISTA Variables in the Vía Láctea (VVV) Survey were used to search for RR Lyrae stars in the Southern Galactic plane. A sizable sample of 404 RR Lyrae of type ab stars was identified across a thin slice of the fourth Galactic quadrant (295° < ℓ < 350°, −2.°24 < b < −1.°05). The sample’s distance distribution exhibits a maximum density that occurs at the bulge tangent point, which implies that this primarily Oosterhoff type I population of RRab stars does not trace the bar delineated by their red clump counterparts. The bulge RR Lyrae population does not extend beyond ℓ ∼ 340°, and the sample’s spatial distribution presents evidence of density enhancements and substructure that warrants further investigation. Indeed, the sample may be employed to evaluate Galactic evolution models, and is particularly lucrative since half of the discovered RR Lyrae are within reach of Gaia astrometric observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

PERIODIC AND APERIODIC VARIABILITY IN THE MOLECULAR CLOUD ρ OPHIUCHUS

Presented are the results of a near-IR photometric survey of 1678 stars in the direction of the ρ Ophiuchus (ρ Oph) star forming region using data from the 2MASS Calibration Database. For each target in this sample, up to 1584 individual J-, H-, and K{sub s} -band photometric measurements with a cadence of ∼1 day are obtained over three observing seasons spanning ∼2.5 yr; it is the most intensive survey of stars in this region to date. This survey identifies 101 variable stars with ΔK{sub s} -band amplitudes from 0.044 to 2.31 mag and Δ(J – K{sub s} ) color amplitudes ranging from 0.053 to 1.47 mag. Of the 72 young ρ Oph star cluster members included in this survey, 79% are variable; in addition, 22 variable stars are identified as candidate members. Based on the temporal behavior of the K{sub s} time-series, the variability is distinguished as either periodic, long time-scale or irregular. This temporal behavior coupled with the behavior of stellar colors is used to assign a dominant variability mechanism. A new period-searching algorithm finds periodic signals in 32 variable stars with periods between 0.49 to 92 days. The chief mechanism driving the periodic variability for 18 stars is rotational modulation of cool starspots while 3 periodically vary due to accretion-induced hot spots. The time-series for six variable stars contains discrete periodic ''eclipse-like'' features with periods ranging from 3 to 8 days. These features may be asymmetries in the circumstellar disk, potentially sustained or driven by a proto-planet at or near the co-rotation radius. Aperiodic, long time-scale variations in stellar flux are identified in the time-series for 31 variable stars with time-scales ranging from 64 to 790 days. The chief mechanism driving long time-scale variability is variable extinction or mass accretion rates. The majority of the variable stars (40) exhibit sporadic, aperiodic variability over no discernable time-scale. No chief variability mechanism could be identified for these variable stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Selection of Spectral Variables and Improvement of the Accuracy of Calibration of Temperature by Projection onto Latent Structures Using the Fluorescence Spectra of Yb{sup 3+}:CaF{sub 2}

The efficiency of interval methods for selecting variables and the divisive method of interval optimization by a genetic algorithm is considered with the purpose to increase the accuracy of temperature calibration by projection onto latent structures. The fluorescence spectra of Yb{sup 3+}:CaF{sub 2} recorded in the 880–1120 nm band with a resolution of approximately 0.2 nm in the temperature range from 66 to 150°C in 2°C increments are used as an example. The best result for the root-mean-square error of temperature prediction in the test sample (0.45°C) was obtained by interval projection onto latent structures by a combination of moving windows. The use of methods for selecting spectral variables improved more than two times the accuracy of temperature calibration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Analysis of Lung Tumor Motion in a Large Sample: Patterns and Factors Influencing Precise Delineation of Internal Target Volume

Purpose/Objective: To evaluate lung tumor motion during respiration and to describe factors affecting the range and variability of motion in patients treated with stereotactic ablative radiation therapy. Methods and Materials: Log file analysis from online respiratory tumor tracking was performed in 145 patients. Geometric tumor location in the lungs, tumor volume and origin (primary or metastatic), sex, and tumor motion amplitudes in the superior-inferior (SI), latero-lateral (LL), and anterior-posterior (AP) directions were recorded. Tumor motion variability during treatment was described using intrafraction/interfraction amplitude variability and tumor motion baseline changes. Tumor movement dependent on the tumor volume, position and origin, and sex were evaluated using statistical regression and correlation analysis. Results: After analysis of >500 hours of data, the highest rates of motion amplitudes, intrafraction/interfraction variation, and tumor baseline changes were in the SI direction (6.0 ± 2.2 mm, 2.2 ± 1.8 mm, 1.1 ± 0.9 mm, and −0.1 ± 2.6 mm). The mean motion amplitudes in the lower/upper geometric halves of the lungs were significantly different (P<.001). Motion amplitudes >15 mm were observed only in the lower geometric quarter of the lungs. Higher tumor motion amplitudes generated higher intrafraction variations (R=.86, P<.001). Interfraction variations and baseline changes >3 mm indicated tumors contacting mediastinal structures or parietal pleura. On univariate analysis, neither sex nor tumor origin (primary vs metastatic) was an independent predictive factor of different movement patterns. Metastatic lesions in women, but not men, showed significantly higher mean amplitudes (P=.03) and variability (primary, 2.7 mm; metastatic, 4.9 mm; P=.002) than primary tumors. Conclusion: Online tracking showed significant irregularities in lung tumor movement during respiration. Motion amplitude was significantly lower in upper lobe tumors; higher interfraction amplitude variability indicated tumors in contact with mediastinal structures, although adhesion to parietal pleura did not necessarily reduce tumor motion amplitudes. The most variable lung tumors were metastatic lesions in women.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Global sensitivity analysis in stochastic simulators of uncertain reaction networks

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol’s decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. Here, a sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

American Gut: an Open Platform for Citizen Science Microbiome Research

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Mercury concentrations in Pacific lamprey ( Entosphenus tridentatus ) and sediments in the Columbia River basin: Mercury in Columbia River Pacific lamprey

We investigated mercury accumulation in Pacific lamprey and sediments in the Columbia River basin. Mercury concentrations in larval lamprey differed significantly among sample locations (P < 0.001) and were correlated with concentrations in sediments (r 2 = 0.83), whereas adult concentrations were highly variable (range 0.1–9.5 µg/g) and unrelated to holding time after collection. The results suggest that Pacific lamprey in the Columbia River basin may be exposed to mercury levels that have adverse ecological effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Diel variation in CO 2 flux is substantial in many lakes

Lakes play a significant role in the global carbon cycle, acting as sources and sinks of carbon dioxide (CO 2 ). In situ measurements of CO 2 flux (FCO 2 ) from lakes have generally been collected during daylight, despite indications of significant diel variability. This introduces bias when scaling up to whole-lake annual aquatic carbon budgets. We conducted an international sampling program to ascertain the extent of diel variation in FCO 2 across lakes. We sampled 21 lakes over 41 campaigns and measured FCO 2 at 4-h intervals over a full diel cycle. Rates of FCO 2 ranged from −3.16 to 4.39 mmol m −2 h −1 . Integrated over a day, FCO 2 ranged from −381.68 to 878.49 mg C m −2 d −1 (mean = 76.54) across campaigns. We identified three characteristic diel patterns in FCO 2 related to trophic status and show that for half of the campaigns, daily flux estimates were biased by > 50% if based on a single (daytime) measurement.

de Eyto, Elvira [Marine Institute, Mayo (Ireland)]↗