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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Intraspecific Diversity in Thermal Performance Determines Phytoplankton Ecological Niche

ABSTRACT Temperature has a primary influence on phytoplankton physiology and ecology. We grew 12 strains of Gephyrocapsa huxleyi isolated from different‐temperature regions for ~45 generations (2 months) and characterised acclimated thermal response curves across a temperature range. Even with similar temperature optima and overlapping cell size, strain growth rates varied between 0.45 and 1 day −1 . Thermal niche widths varied from 16.7°C to 24.8°C, suggesting that strains use distinct thermal response mechanisms. We investigated the implications of this thermal intraspecific diversity using an ocean ecosystem simulation resolving phytoplankton thermal phenotypes. Model analogues of thermal ‘generalists’ and ‘specialists’ resulted in a distinctive global biogeography of thermal niche widths with a nonlinear latitudinal pattern. We leveraged model output to predict ranges of the 12 lab‐reared strains and demonstrated how this approach could broadly refine geographic range predictions. Our combination of observations and modelled biogeography highlights the capacity of diverse groups to survive temperature shifts.

Krinos, Arianna I. [Department of Biology Woods Ho↗
DOE OSTI2025

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (June to October 2019)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken at three time points from June 12, 2019 to October 23,2019 at a location (PTT1) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Sediment samples were collected from 60 to 180 cm below surface every 30cm for microbial analyses through metagenomic sequencing. 15 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0131241. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 780 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June 2018)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June 2018 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 50 to 150 cm depth below surface at discrete depths every 20 cm for microbial analyses. A total of 12 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 1233 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (September 2019)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken September 2019 at one locations (OBJ1) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 50 to 150 cm depth below surface at discrete depths every 20 cm for microbial analyses. A total of 6 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 2562 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Can Agricultural Management Induced Changes in Soil Organic Carbon Be Detected Using Mid-Infrared Spectroscopy?

A major limitation to building credible soil carbon sequestration programs is the cost of measuring soil carbon change. Diffuse reflectance spectroscopy (DRS) is considered a viable low-cost alternative to traditional laboratory analysis of soil organic carbon (SOC). While numerous studies have shown that DRS can produce accurate and precise estimates of SOC across landscapes, whether DRS can detect subtle management induced changes in SOC at a given site has not been resolved. Here, we leverage archived soil samples from seven long-term research trials in the U.S. to test this question using mid infrared (MIR) spectroscopy coupled with the USDA-NRCS Kellogg Soil Survey Laboratory MIR spectral library. Overall, MIR-based estimates of SOC%, with samples scanned on a secondary instrument, were excellent with the root mean square error ranging from 0.10 to 0.33% across the seven sites. In all but two instances, the same statistically significant (p < 0.10) management effect was found using both the lab-based SOC% and MIR estimated SOC% data. Despite some additional uncertainty, primarily in the form of bias, these results suggest that large existing MIR spectral libraries can be operationalized in other laboratories for successful carbon monitoring.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mathematical solutions in internal dose assessment: A comparison of Python-based differential equation solvers in biokinetic modeling

Abstract In biokinetic modeling systems employed for radiation protection, biological retention and excretion have been modeled as a series of discretized compartments representing the organs and tissues of the human body. Fractional retention and excretion in these organ and tissue systems have been mathematically governed by a series of coupled first-order ordinary differential equations (ODEs). The coupled ODE systems comprising the biokinetic models are usually stiff due to the severe difference between rapid and slow transfers between compartments. In this study, the capabilities of solving a complex coupled system of ODEs for biokinetic modeling were evaluated by comparing different Python programming language solvers and solving methods with the motivation of establishing a framework that enables multi-level analysis. The stability of the solvers was analyzed to select the best performers for solving the biokinetic problems. A Python-based linear algebraic method was also explored to examine how the numerical methods deviated from an analytical or semi-analytical method. Results demonstrated that customized implicit methods resulted in an enhanced stable solution for the inhaled 60 Co (Type M) and 131 I (Type F) exposure scenarios for the inhalation pathway of the International Commission on Radiological Protection (ICRP) Publication 130 Human Respiratory Tract Model (HRTM). The customized implementation of the Python-based implicit solvers resulted in approximately consistent solutions with the Python-based matrix exponential method ( expm ). The differences generally observed between the implicit solvers and expm are attributable to numerical precision and the order of numerical approximation of the numerical solvers. This study provides the first analysis of a list of Python ODE solvers and methods by comparing their usage for solving biokinetic models using the ICRP Publication 130 HRTM and provides a framework for the selection of the most appropriate ODE solvers and methods in Python language to implement for modeling the distribution of internal radioactivity.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June to October 2020)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June to October 2020 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 30 cm depth below surface to just above the cobble layer (~190-250 cm depth) at discrete depths every 40 cm for microbial analyses. A total of 35 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 2848 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

