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At least 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Prokaryotic taxa play keystone roles in the soil microbiome associated with woody perennial plants in the genus Buxus

The microbiome associated with ornamental plants has largely been neglected, despite its potential for impacting plant health. This work characterized the composition, diversity, and microbial co-associations in the soil microbiome associated with species and cultivars of plant in the genus Buxus (common name boxwood), a group of woody perennial shrubs commonly used in residential landscapes and found in native ecosystems. Soil was collected from 82 individual curated boxwood accessions at the U.S. National Arboretum National Boxwood Collection. Amplicon libraries targeting archaea, bacteria, and fungi were generated and sequenced using the Illumina MiSeq platform. Identification of individual sequence variants resulted in 275 archaeal, 15,580 bacterial, and 7,525 fungal taxa. Neither spatial distance among samples nor association with different types of boxwood were significant predictors of soil microbiome composition. However, archaeal and bacterial diversity was significantly different in soil from distinct types of boxwood. Co-association networks indicated that archaea and bacteria show greater evidence of being keystone taxa than fungi. Overall, this work demonstrates the potential for targeting specific keystone taxa to shift the soil microbiome associated with these boxwood accessions and that planting different species or cultivars in the landscape may shift the diversity of prokaryotic microorganisms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Camera settings and biome influence the accuracy of citizen science approaches to camera trap image classification

Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion-activated trail cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy is poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best-practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online: Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photograph was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answer for each photograph using a plurality algorithm. Subsequently, a subset of these images underwent expert review and were compared to the citizen scientist results. Classification errors were categorized by the nature of the error (e.g., false species or false empty), and reason for the false classification (e.g., misidentification). Our results show that Snapshot Serengeti had the highest accuracy (97.9%), followed by AmazonCam Tambopata (93.5%), then Wildwatch Kenya (83.4%). Error type was influenced by habitat, with false empty images more prevalent in open-grassy habitat (27%) compared to woodlands (10%). For medium to large animal surveys across all habitat types, our results suggest that to significantly improve accuracy in crowdsourced projects, researchers should use a trail camera set up protocol with a burst of three consecutive photographs, a short field of view, and determine camera sensitivity settings based on in situ testing. Accuracy level comparisons such as this study can improve reliability of future citizen science projects, and subsequently encourage the increased use of such data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Assessing the Application of a Genomic Network Analysis in Population Ecology: Inferring Patterns of Dispersal and Geographic Structure in the Emerging Pathogen, Coccidioides

A challenge in population ecology studies is identifying how to best group individuals into populations, especially when individual origin is unknown. Machine learning has improved upon traditional methods of identifying population structure and is more efficient at handling large, complex datasets. We demonstrate the applicability of a machine learning method to identify hierarchical population structure in an emerging pathogen, Coccidioides spp., the causative agent of Valley fever. We compared the network clusters to structure identified by traditional tools as a validation of the network performance. We used publicly available whole-genome data for 48 C. immitis and 102 C. posadasii, resulting in 168,211 genome-wide SNPs among the two species. The network analysis grouped samples into populations comparable to the literature for these species but also identified fine-scale geographic structure and travel-associated cases not reported thus far. Exploring different resolutions in the network made it easy to identify unique genotypes specific to California and possibly Nevada, as well as Phoenix- and Tucson-acquired infections in non-endemic areas, regardless of reported travel history. The present study provides a promising example of how a ML-based network analysis can improve our ability to understand pathogen ecology, group cases into populations and infer travel-associated infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A global database of nitrogen and phosphorus excretion rates of aquatic animals

Though their importance varies greatly among species and ecosystems, animals can be important in modulating ecosystem-level nutrient cycling. Nutrient cycling rates of individual animals represent valuable data for testing the predictions of important frameworks such as the Metabolic Theory of Ecology (MTE) and ecological stoichiometry (ES). They also represent an important set of functional traits that may reflect both environmental and phylogenetic influences. Over the past two decades, studies of animal-mediated nutrient cycling have increased dramatically, especially in aquatic ecosystems. Here we present a global compilation of aquatic animal nutrient excretion rates. The dataset includes 10,534 observations from freshwater and marine animals of N and/or P excretion rates. Furthermore, these observations represent 491 species, including most aquatic phyla. Coverage varies greatly among phyla and other taxonomic levels. The dataset includes information on animal body size, ambient temperature, taxonomic affiliations, and animal body N:P. We used this data set to test predictions of MTE and ES, as described in Vanni and McIntyre (2016; Ecology DOI: 10.1002/ecy.1582).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Limited evidence for spatial resource partitioning across temperate grassland biodiversity experiments

