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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Yellowstone Ecological Forecasting: Assessing Change in Aspen Extent in Northern Yellowstone National Park

The removal and reintroduction of the gray wolf (Canis lupus) in Yellowstone National Park have shaped the ecological composition of this distinct landscape, representing a textbook example of trophic dynamics. With particular importance to conservation science, researchers have studied the trophic cascades between wolves and species such as elk (Cervus canadensis) and quaking aspen (Populus tremuloides). In conjunction with the National Park Service, Yellowstone National Park, Utah State University, and the University of Wisconsin–Stevens Point, this project utilized satellite remote sensing to investigate the long-term trends in aspen extent. Through random forest modeling and phenological approaches, Landsat 5 Thematic Mapper (TM; years 1986–2011) and Sentinel-2 Multispectral Instrument (MSI; years 2017–2019) datasets were used to derive color composites, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Tasseled Cap Indices (Brightness, Greenness, Wetness). The International Space System (ISS) Global Ecosystem Dynamics Investigation (GEDI) provided canopy height data. The team consolidated results into maps and time-series which provide an in-depth depiction of aspen stand extent. The National Park Service will use these end products to assist in its management practices and inform wildlife restoration decisions within and beyond Yellowstone National Park.

Kyle Steen↗
DOE OSTI2022

Growth and Performance of High-Quality SWCNT Forests on Inconel Foils as Lithium-Ion Battery Anodes

Large-scale production of vertically aligned single-walled carbon nanotubes (VA-SWCNTs) on metal foils promises to enable technological advancements in many fields, from functional composites to energy storage to thermal interfaces. In this work, we demonstrate growth of high-quality (G/D > 6, average diameters ~ 2–3 nm, densities > 10 12 cm –2 ) VA-SWCNTs on Inconel metal for use as a lithium-ion battery (LIB) anode. Scale-up of SWCNT growth on Inconel 625 to 100 cm 2 exhibits nearly invariant CNT structural properties, even when synthesis is performed near atmospheric pressure, and this robustness is attributed to a growth kinetic regime dominated by the carbon precursor diffusion in the bulk gas mixture. SWCNT forests produced on large-area metal substrates at close to atmospheric pressure possess a combination of structural features that are among the best demonstrated so far in the literature for growth on metal foils. Leveraging these achievements for energy applications, we demonstrate a VA-SWCNT LIB anode with capacity >1200 mAh/g at 1.0C and stable cycling beyond 300 cycles. Furthermore, this robust synthesis of high-quality VA-SWCNTs on metal foils presents a promising route toward mass production of high-performance CNT devices for a broad range of applications.

Energy↗
DOE OSTI2022

Effects of short-interval reburns in the boreal forest on soil bacterial communities compared to long-interval reburns

Abstract Increasing fire frequency in some biomes is leading to fires burning in close succession, triggering rapid vegetation change and altering soil properties. We studied the effects of short-interval (SI) reburns on soil bacterial communities of the boreal forest of northwestern Canada using paired sites (n = 44). Both sites in each pair had burned in a recent fire; one site had burned within the previous 20 years before the recent fire (SI reburn) and the other had not. Paired sites were closely matched in prefire ecosite characteristics, prefire tree species composition, and stand structure. We hypothesized that there would be a significant effect of short vs. long fire-free intervals on community composition and that richness would not be consistently different between paired sites. We found that Blastococcus sp. was consistently enriched in SI reburns, indicating its role as a strongly ‘pyrophilous’ bacterium. Caballeronia sordidicola was consistently depleted in SI reburns. The depletion of this endophytic diazotroph raises questions about whether this is contributing to—or merely reflects—poor conifer seedling recolonization post-fire at SI reburns. While SI reburns had no significant effect on richness, dissimilarity between short- and long-interval pairs was significantly correlated with difference in soil pH, and there were small significant changes in overall community composition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Improving Effective Mass Estimations in Pu-Metal Annuli