PS3: The Pheno-Synthesis software suite for integration and analysis of multi-scale, multi-platform phenological data

Phenology is the study of recurring plant and animal life-cycle stages which can be observed across spatial and temporal scales that span orders of magnitude (e.g., organisms to landscapes). The variety of scales at which phenological processes operate is reflected in the range of methods for collecting phenologically relevant data, and the programs focused on these collections. Consideration of the scale at which phenological observations are made, and the platform used for observation, is critical for the interpretation of phenological data and the application of these data to both research questions and land management objectives. However, there is currently little capacity to facilitate access, integration and analysis of cross-scale, multi-platform phenological data. This paper reports on a new suite of software and analysis tools – the “Pheno-Synthesis Software Suite,” or PS3 – to facilitate integration and analysis of phenological and ancillary data, enabling investigation and interpretation of phenological processes at scales ranging from organisms to landscapes and from days to decades. We use PS3 to investigate phenological processes in a semi-aride, mixed shrub-grass ecosystem, and find that the apparent importance of seasonal precipitation to vegetation activity (i.e., “greenness”) is affected by the scale and platform of observation. We end by describing potential applications of PS3 to phenological modeling and forecasting, understanding patterns and drivers of phenological activity in real-world ecosystems, and supporting agricultural and natural resource management and decision-making.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Duke Forest FACE (FACTS-I): Plant and Soil Response Data

This dataset describing the responses of plant and soil pools and fluxes to elevated atmospheric CO2 concentration and increased nitrogen supply was collected from Duke Forest Free Air CO2 Enrichment (FACE) – Forest-Atmosphere Carbon Transfer and Storage (FACTS-I) experiment from 1996 to 2012. The dataset includes data files for allometry (diameter at breast height, tree height, and height to live crown base), leaf area index, biomass (stem, branch, foliage, and root biomass, tree density, and basal area), net primary productivity (stem, branch, foliage, reproductive, and coarse root NPP), sap flux density, soil CO2 efflux, and stem temperature. Data files were formatted as .csv (Microsoft Excel or other spreadsheet programs can be used to read the format) and file descriptions, including variable name, unit, and data range, can be found in ‘FileDescription_[data_name].txt’ files. The Duke FACE experiment was in a loblolly pine (Pinus taeda L.) plantation established in 1983. Naturally regenerated broadleaved species including sweetgum (Liquidambar styraciflua L.) and tulip poplar (Liriodendron tulipifera L.), mostly in the overstory, and winged elm (Ulmus alata Michx.) and red maple (Acer rubrum L.) were common in the understory. The FACE experiment commenced with two plots (plots 7-8) in 1994 (Oren et al. 2001), with six additional plots (plots 1-6) coming online on 27 August 1996. CO2 enrichment was terminated on 31 October 2010 and post-enrichment data collection continued through 2012. Complete fertilization was applied annually to half of plots 7-8 from 1998 to 2004. The nutrient addition experiment expanded to half of plots 1-6 with a common protocol of N-fertilization in 2005 and continued until 2012. The levels of treatment in this dataset were expressed as ambient CO2 (AMB) or elevated CO2 (ELE) for CO2 treatment and control soil (CONT) or fertilized soil (FERT) for N treatment, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Assessment of habitat‐specific competition for oral rabies vaccine baits between raccoons and opossums

Abstract Throughout the eastern United States, the National Rabies Management Program (NRMP) distributes oral rabies vaccine (ORV) baits to manage rabies virus circulation in raccoon ( Procyon lotor ) populations. The consumption of vaccine baits by non‐target species including Virginia opossums ( Didelphis virginiana ) may reduce the effectiveness of ORV programs, but competition for baits remains poorly quantified in many areas of the southeastern United States. We distributed placebo ORV baits injected with a biomarker across 4 land cover types (bottomland hardwood, upland pine, riparian, isolated wetland) on the Savannah River Site in South Carolina, USA, 2017–2019. We then trapped and collected whiskers from 247 raccoons and 78 opossums to assess biomarker presence using fluorescent microscopy. Our data revealed greater bait uptake probability by raccoons (estimated x̅ = 0.30, 95% CI = 0.19–0.44) compared to opossums (estimated x̅ = 0.11, 95% CI = 0.05–0.23) across all cover types surveyed. Probability of bait consumption was not affected by cover type or the abundance of raccoons or opossums. Among raccoons, males were more likely to consume baits than females (estimated x̅ = 0.28, 95% CI = 0.17–0.44 for males and 0.14, 95% CI = 0.05–0.31 for females) and probability of consumption increased by 0.08 with each additional day trapped during the 10‐day trapping session. Uptake rates for raccoons were relatively low compared to other studies and not influenced by competition with opossums. These low consumption rates indicate that additional research addressing the roles of baiting season, bait density, and resource selection will be important to maximize ORV bait uptake by target species in these southeastern landscapes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Investigating the Influence of River Geomorphology on Human Presence Using Night Light Data: A Case Study in the Indus Basin

