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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

TOI–757 b: an eccentric transiting mini–Neptune on a 17.5–d orbit

ABSTRACT We report the spectroscopic confirmation and fundamental properties of TOI$-$757 b, a mini$-$Neptune on a 17.5$-$d orbit transiting a bright star ($V\, =\, 9.7$ mag) discovered by the TESS mission. We acquired high$-$precision radial velocity measurements with the HARPS, ESPRESSO, and PFS spectrographs to confirm the planet detection and determine its mass. We also acquired space$-$borne transit photometry with the CHEOPS space telescope to place stronger constraints on the planet radius, supported with ground$-$based LCOGT photometry. WASP and KELT photometry were used to help constrain the stellar rotation period. We also determined the fundamental parameters of the host star. We find that TOI$-$757 b has a radius of $R_{\mathrm{p}} = 2.5 \pm 0.1 R_{\oplus }$ and a mass of $M_{\mathrm{p}} = 10.5^{+2.2}_{-2.1} M_{\oplus }$, implying a bulk density of $\rho _{\text{p}} = 3.6 \pm 0.8$ g cm$^{-3}$. Our internal composition modelling was unable to constrain the composition of TOI$-$757 b, highlighting the importance of atmospheric observations for the system. We also find the planet to be highly eccentric with e = 0.39$^{+0.08}_{-0.07}$, making it one of the very few highly eccentric planets among precisely characterized mini$-$Neptunes. Based on comparisons to other similar eccentric systems, we find a likely scenario for TOI$-$757 b’s formation to be high eccentricity migration due to a distant outer companion. We additionally propose the possibility of a more intrinsic explanation for the high eccentricity due to star$-$star interactions during the earlier epoch of the Galactic disc formation, given the low metallicity and older age of TOI$-$757.

Alqasim, A. (ORCID:0000000151025505)↗
DOE OSTI2019

NGTS-6b: an ultrashort period hot-Jupiter orbiting an old K dwarf

ABSTRACT We report the discovery of a new ultrashort period hot Jupiter from the Next Generation Transit Survey. NGTS-6b orbits its star with a period of 21.17 h, and has a mass and radius of $1.330^{+0.024}_{-0.028}$MJ and $1.271^{+0.197}_{-0.188}$RJ, respectively, returning a planetary bulk density of $0.711^{+0.214}_{-0.136}$ g cm−3. Conforming to the currently known small population of ultrashort period hot Jupiters, the planet appears to orbit a metal-rich star ([Fe/H] = +0.11 ± 0.09 dex). Photoevaporation models suggest the planet should have lost 5 per cent of its gaseous atmosphere over the course of the 9.6 Gyr of evolution of the system. NGTS-6b adds to the small, but growing list of ultrashort period gas giant planets, and will help us to understand the dominant formation and evolutionary mechanisms that govern this population.

Vines, Jose I.↗
DOE OSTI2018

Hydrodynamic disassembly and expansion of electron-beam-heated warm dense copper

Cu foils, 200 μm in thickness, were heated in two stages by a ~100-ns-long monoenergetic electron bunch at 19.8 MeV and a current of 1.7 kA (8.5 × 10 14 e - ) in a 2-mm-spot to T e ~1 eV. After 45 ns of isochoric heating, the pressure in the foil builds up to >20 GPa (200 kbar), it begins to hydrodynamically disassemble, and a velocity spread is measured. Near the end of the electron pulse, the 1550 nm probe is cut off or absorbed. Photonic Doppler velocimetry measurements were made to quantify the expansion velocity, hydrodynamic disassembly time, and pressure of the foil prior to cutoff. Measurements indicate foil motion begins the instant electrons pass through the foil and continues until the particle velocity approaches the ambient sound velocity of Cu and the bulk density exceeds the critical density of the probe. Finally, once the density of the plasma drops below the critical threshold and begins reflecting again, an expansion velocity of the classical plasma is also measured, similar to the point-source solution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Climate, soil and plant functional types as drivers of global fine-root trait variation

