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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

SPRUCE Sphagnum Growth and Photosynthesis Responses to Shading Treatments, 2021

This dataset reports growth, water content, nitrogen concentration, and photosynthesis of Sphagnum grown under shade cloth of different density in replicated plots adjacent to the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental study plots located in the S1-Bog. Data are reported for May to October 2021. Investigations were instigated from questions arising in the SPRUCE experiment where the Sphagnum-shrub-spruce/larch ecosystem is exposed to air and peat warming in combination with elevated atmospheric CO2. SPRUCE is located at the 8.1-ha S1 Bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Thirty plots (35 × 35 cm) were established in May, 2021, in three blocks on unused large plots on the S-1 bog. Data are reported for growth of Sphagnum angustifolium/fallax and S. divinum growing in plastic columns within the shade plots. Growth is reported as dry mass of new tissue measured when the columns were harvested in October 2021. Additional measurements in the final harvest datasetinclude Sphagnum water content, new stem length, mass per unit length, and nitrogen content. Stem extension was measured periodically during the summer and reported in a separate datasetas stem length. Photosynthesis of Sphagnum angustifolium/fallax samples from hollows under low and high shade was measured in the laboratory. Responses of sphagnum to shading are important for understanding the future of peatland systems under the encroachment of shrubs and other woody plant species. This dataset contains three data files in comma-separated values (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma-separated values (.csv) format and a user guide in PDF (*.pdf) format.

carbon dioxide flux↗
DOE OSTI2020

Modeling the Effects of Global Change on Ecosystem Processes in a Tropical Rainforest

Ongoing land-use change and climate change in wet tropical forests can potentially drive shifts in tree species composition, representing a change in individual species within a functional group, tropical evergreen trees. The impacts on the global carbon cycle are potentially large, but unclear. We explored the differential effects of species within this functional group, in comparison with the effects of climate change, using the Century model as a research tool. Simulating effects of individual tree species on biome-level biogeochemical cycles constituted a novel application for Century. Background and Objectives: A unique, long-term, replicated field experiment containing five evergreen tree species in monodominant stands under similar environmental conditions in a Costa Rican wet forest provided data for model evaluation. Our objectives were to gain insights about this forest’s biogeochemical cycles and effects of tree species within this functional group, in comparison with climate change. Materials and Methods: We calibrated Century, using long-term meteorological, soil, and plant data from the field-based experiment. In modeling experiments, we evaluated effects on forest biogeochemistry of eight plant traits that were both observed and modeled. Climate-change simulation experiments represented two climate-change aspects observed in this region. Results: Model calibration revealed that unmodeled soil processes would be required to sustain observed P budgets. In species-traits experiments, three separate plant traits (leaf death rate, leaf C:N, and allocation to fine roots) resulted in modeled biomass C stock changes of >50%, compared with a maximum 21% change in the climate-change experiments. Conclusions: Modeled ecosystem properties and processes in Century were sensitive to changes in plant traits and nutrient limitations to productivity. Realistic model output was attainable for some species, but unusual plant traits thwarted predictions for one species. Including more plant traits and soil processes could increase realism, but less-complex models provide an accessible means for exploring plant-soil-atmosphere interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

NGEE Arctic Plant Traits: Fine Roots, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

Soil cores were collected from twelve vegetation biomass plots at the Kougarok hillslope in late July of 2016. The sampled plots were located across six ecotypes present at this site (n=2 replicates per ecotype). Soil cores were separated into depth intervals in the field and frozen for transport to Oak Ridge National Laboratory. Data package contains one *.csv and one *.pdf.Laboratory sample processing of these soils generated depth-specific data on soil properties as well as fine root biomass, length, %C, %N, delta13C, and delta15N. Only live fine roots were analyzed. Fine roots were not separated by species or plant functional type.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Strengths and Limitations of 16S rRNA Gene Amplicon Sequencing in Revealing Temporal Microbial Community Dynamics