Locally, plant species richness supports many ecosystem functions. Yet, the mechanisms driving these often-positive biodiversity–ecosystem functioning relationships are not well understood. Spatial resource partitioning across vertical resource gradients is one of the main hypothesized causes for enhanced ecosystem functioning in more biodiverse grasslands. Spatial resource partitioning occurs if species differ in where they acquire resources and can happen both above- and belowground. However, studies investigating spatial resource partitioning in grasslands provide inconsistent evidence. We present the results of a meta-analysis of 21 data sets from experimental species-richness gradients in grasslands. We test the hypothesis that increasing spatial resource partitioning along vertical resource gradients enhances ecosystem functioning in diverse grassland plant communities above- and belowground. To test this hypothesis, we asked three questions. (1) Does species richness enhance biomass production or community resource uptake across sites? (2) Is there evidence of spatial resource partitioning as indicated by resource tracer uptake and biomass allocation above- and belowground? (3) Is evidence of spatial resource partitioning correlated with increased biomass production or community resource uptake? Although plant species richness enhanced community nitrogen and potassium uptake and biomass production above- and belowground, we found that plant communities did not meet our criteria for spatial resource partitioning, though they did invest in significantly more aboveground biomass in higher canopy layers in mixture relative to monoculture. Furthermore, the extent of spatial resource partitioning across studies was not positively correlated with either biomass production or community resource uptake. Our results suggest that spatial resource partitioning across vertical resource gradients alone does not offer a general explanation for enhanced ecosystem functioning in more diverse temperate grasslands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Differences in soil organic matter between EcM- and AM-dominated forests depend on tree and fungal identity

As global change shifts the species composition of forests, we need to understand which species characteristics affect soil organic matter (SOM) cycling to predict future soil carbon (C) storage. Recently, whether a tree species forms a symbiosis with arbuscular (AM) versus ectomycorrhizal (EcM) fungi has been suggested as a strong predictor of soil C storage, but there is wide variability within EcM systems. In this study, we investigated how mycorrhizal associations and the species composition of canopy trees and mycorrhizal fungi related to the proportion of soil C and nitrogen (N) in mineral associations and soil C:N across four sites representing distinct climates and tree communities in the eastern US broadleaf forest biome. In two of our sites, we found the expected relationship of declining mineral-associated C and N and increasing soil C:N ratios as the basal area of EcM-associating trees increased. However, across all sites these soil properties strongly correlated with canopy tree and fungal species composition. Sites where the expected pattern with EcM basal area was observed were (1) dominated by trees with lower quality litter in the Pinaceae and Fagaceae families and (2) dominated by EcM fungi with medium-distance exploration type hyphae, melanized tissues, and the potential to produce peroxidases. Here, this observational study demonstrates that differences in SOM between AM and EcM systems are dependent on the taxa of trees and EcM fungi involved. Important information is lost when the rich mycorrhizal symbiosis is reduced to two categories.

mineral-associated organic matter↗
DOE OSTI2025

All the light we cannot see: Climate manipulations leave short and long‐term imprints in spectral reflectance of trees

Abstract Anthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant‐environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming and drought affect spectra. To address this gap, we used an open‐air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal‐temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400–2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid‐season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long‐ and short‐time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near‐infrared and short‐wave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g., indices and traits) improves inferences about plant‐environment relationships, which is particularly important in times of unprecedented climate change.

Stefanski, Artur [Department of Forest Resources U↗
DOE OSTI2014

Artificial viscosity: back to the basics

Summary In this paper, we take a different perspective on the derivation of artificial viscosity. Heretofore, the development of artificial viscosity has been based on the paper published in Journal of Applied Physics in 1950 authored by John von Neumann and Robert Richtmyer [1]. Earlier, in 1948, Richtmyer published a report at Los Alamos Scientific Laboratory documenting the original concept [2]. This report was the true origin of shock capturing methods and contains several key ideas that are conceptually different than the 1950 journal article. Unfortunately, this report (LA‐671) was classified until 1993. This has resulted in two issues: the misattribution of the invention of artificial viscosity as primarily being the work of von Neumann and the loss of the structurally different ideas in the original report. We seek to right the record of history here and use the ideas contained in Richtmyer's report to good effect in deriving a new shock viscosity. The focus of previous development has been the Hugoniot curve describing the locus of states connected by a single shock wave. Here we follow a path more focused upon the Rayleigh line, which is strongly guided by Richtmyer's line of development of the original artificial viscosity formulation. We provide an implementation of the method resulting from this perspective and computational results for simple shock problems. Copyright © 2014 John Wiley & Sons, Ltd.