Ecosystem functioning relies heavily on below-ground processes, which are largely regulated by plant fine-roots and their functional traits. However, our knowledge of fine-root trait distribution relies to date on local- and regional-scale studies with limited numbers of species, growth forms and environmental variation. We compiled a world-wide fine-root trait dataset, featuring 1115 species from contrasting climatic areas, phylogeny and growth forms to test a series of hypotheses pertaining to the influence of plant functional types, soil and climate variables, and the degree of manipulation of plant growing conditions on species fine-root trait variation. Most particularly, we tested the competing hypotheses that fine-root traits typical of faster return on investment would be most strongly associated with conditions of limiting versus favourable soil resource availability. We accounted for both data source and species phylogenetic relatedness. We demonstrate that: (i) Climate conditions promoting soil fertility relate negatively to fine-root traits favouring fast soil resource acquisition, with a particularly strong positive effect of temperature on fine-root diameter and negative effect on specific root length (SRL), and a negative effect of rainfall on root nitrogen concentration; (ii) Soil bulk density strongly influences species fine-root morphology, by favouring thicker, denser fine-roots; (iii) Fine-roots from herbaceous species are on average finer and have higher SRL than those of woody species, and N 2 -fixing capacity positively relates to root nitrogen; and (iv) Plants growing in pots have higher SRL than those grown in the field. Synthesis. This study reveals both the large variation in fine-root traits encountered globally and the relevance of several key plant functional types and soil and climate variables for explaining a substantial part of this variation. Climate, particularly temperature, and plant functional types were the two strongest predictors of fine-root trait variation. High trait variation occurred at local scales, suggesting that wide-ranging below-ground resource economics strategies are viable within most climatic areas and soil conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A 13‐Year Record Indicates Differences in the Duration and Depth of Soil Carbon Accrual Among Potential Bioenergy Crops

Six years after replacing a maize/soybean cropping system, perennial grasses miscanthus (Miscanthus × giganteus) and switchgrass (Panicum virgatum), and a 28-species restored prairie increased particulate organic carbon in surface soils without increasing soil organic carbon (SOC). To resolve potential changes in the quantity and distribution of SOC, soils were resampled after seven to thirteen years to measure bulk density, carbon (C) content, and stable C isotopes to a depth of 1 m. SOC stocks increased between 1.75 and 2.5 Mg ha −1 year −1 in all perennial crops between 2008 and 2016 (nine growing seasons). Despite relatively low litter inputs and belowground biomass, the highest rate of SOC accrual was in restored prairie (2.5 Mg ha −1 year −1 ), followed by miscanthus (2.0 Mg ha −1 year −1 ) and switchgrass (1.75 Mg ha −1 year −1 ). The change in SOC in maize/soybean was not significant. After 2016, total SOC decreased in maize/soybean and miscanthus, resulting in slower overall rates of SOC accumulation over the full sampling period for miscanthus (0.8 Mg ha −1 year −1 ). The rate of SOC accumulation was greatest below 50 cm depth for restored prairie and switchgrass but in the top 10 cm for miscanthus. Stable isotope analysis showed 13 C enrichment in all depths of switchgrass soils, an indication of new organic C accumulation, but mixed results in all other crops. Planting perennial crops on land formerly in an annual maize/soybean cropping system can slow or reverse soil carbon losses, with the greatest increases in SOC from species-rich prairie.

agriculture↗
DOE OSTI2021

Flexural strength of a conventionally processed and additively manufactured debased 94% alumina

Mechanical strength of a 94 wt% debased alumina was measured using ASTM-C1161 specimens fabricated via conventional and lithography-based ceramic manufacturing (LCM) methods. The effects of build orientation and a 1500°C wet hydrogen fire added to the LCM firing sequence on strength were evaluated. Additionally, a Weibull fit to the conventional flexural specimen data yielded 20 and 356 MPa for the modulus and characteristic strength, respectively. Weibull fits of the data from the LCM specimens yielded moduli between 7.5 and 11.3 and characteristics strengths between 333 and 339 MPa. A Weibull fit to data from LCM specimens subjected to the wet hydrogen fire yielded 14.2 and 376 MPa for the modulus and characteristic strength, respectively. The 95% confidence intervals for all Weibull parameters are reported. Average Archimedes bulk densities of LCM and conventional specimens were 3.732 and 3.730 g/cm 3 , respectively. Process dependent differences in surface morphology were observed in scanning electron microscope (SEM) images of specimen surfaces. SEM images of LCM specimen cross-sections showed alumina grain texture dependent on build direction, but no evidence of porosity concentrated in planes between printed layers. Fracture surfaces of LCM and conventionally processed specimens revealed hackle lines and mirror regions indicative of fracture initiation at the sample surface rather than the interior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