This study explored the short-term planktonic microbial community structure and resilience in Lake Lanier (GA, USA) while simultaneously evaluating the technical aspects of identifying taxa via 16S rRNA gene amplicon and metagenomic sequence data. 16S rRNA gene amplicons generated from four temporally discrete samples were sequenced with 454 GSFLX-Ti yielding ~40,000 rRNA gene sequences from each sample and representing ~300 observed OTUs. Replicates obtained from the same biological sample clustered together but several biases were observed, linked to either the PCR or sequencing-preparation steps. In comparisons with companion whole-community shotgun metagenome datasets, the estimated number of OTUs at each timepoint was concordant, but 1.5 times and ~10 times as many phyla and genera, respectively, were identified in the metagenomes. Our analyses showed that the 16S rRNA gene captures broad shifts in community diversity over time, but with limited resolution and lower sensitivity compared to metagenomic data. We also identified OTUs that showed marked shifts in abundance over four close timepoints separated by perturbations and tracked these taxa in the metagenome vs. 16S rRNA amplicon data. A strong summer storm had less of an effect on community composition than did seasonal mixing, which revealed a distinct succession of organisms. This study provides insights into freshwater microbial communities and advances the approaches for assessing community diversity and dynamics in situ.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

OEDI—Solar Grid Integration Data and Analytics Library

As a part of the Open Energy Data Initiative, this effort aims to develop and demonstrate novel distribution state estimation, control optimization, and transient analysis as well as provide access to data, data integration, and mapping information. More specifically, the focus of the effort will be on physics-based distribution system state estimation, hybrid (physics-based and machine learning) distribution optimal power flow, and event detection/analysis for solar integration and analytics. This work will enable reproducible, robust, replicable, and generalizable R&D in simulation and emulation of solar system integration. These test models and datasets will provide an integrated library for developing and testing power system operation technologies. To make the library user-friendly, this project will provide data curation tools such as data translators, mapping scripts and APIs, database schemas and metadata, interfaces and user dashboard, source code for the reference algorithms, description of the use-cases/scenarios, and comprehensive information on all the assumptions.

14 SOLAR ENERGY↗
DOE OSTI2019

Structure and function of the Orc1 BAH-nucleosome complex

The Origin Recognition Complex (ORC) is essential for replication, heterochromatin formation, telomere maintenance and genome stability in eukaryotes. Here we present the structure of the yeast Orc1 BAH domain bound to the nucleosome core particle. Our data reveal that Orc1, unlike its close homolog Sir3 involved in gene silencing, does not appear to discriminate between acetylated and non-acetylated lysine 16, modification states of the histone H4 tail that specify open and closed chromatin respectively. We elucidate the mechanism for this unique feature of Orc1 and hypothesize that its ability to interact with nucleosomes regardless of K16 modification state enables it to perform critical functions in both hetero- and euchromatin. We also show that direct interactions with nucleosomes are essential for Orc1 to maintain the integrity of rDNA borders during meiosis, a process distinct and independent from its known roles in silencing and replication.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark -- A Bayesian Inverse UQ-based Approach for Data Assimilation

The Organization for Economic Cooperation and Development (OECD) Working Party on Nuclear Criticality Safety (WPNCS) proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian Inverse Uncertainty Quantification (IUQ) as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of Generalized Linear Least Squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. When comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that GLLS predictions fail to replicate computed response distributions for nonlinear applications, while MOCABA shows near agreement, and IUQ uses computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.

FOS: Computer and information sciences↗
DOE OSTI2015

Best Practices for Operando Battery Experiments: Influences of X-ray Experiment Design on Observed Electrochemical Reactivity

Operando experiments are increasingly being applied to capture dynamic reaction intermediates and explore kinetic effects in energy storage research and other areas. A critical assumption of such operando studies is that the data accurately represents the intrinsic system behavior, that is, the system is not perturbed by interaction with the probe or by the sample environment used to replicate the reaction conditions. Here we explore how electrochemical reactivity can be impacted by experiment design, including by X-ray beam interactions or by features of some operando electrochemical cell designs. The results show that without careful experiment design, the electrochemical reactivity in the region being probed by the X-ray beam can be retarded relative to the rest of the cell without obvious signs in the overall cell capacity or electrochemical profile. This can lead to conflicting reports in the literature and incorrect conclusions on reaction mechanisms. Recommendations for reliable operando electrochemical experiments are given.