Determining the effective mass of 240 Pu in a plutonium metal item can be achieved through a number of destructive and non-destructive assay techniques. However, these techniques have one or more shortcomings. These include the need for large quantities of plutonium, long measurement time, or lack of sufficient accuracy. While efforts have been made to mitigate these issues by estimating 240 Pu quantities through neutron coincidence counting techniques, these estimates are subject to systematic bias, and their estimates are not well characterized when other factors of the annulus’ physical form and composition are accounted for. In this work, we expand upon these non-destructive assay techniques via the implementation of random forest machine learning models, which produce correction functions that augment and improve the effective mass estimates derived from classical leakage multiplication, singles, doubles, and triples multiplicity counting equations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1975

Detecting Disturbances in a Forest Environment

The interchange between forest and nonforest land and most man-made and natural forest disturbances can be detected on 1:120,000-scale color-infrared film. Bulk multispectral scanner imagery from the Earth Resources Technology Satellite combined and enhanced at a scale of 1:1,000,000 shows major changes in forest and nonforest land-use categories, many timber harvested areas, and some natural disturbances. Late fall to late spring is the best period of the year for detecting forest disturbances. In a study in Georgia, 79 percent of the disturbances in one county were detected on an ERTS color composite for April 1973 with only 12 percent commission error.

Aldrich, R. C.↗
NASA NTRS1991

Advanced Solid-State Array Spectrometer (ASAS) data sets from the 1990 field season: A unique look at two forested ecosystems

The Advanced Solid-state Array Spectrometer (ASAS) is a pointable imaging spectrometer which uses a solid-state array to acquire imagery of terrestrial targets in 29 spectral bands from .4 to .8 microns. Performance and calibration of the instrument are described. The ASAS data sets obtained in 1990 provide a unique look at forest canopies from two different forest regions of the North America continent under varying temporal, spectral, and bidirectional conditions. These data sets will be used to study such parameters as the albedo of forest canopies, the dynamics of scene radiation due to factors such as canopy architecture, moisture stress, leaf chemistry, topography, and understory composition.

Walthall, Charles L.↗
NASA NTRS1993

Extended ecosystem signatures with application to Eos synergism requirements

The primary objective is to define the advantages of synergistically combining optical and microwave remote sensing measurements for the determination of biophysical properties important in ecosystem modeling. This objective was approached in a stepwise fashion starting with ground-based observations of controlled agricultural and orchard canopies and progressing to airborne observations of more natural forest ecosystems. This observational program is complemented by a parallel effort to model the visible reflectance and microwave scattering properties of composite vegetation canopies. The goals of the modeling studies are to verify our basic understanding of the sensor-scene interaction physics and to provide the basis for development of inverse models optimized for retrieval of key biophysical properties. These retrieval algorithms can then be used to simulate the expected performance of various aspects of Eos including the need for simultaneous SAR and HIRIS observations or justification for other (non-synchronous) relative timing constraints and the frequency, polarization, and angle of incidence requirements for accurate biophysical parameter extractions. This program completed a very successful series of truck-mounted experiments, made remarkable progress in development and validation of optical reflectance and microwave scattering models for vegetation, extended the scattering models to accommodate discontinuous and periodic canopies, developed inversion approaches for surface and canopy properties, and disseminated these results widely through symposia and journal publications. In addition, the third generation of the computer code for the microwave scattering models was provided to a number of other US, Canadian, Australian, and European investigators who are currently presenting and publishing results using the MIMICS research code.