On the bulk compaction of brittle granular materials, part I: SeS analysis of axial compression to 4000 MPa

The bulk compaction of granular materials has been studied for decades to interpret and manage responses for soils and powder-based component fabrication, and geophysical, celestial, and ballistic impact. Their bulk or macroscopic compaction response is limited by what occurs at the granular or microstructural scale. Motivation existed to more closely examine that association specific to granular brittle materials (e.g., ceramics and glasses). That examination is offered in a series of three companion papers where Part I describes a new supplemental analysis adopted to bulk compaction response involving relatively high compaction stresses (4000 MPa). Bulk compactions of vitreous silicates and crystalline quartzes were interpreted in three ways, including that of a new analysis that considers the product of void ratio (e) and stress (S) as a function of S, hereafter referred to as “SeS analysis”. In conclusion, the SeS analysis was found to be an informative supplement to conventional bulk compaction analyses because it provides more consistent higher sensitivity for the identification of bulk density rate increase with increasing compaction (softening); a rate increase that arises from the cumulative effect of the onsets and progression of compaction-induced yielding, fracture or comminution, densification, phase change, or combinations thereof occurring at the granular or microstructural scale.

compaction↗
DOE OSTI2016

Ab initio Modeling of the Electronic Structures and Physical Properties of a‐Si 1− x Ge x O 2 Glass ( x = 0 to 1)

The amorphous silica (a‐SiO 2 ) and germania (a‐GeO 2 ) have a wide range of applications in glass industry. Based on a previously constructed near‐perfect continuous random network model with 1296 atoms and periodic boundary conditions, we extend our study to amorphous Si 1− x G e x O 2 models of homogeneous random substitution of Si by Ge with x ranging from 0 to 1. We have calculated the structural, electronic, mechanical, and optical properties for the series by using the first‐principles density functional theory methods. The x ‐dependence of the variations in the properties is analyzed and critically compared with available experimental data. The mass density, volume, total bond order density, bulk mechanical properties, and refractive index are found to vary linearly as a function of x . For x = 0.5, we have also constructed six different kinds of particle immersion models to test the effect of inclusion of spherical particles of one glass of different sizes in the medium of the other glass on their physical properties. It is shown that particle sizes do affect the properties of particle immersion. Our calculations provide deep insight on the properties of mixture and nanocomposites of a‐SiO 2 and a‐GeO 2 glasses.

Baral, Khagendra↗
DOE OSTI2014

SU-E-J-14: A Novel Approach to Evaluate the Dosimetric Effect of Rectal Variation During Image Guided Prostate Radiotherapy