batteries↗
DOE OSTI2014

The R35 residue of the influenza A virus NS1 protein has minimal effects on nuclear localization but alters virus replication through disrupting protein dimerization

The influenza A virus NS1 protein has a nuclear localization sequence (NLS) in the amino terminal region. This NLS overlaps sequences that are important for RNA binding as well as protein dimerization. To assess the significance of the NS1 NLS on influenza virus replication, the NLS amino acids were individually mutated to alanines and recombinant viruses encoding these mutations were rescued. Viruses containing NS1 proteins with mutations at R37, R38 and K41 displayed minimal changes in replication or NS1 protein nuclear localization. Recombinant viruses encoding NS1 R35A were not recovered but viruses containing second site mutations at position D39 in addition to the R35A mutation were isolated. The mutations at position 39 were shown to partially restore NS1 protein dimerization but had minimal effects on nuclear localization. These data indicate that the amino acids in the NS1 NLS region play a more important role in protein dimerization compared to nuclear localization. - Highlights: • Mutations were introduced into influenza NS1 NLS1. • NS1 R37A, R38A, K41A viruses had minimal changes in replication and NS1 localization. • Viruses from NS1 R35A rescue all contained additional mutations at D39. • NS1 R35A D39X mutations recover dimerization lost in NS1 R35A mutations. • These results reaffirm the importance of dimerization for NS1 protein function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Molecular and Topographical Organization: Influence on Cicada Wing Wettability and Bactericidal Properties

Numerous natural surfaces have micro/nanostructures that result in extraordinary functionality, such as superhydrophobicity, self-cleaning, antifogging, and antimicrobial properties. One such example is the cicada wing, where differences in nanopillar geometry and composition among species can impact and influence the degree of exhibited properties. To understand the relationships between surface topography and chemical composition with multifunctionality, the wing properties of Neotibicen pruinosus (superhydrophobic) and Magicicada cassinii (hydrophobic) cicadas are investigated at time points after microwave-assisted extraction of surface molecules to characterize the chemical contribution to nanopillar functionality. Electron microscopy of the wings throughout the extraction process illustrates nanoscale topographical changes, while concomitant changes in hydrophobicity, bacterial fouling, and bactericidal properties are also measured. Extract analysis reveals the major components of the nanostructures to be fatty acids and saturated hydrocarbons ranging from C17 to C44. Effects on the antimicrobial character of a wing surface with respect to the extracted chemicals suggest that the molecular composition of the nanopillars plays both a direct and an indirect role in concert with nanopillar geometry. The data presented not only correlates the nanopillar molecular organization to macroscale functional properties, but it also presents design guidelines to consider during the replication of natural nanostructures onto engineered substrates to induce desired properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Jet stability and wall impingement flow field in a thermal striping experiment

We present velocity and temperature field measurements for a 0.9 x 0.9 x 1.7 m glass tank in which two air jets at Re=10000 mix and impinge upon the lid at ambient temperature and pressure. Flow patterns are characterized across a 350 x 200 mm plane located 3 mm below the lid for two inlet geometries: 1) “extended”, in which inlet channels protrude above the tank base, and 2) “flush”, a flat base without protrusions. This minor geometry variation produced distinct changes in the lid flow field, appearing as three stagnant regions for the extended case and only one for flush. The dichotomy is attributed to system stability characteristics: jets are stable in the extended case and unstable for flush. In a separate set of nonisothermal tests, the impingement temperature field was measured for inlet temperature mismatches of 4 oC and jets near Re=10000. A 50 m-long fiber optic distributed temperature sensor positioned 2 mm below the lid measured at 1350 locations. Like the velocity fields, the temperature fields differ for the two inlet geometries: good thermal mixing for the flush case and subdued mixing for the extended case. Simulations with the spectral element code Nek5000 replicated the observed stability dichotomy, duplicating the number of stagnant regions observed in the experiment and matching their locations within ±10 mm. Simulation data suggests that flush case instability is due to interactions between jets and wall flows at the bottom of the tank. The clear flow dichotomy exhibited by this two-jet setup presents an unambiguous case to test the ability of CFD tools to predict subtle flow field changes driven by minor modifications in geometry in the context of thermal striping.