Human settlements have historically thrived near rivers due to enhanced navigation and trade, and the availability of water supply and resources. The use of night light data, representing economic activities, provides a novel approach to studying the interactions between human activity and rivers over time. Here, we use the Defense Meteorological Satellite Program (DMSP) stable night light data from 2000 to 2013 as a proxy for human presence and activities to quantify the statistical relationships between night light presence and intensity in the Indus Basin, Asia. We test how these data are affected by proximity to trunk channels and by channel type (single/multi-thread) in the study area. We find that night light presence is enhanced by 26% within a 0 to 5 km proximity range of the Indus River and its tributaries, relative to the basin as a whole. We interpret this to represent increased human presence and activity within this zone. However, the mean intensity is lower near the river and higher away from the river, signifying denser settlements, such as towns and cities, which are preferentially located away from the Indus and its tributaries. Moreover, the enhancement of lit pixels signifying human presence and activities is increased by 18% near single-thread sections of the Indus River, compared to segments of the Indus displaying multi-thread morphologies. We suggest that this is due to the enhanced stability of single-threaded channels, relative to mobile multi-threaded channel reaches. This study demonstrates how night lights are an important tool in studying the relationship between human presence and river dynamics in large catchments such as the Indus, and we suggest that these data will have an important role in assessing differential flood spatial and social vulnerability at a regional scale.

Environmental Sciences & Ecology↗
DOE OSTI2021

Adaptive Phenotypic Plasticity Stabilizes Evolution in Fluctuating Environments

Fluctuating environmental conditions are ubiquitous in natural systems, and populations have evolved various strategies to cope with such fluctuations. The particular mechanisms that evolve profoundly influence subsequent evolutionary dynamics. One such mechanism is phenotypic plasticity, which is the ability of a single genotype to produce alternate phenotypes in an environmentally dependent context. Here, we use digital organisms (self-replicating computer programs) to investigate how adaptive phenotypic plasticity alters evolutionary dynamics and influences evolutionary outcomes in cyclically changing environments. Specifically, we examined the evolutionary histories of both plastic populations and non-plastic populations to ask: (1) Does adaptive plasticity promote or constrain evolutionary change? (2) Are plastic populations better able to evolve and then maintain novel traits? And (3), how does adaptive plasticity affect the potential for maladaptive alleles to accumulate in evolving genomes? We find that populations with adaptive phenotypic plasticity undergo less evolutionary change than non-plastic populations, which must rely on genetic variation from de novo mutations to continuously readapt to environmental fluctuations. Indeed, the non-plastic populations undergo more frequent selective sweeps and accumulate many more genetic changes. We find that the repeated selective sweeps in non-plastic populations drive the loss of beneficial traits and accumulation of maladaptive alleles, whereas phenotypic plasticity can stabilize populations against environmental fluctuations. This stabilization allows plastic populations to more easily retain novel adaptive traits than their non-plastic counterparts. In general, the evolution of adaptive phenotypic plasticity shifted evolutionary dynamics to be more similar to that of populations evolving in a static environment than to non-plastic populations evolving in an identical fluctuating environment. All natural environments subject populations to some form of change; our findings suggest that the stabilizing effect of phenotypic plasticity plays an important role in subsequent adaptive evolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Long-term variability of root production in bioenergy crops from ingrowth core measurements