Ulaby, Fawwaz T.↗
NASA NTRS2007

Advanced Airfoils Boost Helicopter Performance

Carson Helicopters Inc. licensed the Langley RC4 series of airfoils in 1993 to develop a replacement main rotor blade for their Sikorsky S-61 helicopters. The company's fleet of S-61 helicopters has been rebuilt to include Langley's patented airfoil design, and the helicopters are now able to carry heavier loads and fly faster and farther, and the main rotor blades have twice the previous service life. In aerial firefighting, the performance-boosting airfoils have helped the U.S. Department of Agriculture's Forest Service control the spread of wildfires. In 2003, Carson Helicopters signed a contract with Ducommun AeroStructures Inc., to manufacture the composite blades for Carson Helicopters to sell

Source record↗
NASA NTRS2015

Quantifying Sources and Sinks of Reactive Gases in the Lower Atmosphere Using Airborne Flux Observations

Atmospheric composition is governed by the interplay of emissions, chemistry, deposition, and transport. Substantial questions surround each of these processes, especially in forested environments with strong biogenic emissions. Utilizing aircraft observations acquired over a forest in the southeast U.S., we calculate eddy covariance fluxes for a suite of reactive gases and apply the synergistic information derived from this analysis to quantify emission and deposition fluxes, oxidant concentrations, aerosol uptake coefficients, and other key parameters. Evaluation of results against state-of-the-science models and parameterizations provides insight into our current understanding of this system and frames future observational priorities. As a near-direct measurement of fundamental process rates, airborne fluxes offer a new tool to improve biogenic and anthropogenic emissions inventories, photochemical mechanisms, and deposition parameterizations.

emission↗
NASA NTRS2003

Ectomycorrhizal Community Structure and Soil Characteristics of Mature Lodgepole Pine (Pinus Contorta) and Adjacent Stands of Old Growth Mixed Conifer in Yellowstone National Park, Wyoming USA

Forest development patterns following disturbance are known to influence the physical and chemical attributes of soils at different points in time. Changes in soil resources are thought to have a corresponding effect on ectomycorrhizal (ECM) community structure. We used molecular methods to compare below-ground ECM species richness, composition, and abundance between adjacent stands of homogenous lodgepole pine and old growth mixed conifer in Yellowstone National Park (YNP). In each stand-type we collected soil cores to both identify mycorrhizae and assess soil chemistry. Although no statistical difference was observed in the mean number of ECM root tips per core between stand types, the total number of species identified (85 versus 35) and the mean number of species per core (8.8 +/- 0.6 versus 2.5 +/- 0.3) were significantly higher in lodgepole pine. Differences between the actual and estimated species richness levels indicated that these forest types support a high number of ECM species and that undersampling was severe. Species compositions were widely disparate between stands where only four species were shared out of a total of 116. Soil analysis also revealed that mixed conifer was significantly lower in pH, but higher in organic matter, potassium, phosphorus, and ammonium when compared to lodgepole pine stands. Species richness per core was correlated with these chemical data, however, analysis of covariance indicated that stand type was the only statistically significant factor in the observed difference in species richness. Our data suggest that ECM fungal richness increases as homogenous lodgepole pine stands grow and mature, but declines after Engelmann spruce and subalpine fir colonize. Despite difficulties linking species composition with soil chemistry, there are a variety of physical and chemical factors that could be influencing ECM community structure. Future field experiments are necessary to test some of the mechanisms potentially operating within this system.