Mattsson, Ann E.↗
DOE OSTI2023

Thermal insulation versus capacitance: A simulation experiment comparing effects of shade and hyporheic exchange on daily and seasonal stream temperature cycles

In streams where water temperatures stress native biota, management of riparian shade or hyporheic exchange are both considered viable management strategies for reducing the peaks of daily and seasonal stream channel temperature cycles. Although shade and hyporheic exchange may have similar effects on stream temperatures, their mechanisms differ. Improved understanding of the heat-exchange mechanisms influenced by shade and hyporheic exchange will aid in the appropriate application of either stream temperature management strategy. To illustrate a conceptual model highlighting shade as ‘thermal insulation’ and hyporheic exchange imparting ‘thermal capacitance’ to a stream reach, we conducted an in-silico simulation modelling experiment increasing shade or hyporheic exchange parameters on an idealized, hypothetical stream. We assessed the potential effects of increasing shade or hyporheic exchange on a stream reach using an established process-based heat-energy budget model of stream-atmosphere heat exchange and incorporated an advection-driven hyporheic heat exchange routine. The model tracked heat transport through the hyporheic zone and exchange with the stream channel, while including the effects of hyporheic water age distribution on upwelling hyporheic temperatures. Results showed that shade and hyporheic exchange similarly damped diurnal temperature cycles and differentially altered seasonal cycles of our theoretical stream. In winter, hyporheic exchange warmed simulated channel temperatures whereas shade had little effect. In summer, both shade and hyporheic exchange cooled channel temperatures, though the effects of shade were more pronounced. Our simple-to-grasp analogies of ‘thermal insulation’ for shade effects and ‘thermal capacitance’ for hyporheic exchange effects on stream temperature encourage more accurate conceptualization of complex, dynamic heat exchange processes among the atmosphere, stream channel, and alluvial aquifer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Modelling the Sensitivity of Yukon River Biogeochemical Dynamics to Environmental and Chemical Drivers: Implications for Dissolved Organic Carbon

Riverine dissolved organic carbon (DOC) is a critical biogeochemical component that transmits information from Arctic soils to the Arctic Ocean, significantly influencing carbon dynamics in this unique ecosystem. As DOC travels downstream, it undergoes transformations that alter its composition and fate. The Yukon River serves as an effective testbed for modelling these dynamics, offering sufficient scale to capture key biogeochemical processes while having a simpler hydrology than other major Arctic rivers, as well as long-term DOC observational data for model validation. To investigate DOC transformations during transit in the Yukon River, we adapted our Arctic Riverine Organic Macromolecular Model by applying regional-specific parameterisations. Our model simulates the transport and transformation of 15 organic macromolecules, including CDOM (coloured dissolved organic matter), proteins, polysaccharides, lipids, lignin phenols, and humic substances. Initial DOC concentrations were derived from observed soil organic carbon stocks in the surrounding watershed, while chemical transformations and hydrological dynamics were modelled along the river's course. Sensitivity and uncertainty analyses were conducted using a Monte Carlo approach under two experimental setups. Results revealed that variability in DOC and CDOM concentrations at the river mouth were predominantly driven by initial DOC concentration (~70% of variability explained) and dilution at confluence points (~10%). The refractory fraction of DOC explained 21%–88% of the variability in 14 macromolecular concentrations and ranked in the top five sensitive parameters for all outputs when a uniform parameter distribution was assumed. However, when a more likely variability was applied to this parameter, its influence on DOC and CDOM decreased. Given that refractory DOC accounts for ~80% of total DOC in Arctic Rivers, this suggests that most DOC resists degradation and retains its chemical composition during transport to the coastal environment. River velocity, which determines residence time, explained 8%–47% of the variability in protein, polysaccharide, lipid, pigments, and lignin phenols at the river mouth. In contrast, chemical turnover times contributed only 1%–5% to output variability. Our findings underscore the need for improved land-specific headwater observations, including seasonal soil moisture and lateral transport dynamics that control the initial tributary-specific DOC inputs. With accelerated permafrost thaw and increasing river discharge, extending our model to other Arctic River systems and seasons will enhance understanding of Arctic riverine carbon fluxes and their contributions to the Arctic Ocean.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Linking Lattice Strain and Fractal Dimensions to Non‐monotonic Volume Changes in Irradiated Nuclear Graphite

Graphite's resilience to high temperatures and neutron damage makes it vital for nuclear reactors, yet irradiation alters its microstructure, degrading key properties. We used small- and wide-angle X-ray scattering to study neutron-irradiated fine-grain nuclear graphite (Grade G347A) across varied temperatures and fluences. Results show significant shifts in internal strain and porosity, correlating with radiation-induced volume changes. Notably, porosity volume distribution (fractal dimensions) follows non-monotonic volume changes, suggesting a link to the Weibull distribution of fracture stress.