Long-term determination of root biomass production upon land-use conversion to biofuel crops is rare. To assess land-use legacy influences on belowground biomass accumulation, we converted 22-year-old Conservation Reserve Program (CRP) grasslands and 50+-year-old agricultural (AGR) lands to corn (C), switchgrass (Sw) and restored prairie (Pr) biofuel crops. We maintained one CRP grassland as a reference (Ref). We hypothesized that land-use history and crop type have significant effects on root density, with perennial crops on CRP grasslands having a higher root biomass productivity, while corn grown on former agricultural lands produce the lowest root biomass. Methods The ingrowth core method was used to determine in situ ingrowth root biomass, alongside measurements of aboveground net primary productivity (ANPP). Ancillary measurements, including air temperature, growing season length and precipitation were used to examine their influences on root biomass production. Important Findings Root biomass productivity was the highest in unconverted CRP grassland (1716 g m-2 yr-1) and lowest in corn fields (526 g m-2 yr-1). All perennial sites converted from CRP and AGR lands had lower root biomass and ANPP in the first year of planting but peaked in 2011 for switchgrass and a year later for restored prairies. Ecosystem stability was higher in restored prairies (AGR-Pr: 4.3 ± 0.11; CRP-Pr: 4.1 ± 0.10), with all monocultures exhibiting a lower stability. Root biomass production was positively related to ANPP (R2 = 0.40). Overall, attention should be given to root biomass accumulation in large-scale biofuel production as it is a major source of carbon sequestration.

Environmental Sciences & Ecology↗
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)]↗
DOE OSTI2022

Data from: "Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers"

This archive contains data used to draw conclusions in “Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers”, by Kueppers et al. 2017. Cone collection and field experiments were conducted on Niwot Ridge, Colorado, with the latter completed within the Alpine Treeline Warming Experiment (ATWE). Laboratory germination experiments were conducted at the University of California Merced. Geospatial files are also provided for additional geographical context.There are four data file formats in this package: comma-separated values (.csv), Microsoft Excel (.xlsx), keyhole markup language (.kml), and ESRI shapefile (.shp). The latter two are geospatial file formats. .csv files can be opened using any simple text editor program such as TextEdit (Mac) and Notepad (Windows), and .xlsx files can be opened using Microsoft Excel or Google Sheets. The .kml file contains coordinate data, and is compatible with Google Earth and Google Maps. ESRI shapefiles (.shp) are compatible with any geospatial software able to read the file type, such as QGIS and ESRI’s ArcGIS Suite. This data user’s guide is available in as a .pdf, and can be opened using software such as Adobe Acrobat Reader.-----------------------------------------------------------------------------------------------------------------------------------Accurately predicting upslope shifts in subalpine tree ranges with warming requires understanding how future forest populations will be affected by climate change, as these are the seed sources for new tree line and alpine populations. Early life history stages are particularly sensitive to climate and are also influenced by genetic variation among populations. We tested the climate sensitivity of germination and initial development for two widely distributed subalpine conifers, using controlled-environment growth chambers with one temperature regime from subalpine forest in the Colorado Rocky Mountains and one 5 °C warmer, and two soil moisture levels. We tracked germination rate and timing, rate of seedling development, and seedling morphology for two seed provenances separated by ~300 m elevation. Warming advanced germination timing and initial seedling development by a total of ~2 weeks, advances comparable to mean differences between provenances. Advances were similar for both provenances and species; however, warming reduced the overall germination rate, as did low soil moisture, only for Picea engelmannii. A three-year field warming and watering experiment planted with the same species and provenances yielded responses qualitatively consistent with the lab trials. Together these experiments indicate that in a warmer, drier climate, P. engelmannii germination, and thus regeneration, could decline, which could lead to declining subalpine forest populations, while Pinus flexilis forest populations could remain robust as a seed source for upslope range shifts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Contaminant Migration Modeling to Support the In Situ Decommissioning of Hardened Nuclear Facilities - 20215