Douglas, Robert B.↗
NASA NTRS2007

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

This report details one of three experiments performed during FY 2007 for the NASA RPC (Rapid Prototyping Capability) at Stennis Space Center. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria dispar). The intent of the RPC experiment was to assess the degree to which VIIRS data can provide forest disturbance monitoring information as an input to a forest threat EWS (Early Warning System) as compared to the level of information that can be obtained from MODIS data. The USDA Forest Service (USFS) plans to use MODIS products for generating broad-scaled, regional monitoring products as input to an EWS for forest health threat assessment. NASA SSC is helping the USFS to evaluate and integrate currently available satellite remote sensing technologies and data products for the EWS, including the use of MODIS products for regional monitoring of forest disturbance. Gypsy moth defoliation of the mid-Appalachian highland region was selected as a case study. Gypsy moth is one of eight major forest insect threats listed in the Healthy Forest Restoration Act (HFRA) of 2003; the gypsy moth threatens eastern U.S. hardwood forests, which are also a concern highlighted in the HFRA of 2003. This region was selected for the project because extensive gypsy moth defoliation occurred there over multiple years during the MODIS operational period. This RPC experiment is relevant to several nationally important mapping applications, including agricultural efficiency, coastal management, ecological forecasting, disaster management, and carbon management. In this experiment, MODIS data and VIIRS data simulated from MODIS were assessed for their ability to contribute broad, regional geospatial information on gypsy moth defoliation. Landsat and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data were used to assess the quality of gypsy moth defoliation mapping products derived from MODIS data and from simulated VIIRS data. The project focused on use of data from MODIS Terra as opposed to MODIS Aqua mainly because only MODIS Terra data was collected during 2000 and 2001-years with comparatively high amounts of gypsy moth defoliation within the study area. The project assessed the quality of VIIRS data simulation products. Hyperion data was employed to assess the quality of MODIS-based VIIRS simulation datasets using image correlation analysis techniques. The ART (Application Research Toolbox) software was used for data simulation. Correlation analysis between MODIS-simulated VIIRS data and Hyperion-simulated VIIRS data for red, NIR (near-infrared), and NDVI (Normalized Difference Vegetation Index) image data products collectively indicate that useful, effective VIIRS simulations can be produced using Hyperion and MODIS data sources. The r(exp 2) for red, NIR, and NDVI products were 0.56, 0.63, and 0.62, respectively, indicating a moderately high correlation between the 2 data sources. Temporal decorrelation from different data acquisition times and image misregistration may have lowered correlation results. The RPC experiment also generated MODIS-based time series data products using the TSPT (Time Series Product Tool) software. Time series of simulated VIIRS NDVI products were produced at approximately 400-meter resolution GSD (Ground Sampling Distance) at nadir for comparison to MODIS NDVI products at either 250- or 500-meter GSD. The project also computed MODIS (MOD02) NDMI (Normalized Difference Moisture Index) products at 500-meter GSD for comparison to NDVI-based products. For each year during 2000-2006, MODIS and VIIRS (simulated from MOD02) time series were computed during the peak gypsy moth defoliation time frame in the study area (approximately June 10 through July 27). Gypsy moth defoliation mapping products from simated VIIRS and MOD02 time series were produced using multiple methods, including image classification and change detection via image differencing. The latter enabled an automated defoliation detection product computed using percent change in maximum NDVI for a peak defoliation period during 2001 compared to maximum NDVI across the entire 2000-2006 time frame. Final gypsy moth defoliation mapping products were assessed for accuracy using randomly sampled locations found on available geospatial reference data (Landsat and ASTER data in conjunction with defoliation map data from the USFS). Extensive gypsy moth defoliation patches were evident on screen displays of multitemporal color composites derived from MODIS data and from simulated VIIRS vegetation index data. Such defoliation was particularly evident for 2001, although widespread denuded forests were also seen for 2000 and 2003. These visualizations were validated using aforementioned reference data. Defoliation patches were visible on displays of MODIS-based NDVI and NDMI data. The viewing of apparent defoliation patches on all of these products necessitated adoption of a specialized temporal data processing method (e.g., maximum NDVI during the peak defoliation time frame). The frequency of cloud cover necessitated this approach. Multitemporal simulated VIIRS and MODIS Terra data both produced effective general classifications of defoliated forest versus other land cover. For 2001, the MOD02-simulated VIIRS 400-meter NDVI classification produced a similar yet slightly lower overall accuracy (87.28 percent with 0.72 Kappa) than the MOD02 250-meter NDVI classification (88.44 percent with 0.75 Kappa). The MOD13 250-meter NDVI classification had a lower overall accuracy (79.13 percent) and a much lower Kappa (0.46). The report discusses accuracy assessment results in much more detail, comparing overall classification and individual class accuracy statistics for simulated VIIRS 400-meter NDVI, MOD02 250-meter NDVI, MOD02-500 meter NDVI, MOD13 250-meter NDVI, and MOD02 500-meter NDMI classifications. Automated defoliation detection products from simulated VIIRS and MOD02 data for 2001 also yielded similar, relatively high overall classification accuracy (85.55 percent for the VIIRS 400-meter NDVI versus 87.28 percent for the MOD02 250-meter NDVI). In contrast, the USFS aerial sketch map of gypsy moth defoliation showed a lower overall classification accuracy at 73.64 percent. The overall classification Kappa values were also similar for the VIIRS (approximately 0.67 Kappa) versus the MOD02 (approximately 0.72 Kappa) automated defoliation detection product, which were much higher than the values exhibited by the USFS sketch map product (overall Kappa of approximately 0.47). The report provides additional details on the accuracy of automated gypsy moth defoliation detection products compared with USFS sketch maps. The results suggest that VIIRS data can be effectively simulated from MODIS data and that VIIRS data will produce gypsy moth defoliation mapping products that are similar to MODIS-based products. The results of the RPC experiment indicate that VIIRS and MODIS data products have good potential for integration into the forest threat EWS. The accuracy assessment was performed only for 2001 because of time constraints and a relative scarcity of cloud-free Landsat and ASTER data for the peak defoliation period of the other years in the 2000-2006 time series. Additional work should be performed to assess the accuracy of gypsy moth defoliation detection products for additional years.The study area (mid-Appalachian highlands) and application (gypsy moth forest defoliation) are not necessarily representative of all forested regions and of all forest threat disturbance agents. Additional work should be performed on other inland and coastal regions as well as for other major forest threats.