Purpose: Deformable registration establishes the spatial correspondence back to the reference image in order to accumulate dose. However, in prostate radiotherapy the changing shape and volume of the rectum present a challenge to accurate deformable registration and consequently calculation of delivered dose. We explored an alternative approach to calculating accumulated dose to the rectum, independent of deformable registration. Methods: This study was performed on three patients who received online image-guided radiotherapy (IGRT) with daily CBCT (XVI-system,Elekta) and target localization using intraprostatic fiducials. On each CBCT, the rectum was manually contoured and bulk density assignments were made allowing dose to be calculated for each fraction. Dose-surface maps (DSM) were generated (MATLAB,Mathworks,Natick,MA) by considering the rectum as a cylinder and sampling the dose at 21-equispaced points on each CT slice. The cylinder was “cut” at the posterior-most position on each CT and unfolded to generate a DSM. These were normalised in the longitudinal direction by interpolation creating maps of 21×21 pixels. A DSM was produced for each CBCT and the dose was accumulated. Results: The mean accumulated delivered rectal surface dose was on average 7.5(+/−3.5)% lower than the planned dose. The dose difference maps consistently show that the greatest variation in dose between planned and delivered dose is away from where the rectal surface is adjacent to the prostate. Conclusion: Estimation of dose accumulation using DSM provides an alternative method for determining actual delivered dose to the rectum. The dose difference is greatest in areas away from the region where the rectal surface abuts the prostate, the region where set-up is verified. The change in size and shape of the rectum was shown to resultin a change in the accumulated dose compared to the planned dose and this will have an impact on determining the relationships between dose delivered and toxicity. We acknowledge funding from CRUK and acknowledge NHS funding to the NIHR Biomedical Research Centre for Cancer. Patients were treated within the CHHiP IGRT sub-study (CRUK/06/016, ISRCTN:97182923) funded by CRUK. RayStation was used under an evaluation agreement with RaySearch Laboratories AB.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Exploring limitations in the induced polarization versus surface conductivity relationship in the case of wetland soils

Recent induced polarization studies suggest that the real part of surface conductivity (σ' surf ) scales linearly with the imaginary conductivity (σ'' = σ'' surf ) or normalized chargeability (Mn) for a range of soil types. The coefficients of this relationship l and l_Mn ( l = σ''/σ' surf or l_Mn = Mn/σ' surf ) allow the separation of the surface and electrolytic conductivities from the bulk conductivity. However, the dependence of these constants on varying soil physicochemical properties, including under unsaturated conditions, is yet to be assessed. Using estimates of σ' surf from 18 undisturbed soil samples from a restored wetland and σ'' measured over a frequency range of 0.01 Hz to 10 kHz, the σ' surf and σ'' were compared with the laboratory measurements of soil properties. Also, l and l_Mn were calculated for each soil sample and regressed them against the soil properties. We find an apparent dependence of l on soil texture, bulk density, organic matter, and moisture contents, with coefficients of determination (R 2 ) ranging from 0.5 to 0.65 at low frequencies (e.g., 1 Hz) but not at high frequencies (e.g., 936 Hz). This dependence of l on soil texture results from the insensitivity of σ'' at low frequency to σ' surf and, by implication, to the soil properties controlling σ' surf . In contrast, l_Mn indicates no correlation with the soil properties because Mn is linearly correlated with σ' surf and correlated with the soil properties controlling σ' surf . Finally, our results call for caution on the application of σ'' at a single frequency as a proxy of σ' surf because σ'' is not necessarily correlated with σ' surf across all soil types. Although using l_Mn derived from multifrequency measurements overcomes this limitation, field acquisition of spectral information (e.g., up to 1000 Hz) remains a challenge.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Application of a new hybrid particle swarm optimization-mixed kernels function-based support vector machine model for reservoir porosity prediction: A case study in Jacksonburg-Stringtown oil field, West Virginia, USA

Porosity is a fundamental property that characterizes the storage capability of fluid and gas-bearing formations in a reservoir. An accurate porosity value can be measured from core samples in the laboratory; however, core analysis is expensive and time consuming. Well-log data can be used to calculate porosity, but the availability of log suites is often limited in mature fields. Therefore, robust porosity prediction requires integration of core-measured porosity with available well-log suites to control for changes in lithology and fluid content. A support vector machine (SVM) model with mixed kernel function (MKF) is used to construct the relationship between limited conventional well-log suites and sparse core data. Porosity is the desired output, and two conventional well-log responses (gamma ray [GR] and bulk density) and three well-log-derived parameters (the slope of GR, the slope of density, and [Formula: see text]) are input parameters. A global stochastic searching algorithm, particle swarm optimization (PSO), is applied to improve the efficiency of locating the appropriate values of five control parameters in MKF-SVM model. The results of SVM with different traditional kernel functions were compared, and the MKF-SVM model provided an improvement over the traditional SVM model. To confirm the advantage of the hybrid PSO-MKF-SVM model, the results from three models: (1) radial basis function (RBF)-based least-squares SVM, (2) multilayer perceptron artificial neural network (ANN), and (3) RBF ANN, are compared with the result of the hybrid PSO-MKF-SVM model. The results indicate that the hybrid PSO-MKF-SVM model improves porosity prediction with the highest correlation coefficient ([Formula: see text] of 0.9560), the highest coefficient of determination ([Formula: see text] of 0.9140), the lowest root-mean-square error (1.6505), average absolute error value (1.4050), and maximum absolute error (2.717).