The decommissioning of hardened nuclear facilities provides a unique challenge in balancing current worker dose with exposure to future receptors and media. In situ decommissioning (ISD) is a cost-effective and safe option for the closure of such facilities but requires a detailed understanding of the threat that radioactive and hazardous constituents remaining in the facilities pose to groundwater and surrounding surface water. The Savannah River Site (SRS) extensively employs contaminant migration models within the decommissioning process to develop site-specific removal, grouting, and monitoring strategies in support of safe and effective final end states of nuclear facilities. This work discusses the use of contaminant migration modeling in the ISD process at SRS, including specific examples from the closure of P-Reactor and R-Reactor, Building 235-F, F-Canyon and F/H Laboratory Complex. Migration models developed during the closure of P-Reactor and R-Reactor were divided into four source areas: the reactor vessel, the process area, the disassembly basin, and the purification wing. Each source area was assigned a specific inventory and migration pathway and was then subject to varying hypothetical removal, capping, and grouting schemes. Modeling indicated that groundwater Maximum Concentration Limits (MCLs) might be exceeded if no action was taken for eleven and ten constituents of concern (COCs) at P-Reactor and R-Reactor, respectively. These exceedances could occur in as few as 200 to 500 years. Alternatively, the migration modeling demonstrated that the selected ISD actions reduced contaminant mobility which allowed for significant radioactive decay and resulted in fewer predicted exceedances of groundwater MCLs (five COCs for P-Reactor; eight COCs for R-Reactor). In response to the modeling results for P-Reactor and R-Reactor, effectiveness monitoring programs were developed to target contaminants, specific to each reactor, that may migrate to groundwater. Contaminant migration modeling also revealed that roof collapse was a large factor in the release of COCs to the environment, giving rise to roof improvements, and an inspection and vegetation control program to ensure roof stability over time. Contaminant migration modeling is also aiding in the closure planning for hardened facilities in F Area. Building 235-F housed the Actinide Billet Line, which produced Np-237 billets for irradiation in SRS reactors, and the Plutonium Fuel Form (PuFF) facility that produced Pu-238 heat sources for the space program. As a result of these missions, areas within Building 235-F contain considerable residual amounts of both Pu-238 and Np-237. Contaminant migration modeling of Building 235-F was originally performed in 2012 to identify the feasibility of ISD and the amount of radioactive material removal required to prevent the exceedance of groundwater MCLs. The original model indicated that a 60% reduction in the PuFF facility Pu-238 inventory could keep groundwater concentrations below standards, while Np-237 did not pose a threat to groundwater. However, updates to the model with an emphasis on source impact pathways revealed that, due to the orientation of the source areas relative to groundwater flow, no amount of reasonable removal of Pu-238 would keep groundwater concentrations below MCLs and that Np-237 could be a large contributor to localized MCL exceedances. With this insight, the refined 2019 model is being used to assist in the development of grouting plans specific to each facility source area, where bentonite may be utilized to slow the migration of Pu-238 and its daughter products from the PuFF facility and a reducing grout may decrease Np-237 transport by ensuring the nuclide remains in the less mobile +IV oxidation state. The beginning phases of contaminant migration modeling are underway for F-Canyon and associated facilities using lessons learned from the Reactors and Building 235-F. A contaminant migration pathway, similar to the pathway used for the reactor vessels, is being developed for the hot and warm canyons. The F-Canyon inventories are being spatially refined to identify specific and localized source zones, comparable to Building 235-F, that may impact groundwater. Contaminant migration modeling provides vital input within the ISD process, from facility investigation to post closure effectiveness monitoring, making it a valuable tool in the development of safe and effective end states for hardened nuclear facilities at SRS. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Data from: "Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions"

This archive contains data files that were used to draw conclusions in “Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions”, by Moyes et al., 2015. All field research was completed in common garden plots set up as part of the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA.There are two main data file formats in this archive: comma-separated values (.csv), and Microsoft Excel (.xls and .xlsx). .xlsx files can be read using Microsoft Excel and Google Sheets, and .csv files can be read using any simple text editor program, such as TextEdit (Mac) and Notepad (Windows). This .pdf data user’s guide can be read using Adobe Acrobat Reader, or any other compatible software. Seedling photographs and their corresponding leaf area-processed images are available in .jpg/.JPG image format, and can be opened using Preview (Mac) and Photos (Windows). To provide additional spatial context, two types of geospatial files are also published in this data package: ESRI shapefiles (.shp) and .kml files. Shapefiles are compatible with any GIS software able to read the file type (such as QGIS or ESRI’s ArcGIS suite), and .kml files can be opened with Google Earth or Google Maps. Figures 3 and 4 in the publication contain data from Moyes et al. 2013. This publication is cited in the References section in this archive, and data files can be accessed via the Alpine Treeline Warming Experiment project portal on ESS-DIVE. ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Climate change is altering plant species distributions globally, and warming is expected to promote uphill shifts in mountain trees. However, at many cold-edge range limits, such as alpine treelines in the western United States, tree establishment may be colimited by low temperature and low moisture, making recruitment patterns with warming difficult to predict.- We measured response functions linking carbon (C) assimilation and temperature- and moisture-related microclimatic factors for limber pine (Pinus flexilis) seedlings growing in a heating × watering experiment within and above the alpine treeline. We then extrapolated these response functions using observed microclimate conditions to estimate the net effects of warming and associated soil drying on C assimilation across an entire growing season.- Moisture and temperature limitations were each estimated to reduce potential growing season C gain from a theoretical upper limit by 15–30% (c. 50% combined). Warming above current treeline conditions provided relatively little benefit to modeled net assimilation, whereas assimilation was sensitive to either wetter or drier conditions.- Summer precipitation may be at least as important as temperature in constraining C gain by establishing subalpine trees at and above current alpine treelines as seasonally dry subalpine and alpine ecosystems continue to warm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A multiscale landscape approach for prioritizing river and stream protection and restoration actions

River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.

54 ENVIRONMENTAL SCIENCES↗