Spruce, Joseph P.↗
DOE OSTI2022

Predicting oxidation damage in ultra high-temperature borides: A machine learning approach

Ultra-high temperature (UHT) borides are ceramics materials with melting points above 3000 °C for structural applications in extreme environments. However, at temperatures exceeding 1600 °C and under oxidizing conditions, the material suffers from detrimental degradation. Optimized design and performance of diboride materials under such extreme conditions requires filling the missing composition-microstructure-oxidation gap. This study proposes a computational data-driven framework to connect the processing and microstructure of Ultra-high temperature borides with the oxidation damage. Random Forest Regressor (RFR) model is adopted to forecast the oxide scale thickness developed after oxidation testing based on processing variables and microstructural features. The model trained on a dataset consisting of 107 samples of experimental data extracted from the literature aims to predict oxidation damage. With proper data manipulation and fine model tuning, the predictor could forecast the oxide scale thickness of UHT diborides with a Mean Absolute Error of 37.45 μm and an R-square of 0.83. This model could be used as a high-throughput scheme to design and test new UHT diborides materials computationally. Furthermore, a model with larger composition capabilities could also be developed in the future as more experimental data become available.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Multitemporal diurnal AVIRIS images of a forested ecosystem

Both physiological and ecosystem structural information may be derived from diurnal images. Structural information may be inferred from changes in canopy shadows between images and from changes in spectral composition due to changes in proportions of subpixel mixing resulting from the differences in sun/view angles. Physiological processes having diurnal scales also may be measurable if a stable basis for spectral comparison can be established. Six diurnal images of an area east of Mt. Shasta, CA were acquired on 22 Sep. 1989. This unique diurnal data set provided an opportunity to test the consistency of endmember fractions and residuals. It was expected that shade endmember abundances would show the greatest change as lighting geometry changed and less change in the normalized fractional proportion of other endmembers. Diurnal changes in spectral features related to physiological characteristics may be identifiable as changes in wavelength specific residuals.