X-ray scattering↗
DOE OSTI2020

Adult weight change and premenopausal breast cancer risk: A prospective pooled analysis of data from 628,463 women

Early-adulthood body size is strongly inversely associated with risk of premenopausal breast cancer. It is unclear whether subsequent changes in weight affect risk. We pooled individual-level data from 17 prospective studies to investigate the association of weight change with premenopausal breast cancer risk, considering strata of initial weight, timing of weight change, other breast cancer risk factors and breast cancer subtype. Hazard ratios (HR) and 95% confidence intervals (CI) were obtained using Cox regression. Among 628,463 women, 10,886 were diagnosed with breast cancer before menopause. Models adjusted for initial weight at ages 18–24 years and other breast cancer risk factors showed that weight gain from ages 18–24 to 35–44 or to 45–54 years was inversely associated with breast cancer overall (e.g., HR per 5 kg to ages 45–54: 0.96, 95% CI: 0.95–0.98) and with oestrogen-receptor(ER)-positive breast cancer (HR per 5 kg to ages 45–54: 0.96, 95% CI: 0.94–0.98). Weight gain from ages 25–34 was inversely associated with ER-positive breast cancer only and weight gain from ages 35–44 was not associated with risk. None of these weight gains were associated with ER-negative breast cancer. Weight loss was not consistently associated with overall or ER-specific risk after adjusting for initial weight. Weight increase from early-adulthood to ages 45–54 years is associated with a reduced premenopausal breast cancer risk independently of early-adulthood weight. Biological explanations are needed to account for these two separate factors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Perceived Conflicts of Systems Engineering in Early-Stage Research and Development 1

Early Systems Research and Development (ESR&D) is one of the most crucial phases in the product development process. It both blends and blurs the lines between science and engineering, and requires a risk-based, disciplined, and graded approach to effectively manage scope, cost, and complexity of the final product. Many leaders, program managers, and scientists are unwilling to involve systems engineering because of the perception that systems engineering is heavily process oriented, adds unnecessary costs, and should be applied only to mature technologies. The value of systems engineering as applied to ESR&D is unclear to these key individuals. The unfortunate result is that system engineering is not applied to ESR&D. This results in R&D efforts that may have solved the wrong problem, selected the wrong architecture, require technical rework, have difficulty transitioning later maturity levels, and result in higher R&D costs and extended development timelines. This work discusses the difficulty of introducing systems engineering to the research and early development process and their inclination perspectives of researchers, engineers, and managers. The article shall offer potential means to manage the cultural transformation of early adoption of right-sized systems engineering in ESR&D and reverse the attitudinal positions.

42 ENGINEERING↗
DOE OSTI2018

The presence of fecal test soil protects bacteria during cleaning/disinfection

Abstract Reusable medical devices (RMDs) must be reprocessed between uses to render them safe for each use and each patient. Cleaning used devices removes organic and inorganic soil making them either safe for reuse or ready for disinfection/sterilization depending on the device. Although cleaning is an important step in a RMD's life cycle, it is not always a priority during device design. In addition, when performing cleaning validation, it is recommended that the manufacturer takes into consideration, what the most appropriate or worst case conditions are in terms of type of soil or the presence of bacteria. This study compared the ability of three different cleaning/disinfecting agents (water, alcohol, and bleach) to remove bacteria and fecal test soil from two different polymers: polypropylene and ultrahigh molecular weight polyethylene (UHMWPE) with two different roughness. There were some differences in the effects of the cleaning/disinfecting agents, the materials, and the roughness depending on the particular circumstances. However, the most consistent effect on the removal of bacteria was the presence of soil, which protected the bacteria from being removed. Conversely, the presence of bacteria played little role in the removal of soil. Although the interactions between material type and roughness, soil type, and bacteria are complicated, they should be taken into account during device design and reprocessing validation to create a device that is easy and safe to use. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 107B: 1706–1710, 2019.

Nandy, Poulomi↗