Geochemistry & Geophysics↗
DOE OSTI2021

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗
DOE OSTI2024

Epoxy Coating of Biofiber: An Effective Modifier of Biofiber Physical and Flow Properties for Improved Tensile Behavior of Biofiber-Reinforced Biocomposite

Biocomposites combine renewable, plant-based fibers with degradable polymers and are an attractive option for sustainable, lightweight, and cost-effective materials with a low carbon footprint, especially for large-scale additive manufacturing. One of the major challenges in the widespread adoption of biocomposites is that their mechanical performance is significantly inferior to that of synthetic composites. Surface treatment is a common and effective technique to improve the mechanical properties of the biofibers used in biocomposites. This study aims to investigate the physical and flow properties of surface-treated biofibers, as well as the tensile properties of their PLA-based biocomposite, to gain insights into how surface treatment changes the fiber‘s characteristics and biocomposite‘s mechanical properties. Surface treatment was created using a two-component epoxy system by reacting poly(bisphenol A-co-epichlorohydrin) glycidyl end-capped (PBG) and dicyandiamide (DICY). The treatment was tested on two different biofibers (loblolly pine and corn stover fibers) with three different PBG/DICY molar ratios (0.25, 0.5, and 2). Results showed that surface-treated fibers improved the tensile strength and Young‘s modulus of the biocomposites. Loblolly pine biocomposites from fibers treated with a PBG/DICY ratio of 0.25 exhibited the best tensile properties. The surface treatment resulted in a more loosely dispersed fiber bulk structure, as evidenced by less fiber agglomeration into smaller particle sizes, higher fiber sphericity, and lower loose bulk density. This can enhance stress distribution and the overall mechanical performance of the biocomposites. Additionally, surface-treated fibers exhibited better dynamic flow properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Intraspecific variability in plant and soil chemical properties in a common garden plantation of the energy crop Populus

Optimizing crops for synergistic soil carbon (C) sequestration can enhance CO 2 removal in food and bioenergy production systems. Yet, in bioenergy systems, we lack an understanding of how intraspecies variation in plant traits correlates with variation in soil biogeochemistry. This knowledge gap is exacerbated by both the heterogeneity and difficulty of measuring belowground traits. Here, we provide initial observations of C and nutrients in soil and root and stem tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes—established for aboveground biomass-to-biofuels research. Our goal was to explore the value of such field sites for evaluating genotype-specific effects on soil C, which ultimately informs the potential for optimizing bioenergy systems for both aboveground productivity and belowground C storage. To do this, we investigated variation in chemical traits at the scale of individual trees and genotypes and we explored correlations among stem, root, and soil samples. We observed substantial variation in soil chemical properties at the scale of individual trees and specific genotypes. While correlations among elements were observed both within and among sample types (soil, stem, root), above-belowground correlations were generally poor. We did not observe genotype-specific patterns in soil C in the top 10 cm, but we did observe genotype associations with soil acid-base chemistry (soil pH and base cations) and bulk density. Finally, a specific phenotype of interest (high vs low lignin) was unrelated to soil biogeochemistry. Our pilot study supports the usefulness of decade-old, genetically-variable, Populus bioenergy field test plots for understanding plant genotype effects on soil properties. Finally, this study contributes to the advancement of sampling methods and baseline data for Populus systems in the Pacific Northwest, USA. Further species- and region-specific efforts will enhance C predictability across scales in bioenergy systems and, ultimately, accelerate the identification of genotypes that optimize yield and carbon storage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Depth and elevation of floodplain fine sediment along the East River near Crested Butte, Colorado measured in 2016 and 2017