Ustin, Susan L.↗
NASA NTRS2008

Strain and Temperature Sensing Properties of Multiwalled Carbon Nanotube Yarn Composites

Strain and temperature response of Multiwalled Carbon Nanotube (MWCNT/CNT) yarns on a stainless steel test beam has been studied. The carbon nanotube yarns are spun from a multiwalled carbon nanotube forest grown on a silicon substrate to a 4-ply yarn with a diameter of about 15-20 microns. Four of the 4-ply CNT yarns are arranged in a Wheatstone bridge configuration on the stainless steel test beam using a thin layer of polyurethane resin that insulates and protects the yarns from the test beam. Strain sensitivities of the CNT yarn sensors range from 1.39 to 1.75 mV/V/1000 microstrain at room temperature, and temperature sensitivity of the CNT yarn bridge is 91 microA/degC. Resistance of the yarns range from 215 to 270 ohms for CNT yarn length of approximately 5 mm. Processes used in attaching the CNT yarns on the test beam and experimental procedures used for the measurements are described. Conventional metallic foil strain gages are attached to the test beam to compare with the CNT sensors. The study demonstrates multifunctional capability of the sensor for strain and temperature measurements and shows its applicability where engineering strain is less than 3%.

Kahng, Seun K.↗
DOE OSTI2024

Methane-cycling microbial communities from Amazon floodplains and upland forests respond differently to simulated climate change scenarios

Seasonal floodplains in the Amazon basin are important sources of methane (CH 4 ), while upland forests are known for their sink capacity. Climate change effects, including shifts in rainfall patterns and rising temperatures, may alter the functionality of soil microbial communities, leading to uncertain changes in CH 4 cycling dynamics. To investigate the microbial feedback under climate change scenarios, we performed a microcosm experiment using soils from two floodplains (i.e., Amazonas and Tapajós rivers) and one upland forest. We employed a two-factorial experimental design comprising flooding (with non-flooded control) and temperature (at 27 °C and 30 °C, representing a 3 °C increase) as variables. We assessed prokaryotic community dynamics over 30 days using 16S rRNA gene sequencing and qPCR. These data were integrated with chemical properties, CH 4 fluxes, and isotopic values and signatures. In the floodplains, temperature changes did not significantly affect the overall microbial composition and CH 4 fluxes. CH 4 emissions and uptake in response to flooding and non-flooding conditions, respectively, were observed in the floodplain soils. By contrast, in the upland forest, the higher temperature caused a sink-to-source shift under flooding conditions and reduced CH 4 sink capability under dry conditions. The upland soil microbial communities also changed in response to increased temperature, with a higher percentage of specialist microbes observed. Floodplains showed higher total and relative abundances of methanogenic and methanotrophic microbes compared to forest soils. Isotopic data from some flooded samples from the Amazonas river floodplain indicated CH 4 oxidation metabolism. This floodplain also showed a high relative abundance of aerobic and anaerobic CH 4 oxidizing Bacteria and Archaea. Taken together, our data indicate that CH 4 cycle dynamics and microbial communities in Amazonian floodplain and upland forest soils may respond differently to climate change effects. We also highlight the potential role of CH 4 oxidation pathways in mitigating CH 4 emissions in Amazonian floodplains.

16S rRNA sequencing↗
DOE OSTI2022

Integrating very-high-resolution UAS data and airborne imaging spectroscopy to map the fractional composition of Arctic plant functional types in Western Alaska