42 ENGINEERING↗
DOE OSTI2021

Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion

Combinatorial fusion analysis (CFA) is an approach for combining multiple scoring systems using the rank-score characteristic function and cognitive diversity measure. One example is to combine diverse machine learning models to achieve better prediction quality. In this work, we apply CFA to the synthesis of metal halide perovskites containing organic ammonium cations via inverse temperature crystallization. Using a data set generated by high-throughput experimentation, four individual models (support vector machines, random forests, weighted logistic classifier, and gradient boosted trees) were developed. We characterize each of these scoring systems and explore 66 possible combinations of the models. When measured by the precision on predicting crystal formation, the majority of the combination models improves the individual model results. The best combination models outperform the best individual models by 3.9 percentage points in precision. In addition to improving prediction quality, we demonstrate how the fusion models can be used to identify mislabeled input data and address issues of data quality. In particular, we identify example cases where all single models and all fusion models do not give the correct prediction. Experimental replication of these syntheses reveals that these compositions are sensitive to modest temperature variations across the different locations of the heating element that can hinder or enhance the crystallization process. In summary, we demonstrate that model fusion using CFA can not only identify a previously unconsidered influence on reaction outcome but also be used as a form of quality control for high-throughput experimentation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Comparing traditional and Bayesian approaches to ecological meta‐analysis

Abstract Despite the wide application of meta‐analysis in ecology, some of the traditional methods used for meta‐analysis may not perform well given the type of data characteristic of ecological meta‐analyses. We reviewed published meta‐analyses on the ecological impacts of global climate change, evaluating the number of replicates used in the primary studies ( n i ) and the number of studies or records ( k ) that were aggregated to calculate a mean effect size. We used the results of the review in a simulation experiment to assess the performance of conventional frequentist and Bayesian meta‐analysis methods for estimating a mean effect size and its uncertainty interval. Our literature review showed that n i and k were highly variable, distributions were right‐skewed and were generally small (median n i = 5, median k = 44). Our simulations show that the choice of method for calculating uncertainty intervals was critical for obtaining appropriate coverage (close to the nominal value of 0.95). When k was low (<40), 95% coverage was achieved by a confidence interval (CI) based on the t distribution that uses an adjusted standard error (the Hartung–Knapp–Sidik–Jonkman, HKSJ), or by a Bayesian credible interval, whereas bootstrap or z distribution CIs had lower coverage. Despite the importance of the method to calculate the uncertainty interval, 39% of the meta‐analyses reviewed did not report the method used, and of the 61% that did, 94% used a potentially problematic method, which may be a consequence of software defaults. In general, for a simple random‐effects meta‐analysis, the performance of the best frequentist and Bayesian methods was similar for the same combinations of factors ( k and mean replication), though the Bayesian approach had higher than nominal (>95%) coverage for the mean effect when k was very low ( k < 15). Our literature review suggests that many meta‐analyses that used z distribution or bootstrapping CIs may have overestimated the statistical significance of their results when the number of studies was low; more appropriate methods need to be adopted in ecological meta‐analyses.