The depth of floodplain fine sediment was measured at 1,601 points along the East River near Crested Butte, Colorado spanning a study reach approximately 800 m in length in 2016 and 2017. These depths are being used to estimate the volume of floodplain sediment present along the study reach, converted into mass of sediment using bulk density measurements, and finally used to estimate the mass of organic carbon stored in the floodplain based on elemental analysis of percent organic carbon content. Recorded depths include a minimum of 1 cm, a median of 56 cm, a maximum of 175 cm, and a mean with standard deviation of 61 ± 34 cm. This data include a csv file of the coordinates for each point in NAD 83 UTM zone 13, measured sediment depths, distance from the river channel active during 2015 measured using geographic information systems, the elevation of the floodplain surface derived from 0.5-m resolution lidar, and the elevation of the underlying gravel/bedrock surface, and in some cases the distance from the active channel measured in the field along the sampling transect. Also included is an ESRI ArcMap shapefile of the measurement points complete with the data listed above.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Unsaturated and Saturated Hydraulic Parameters of Soils at the East River Watershed, Colorado Calculated using the Pedotransfer Function Method.

The purpose of the data package is to present the results of calculations of the following unsaturated-saturated hydraulic parameters of soils of the East River Watershed, Colorado: fully saturated water content (Qs), residual saturation (Qr), van genuchten parameters alpha and n, field capacity (FC), and saturated hydraulic conductivity (Ks). Calculations were conducted for the following soil texture types: sandy_loam, loam, silty_clay_loam, clay_loam, silt loam; the particle size distribution included the percentage of sand, silt, clay, and the bulk density (BD) of soils. Calculations were conducted for the following areas- Lower_Subalpine (6 samples),- Lower_Montane_lower_hillslope (7 samples),- Floodplain_at_base_of_lower_montane_hillslope, (11 samples),- PLM-0 (10 samples),- PLM-1 (10 samples), and - PLM-3 (13 samples)Calculations were conducted using the Pedotransfer Function Method developed by Tóth et al. (2014) with the application of the code ”euptf” in Rstudio. The data are being summarized in the Excel file ”Unsaturated_Saturated_Hydraulic_Parameters_PTF_calculated_EASt_EIver.xls" including two worksheets:“full_data_EAST_RIVER” which includes (a) the input data used for calculations, the soil texture triangle, and the plots of the water retention curves and unsaturated hydraulic conductivity for several types of soil texture, and (b) the summary table with the averaged parameters for each area. The the texture triangle was plotted using the Rstudio "soiltexture." Microsoft Excel software is required to open the Excel file. The metadata and a list of references to the Rstudio libraries used for calculations and data visualization are giving in the Word Readme file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Nutrient and carbon concentrations in dated soil cores at US-OWC Ameriflux wetland site (OWC NERR)

Soil cores were sampled at the Old Woman Creek (OWC) National Estuarine Research Reserve at the south shore of Lake Erie, near Huron, Ohio, USA. OWC is a temperate mineral soil marsh. We dated the soil cores using lead isotope analysis and measured the concentrations of carbon and nutrients (nitrogen, phosphorus) throughout the core depths. We analyzed 36 cores, sampled along three transects at areas of the wetland with different hydrological regimes. Each transect included three coring sites at different water depth categories (shallow, intermediate deep) with four core samples per coring site. The data can be used to determine the carbon sequestration rates and nutrient accumulation rates, at multiple locations throughout OWC wetland.Dataset, in csv format, with data variables in columns, and different cores and core depths slices in rows, includes results from 36 sediment cores (0-30 cm depth) taken at 9 locations (4 replicates at each location) along 3 gradients of water depth (shallow, intermediate, deep), each at a different hydrologic location (outflow, backflow, middle). At each depth slice within a core, we provide depth, date (using 210Pb), bulk density, and the concentrations of carbon, nitrogen, phosphorus, d13C, and d15N.

54 ENVIRONMENTAL SCIENCES↗