Widespread changes in vegetation cover and composition are driving strong impacts on Arctic ecosystem functioning and global climate feedbacks. An accurate characterization of tundra vegetation composition is required to understand how the Arctic will respond to future climate change. However, quantifying tundra vegetation composition over large areas is challenging as commonly-used satellite observations are too coarse, spatially and spectrally, to differentiate low-lying tundra vegetation types. Recent airborne and spaceborne imaging spectroscopy platforms provide better data to characterize vegetation composition. Yet, our ability to characterize vegetation composition with imaging spectroscopy remains largely unexplored in the Arctic, particularly due to a lack of ground observations needed to train and test classification models. To address this problem, we collected very-high-resolution (VHR, ~5 cm) unoccupied aerial system (UAS) imagery at three low-Arctic tundra sites located on the Seward Peninsula, western Alaska. In this paper, we examine the feasibility of integrating imagery from the UAS and the hyperspectral Airborne Visible/Infrared Imaging Spectrometer, Next Generation (AVIRIS-NG) airborne instrument to map the fractional composition of 12 key Arctic plant functional types (PFTs). To this end, we first mapped the 12 PFTs from our VHR UAS imagery using random forest classification. We then used these UAS-derived PFT maps as ground truth to develop partial least squares regression (PLSR) models to predict the fractional cover (FCover) of each PFT from AVIRIS-NG imagery. Further, we evaluated the performance of our PLSR models using reserved UAS samples, as well as by mapping PFT FCover and dominant PFT for large tundra landscapes. Our results show that 1) Arctic PFTs can be effectively mapped using VHR UAS imagery, with overall accuracy between 86% and 92%, 2) when the UAS mapped PFTs were used to inform PLSR scaling models, the FCover of the 12 PFTs could be effectively estimated from AVIRIS-NG imagery with a mean absolute error (MAE) <0.13, and 3) our PLSR models outperformed traditional, fully constrained least-squares (FCLS) linear mixture analysis and produced high-quality, spatially contiguous PFT FCover and PFT maps that captured vegetation spatial patterns with similar accuracy to those developed from UAS imagery. The developed PLSR models have the potential to be broadly applied for quantifying vegetation composition with AVIRIS-NG images to help monitor tundra vegetation dynamics and improve process-based modeling of tundra ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Exploring viral particle, soil, and extraction buffer physicochemical characteristics and their impacts on extractable viral communities

Viruses are expected to be pivotal members of soil ecosystems, and recent advances in viral size fraction metagenomic (viromic) approaches have improved our ability to interrogate soil viral ecology. However, viromics relies on extraction buffers to effectively desorb viral particles from the soil matrix for downstream analysis, and viral extraction efficiency could be affected by the interplay between viral particles, soils, and extraction buffer chemistry. Here, we investigated whether extraction buffer chemistry affected extractable viral community composition measured by viromics from different soil types, for both biological (samples collected 1 m apart) and technical (subsamples from the same soil homogenate) replicates. We investigated pH manipulation of protein-supplemented phosphate-buffered saline buffer (PPBS, pHs 4.5, 5.5, 6.5, and 7.5) on forest, grassland and wetland soils that exhibited different soil edaphic properties, and we tested different buffer chemistries (PPBS, Carbonated Buffer, Glycine, and Saline Magnesium) on just the wetland soil. Spatial distance (i.e., biological replicate) was the primary driver of extractable viral community composition across all buffers and soils tested. Differences in viral community composition according to extraction buffer properties were only observed in the grassland technical replicates at PPBS buffer pH 4.5, and in both the wetland technical and biological replicates treated with different buffer chemistries, but the effects of buffer chemistry were secondary to spatial distance in the biological replicates. The lack of buffering capacity in the grassland soil technical replicates likely increased sorption of viral particles at pH 4.5, but neither protein composition nor isoelectric point explained this phenomenon. In conclusion, given that most soil viral ecological studies to date include sample collection over distances much farther apart than the 1-m distances considered here, results suggest that extraction buffer chemistry is likely of much lower importance than ecological considerations, such as spatial distance, in the design of future soil viral ecological investigations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Wi3 Mature hardwood (MHW)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Wi3 Mature hardwood (MHW). This is the FLUXNET version of the carbon flux data for the site US-Wi3 Mature hardwood (MHW) produced by applying the standard ONEFlux (1F) software. Site Description - The Wisconsin Mature Hardwood site is located in the Washburn Ranger District of the northeastern section of Chequamegon National Forest. A member of the northern coniferous-deciduous biome, surveys from the mid-19th century indicate the region consisted of a mixed stand of red, white, and jack pines. After extensive timber harvesting, wildfires, and farming activity, the region turned into a fragmented mosaic of stands of various ages and composition. As an assemblage, the ten Wisconsin sites are indicative of the successional stages of development in the predominant stand types of a physically homogeneous landscape. The mature hardwood stand represents a typical naturally regenerated second-growth forest, free of anthropogenic disturbances for at least 70 years.

Chen, Jiquan↗