Pappalardo, Paula↗
DOE OSTI2022

A seed-like proteome in oil-rich tubers

There are numerous examples of plant organs or developmental stages that are desiccation-tolerant and can withstand extended periods of severe water loss. One prime example are seeds and pollen of many spermatophytes. However, in some plants, also vegetative organs can be desiccation-tolerant. One example are the tubers of yellow nutsedge ( Cyperus esculentus ), which also store large amounts of lipids similar to seeds. Interestingly, the closest known relative, purple nutsedge ( Cyperus rotundus ), generates tubers that do not accumulate oil and are not desiccation-tolerant. We generated nanoLC-MS/MS-based proteomes of yellow nutsedge in five replicates of four stages of tuber development and compared them to the proteomes of roots and leaves, yielding 2257 distinct protein groups. Our data reveal a striking upregulation of hallmark proteins of seeds in the tubers. A deeper comparison to the tuber proteome of the close relative purple nutsedge ( C. rotundus ) and a previously published proteome of Arabidopsis seeds and seedlings indicates that indeed a seed-like proteome was found in yellow but not purple nutsedge. This was further supported by an analysis of the proteome of a lipid droplet-enriched fraction of yellow nutsedge, which also displayed seed-like characteristics. One reason for the differences between the two nutsedge species might be the expression of certain transcription factors homologous to ABSCISIC ACID INSENSITIVE3, WRINKLED1, and LEAFY COTYLEDON1 that drive gene expression in Arabidopsis seed embryos.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Next-generation wargames

Over the past century, and particularly since the outset of the Cold War, wargames (interactive simulations used to evaluate aspects of tactics, operations, and strategy) have become an integral means for militaries and policy-makers to evaluate how strategic decisions are made related to nuclear weapons strategy and international security. Furthermore, these methods have also been applied beyond the military realm, to examine phenomena as varied as elections, government policy, international trade, and supply-chain mechanics. Today, a renewed focus on wargaming combined with access to sophisticated and inexpensive drag-and-drop digital game development frameworks and new cloud computing architectures have democratized the ability to enable massive multiplayer gaming experiences. With the integration of simulation tools and experimental methods from a variety of social science disciplines, a science-based experimental gaming approach has the potential to transform the insights generated from gaming by creating human-derived, large-n datasets for replicable, quantitative analysis. In the following, we outline challenges associated with contemporary simulation and wargaming tools, investigate where scholars have searched for game data, and explore the utility of new experimental gaming and data analysis methods in both policy-making and academic settings.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Electronic Visualization Laboratory's 50th Anniversary Retrospective: Look to the Future, Build on the Past

September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL's introduction of the CAVE Automatic Virtual Environment in 1992, the first widely replicated, projection-based, walk-in, virtual-reality (VR) system in the world, put EVL at the forefront of collaborative, immersive data exploration and analytics. However, the journey did not begin then. Since its founding in 1973, EVL has been developing tools and techniques for real-time, interactive visualizations—pillars of VR. But EVL's culture is also relevant to its successes, as it has always been an interdisciplinary lab that fosters teamwork, where each person's expertise contributes to the development of the necessary tools, hardware, system software, applications, and human interface models to solve problems. Over the years, as multidisciplinary collaborations evolved and advanced scientific instruments and data resources were distributed globally, the need to access and share data and visualizations while working with colleagues, local and remote, synchronous and asynchronous, also became important fields of study. This paper is a retrospective of EVL's past 50 years that surveys the many networked, immersive, collaborative visualization and VR systems and applications it developed and deployed, as well as lessons learned and future plans.

Johnson, Andrew E.↗
DOE OSTI2015

Use of XRF to characterize pre-Hanford orchards in the 100-OL-1 operable unit - 15717

Prior to 1943, Hanford site included several small towns with approximately 5,000 acres of orchards; at the time lead arsenate (PbHAsO{sub 4}) was the most commonly used pesticide. High concentration of lead and arsenic have been recorded where trees and stumps are still visible. Pre-Hanford orchards have been designated as 100-OL-1 Operable Unit. An Optimization study evaluated optimal counting time and position of the XRF from soils collected at the site. A Pilot Study included the evaluation of a field portable x-ray fluorescence (XRF) analyzer determining if performance results meet quality assurance criteria for cleanup. XRF has only previously been used as a screening tool. Four Decision Units (DUs) are to be analyzed: Ol-14. OL-32. OL-IU6-4 and OL-FR2-1. The DUs vary in size and have had distinct historic activities; such as 46.4 acres OL-14 having a military camp in the 1950's unlike OL-FR2-1 having been disturbed as it is near the F area reactor. Together the DUs provide an adequate representation of the Operable Unit. Screening criteria for lead (250 mg/kg) and arsenic (20 mg/kg). Six samples were collected ranging above, at, and below the screening criteria of 250 mg/kg for Pb and 20 mg/kg for As at the Decision Units OL-14 and OL-IU6-4, and labeled respectively. Samples were hand sieved, homogenized and placed in sample cups. Three replicates were prepared for each sample. Each sample cup was analyzed 3 times for 30 sec. A Standard Reference Material (SRM) was analyzed after every 20 readings. Three samples were selected for 15, 30, 45, 60, 90, 120, 150 and 180 second fixed and variable analysis. Two transects at OL-14, and one at OL-IU6-4 were created by selecting locations 90. around ground zero at distances of 0.5, 1, 2, 4, 8 and 12 feet (16 ft for OL-14). Locations were scanned in triplicate for 60 seconds each. 4 Decision Units spanning roughly 370 acres were chosen to represent 100-OL-1 Operable Unit. 40 locations within each DU were selected using Visual Sample Plan (VSP) with a random start and systematic grid pattern. Each location would be analyzed with 3 replicates and a 60 second count time. The Standard Reference Material (SRM) and blank are analyzed after every 20 counts to ensure accuracy. Data is extracted from XRF to be implemented in GIS for visual representation of site with 1943 and 2013 aerial imagery. Discussion/Conclusion: - XRF provided a good indication of precision and accuracy relative to ICP with a linear correlation R{sup 2} value higher than anticipated at .9735; - MDL proved the detection limit is significantly lower than the screening criteria; - When comparing results from the first 40 locations of OL-14 to the total 80 locations of OL-14, the same variability was seen; - We expect high concentrations of Pb and As to be where past orchards are present though this does not occur as all sites. Significance: - XRF is competent for decision making as values fall within ±20% ICP data; - The highest concentrations are not where expected, which may be an issue for sites outside of Hanford that have had more development; - The size of the DU does not affect the number of samples measured. Future Work: - Verification and validation of the XRF Data (QA/QC); - Revise conceptual site model; - Statistical evaluations to investigate: Estimation of variability in surface soils, appropriate size for DU, and sample size per DU; - Coordinating sample results through CORE; - Displaying sample results in PHOENIX (GIS tool)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

SPRUCE Deep Peat Heating (DPH) Peat Water Content and Temperature for Experimental Plot Cores, June 2014 through June 2015

This data set provides the peat water content and peat temperature at time of sampling for peat cores collected before and during the SPRUCE Deep Peat Heating (DPH) study. Cores were collected during three sampling events: 03 June 2014, 09 September 2014, and 16 June 2015. Two cores were extracted from hollow locations in each of the 10 experimental plots (4, 6, 8, 10, 11, 13, 16, 17, 19, and 20). The five ambient plots (5, 7, 14, and 21) were not included in the DPH sampling efforts. See Table 1. Cores were partitioned into samples at 11 depth increments: 0-10, 10-20, 20-30, 30-40, 40-50, 50-75, 75-100, 100-125, 125-150, 150-175, and 175-200 cm below surface of the hollow. The DPH study was undertaken to evaluate possible rapid responses of deep peat carbon (C) stocks, microbial communities, and biogeochemical cycling processes to unprecedented temperatures. In June 2014, deep soil heating was initiated at 5 warming levels (+0, +2.25, +4.5, +6.75 and +9 °C) with 2 replicate plots per level. Warming levels at depth were achieved over a 25 (+ 2.25 °C) to 60-day (+9 °C) period depending on the target treatment temperatures. Data file – There is one comma-separated (*.csv) file with peat core water content and temperature at time of sampling, plus the amount of dried archived material retained after analyses. User Note: In this third release, four variables related to extrapolations of peat core temperature were removed. See the Data Set History table for additional details. 25-150, 150-175, and 175-200 cm below surface of the hollow.

54 ENVIRONMENTAL SCIENCES↗