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DOE OSTI2024

Total Water Level Prediction at Continental Scale: Coastal Ocean

We demonstrate recent progress made in the simulation of total water level (TWL) at continental scale, using the coastal ocean of US East Coast/Gulf of Mexico coast as an example. A key difference between the continental-scale and small-scale modeling is that the former requires a more accurate vertical datum. Using a geoid-based datum (xGEOID20b), a satellite altimetry product, and a state-of-the-art 3D unstructured-grid model, we significantly improve the accuracy for TWL both near- and off-shore. The average root-mean-square error at all NOAA stations is 14 cm. The non-tidal signals are found to be sensitive to the representation of a large-scale current system near the boundary and extending the domain extent to accommodate this system improves these signals.

Cui, Linlin↗

DOE OSTI2022

Chronic drought differentially alters the belowground microbiome of drought tolerant and drought susceptible genotypes of Populus trichocarpa

Populus trichocarpa is an ecologically important tree species and economically important biofeedstock. Belowground, P. trichocarpa interacts with diverse microorganisms in the rhizosphere and root endosphere. These plant-microbial interactions can bolster a variety of plant processes, ranging from pathogen suppression to drought tolerance, yet we know little about the impact of chronic drought stress on P. trichocarpa’s belowground microbiomes. To investigate the interactive effect of chronic drought on belowground microbial communities across genetically different P. trichocarpa hosts, we assessed archaeal/bacterial and fungal communities within the root endosphere, rhizosphere, and surrounding bulk soil of selected genotypes in a long-term drought experiment in Boardman, OR, USA. We sequenced the 16S rRNA and ITS2 gene region on samples collected from 16 distinct P. trichocarpa genotypes in plots with full or reduced irrigation. Eight of these genotypes have been previously identified as drought tolerant while the other eight genotypes were drought susceptible. While reduced irrigation influenced the composition of every archaeal/bacterial microbiome compartment, fungal communities were only affected in the rhizosphere and bulk soil compartments. Drought-tolerant bacteria, such as Actinobacteria, were differentially abundant in reduced irrigation across all belowground microbiomes. Host drought-tolerance influenced plant-associated microbiome compartments but had little impact on the bulk soil compartment. Drought-tolerant trees were enriched for potential growth-promoting microorganisms in the root endosphere and rhizosphere, including Sphingomonas bacteria and ectomycorrhizal fungi. Overall, associations of growth-promoting microbes in drought resistant P. trichocarpa genotypes can be leveraged to improve biofeedstock productivity in regions prone to periodic drought.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1980

X-ray technique verifies weld-root fusion

Small holes drilled along back edge of surface to be joined are filled when weld root is adequately fused. Holes 2% of thickness of material can be detected with X-rays. Absence of detectable holes indicates good weld. Procedure has been proven in production and is more reliable than conventional X-ray methods.

Kleint, R. E.↗

NASA NTRS1981

Development of guayule (Parthenium argentatum) research in cell culture

Utilizing the lateral buds of known high rubber producing plants as explants in culture medium specifically designed to engender shoot development and to prevent callus formation, unlimited numbers of replicate plants can be produced. Each has the same genotype as the parent. This procedure has long been used to rid plants of virus, the latter generally does not occur in the embryonic tissues of the bud; it also, by virtue of its axenic nature, eliminates all microorganisms characteristic of the parent plant. Auxins were found essential to callus formation, but since the latter is known to bring about chromosomal aberrations, it was avoided. The cytokinin benzylaminopurine strongly stimulated shoot growth, and the number of regenerated buds on the inoculum was proportional to its concentration. These buds produced shoots several centimeters in length which were caused to root on medium containing indolebutyric acid. Transferred to the septic condition of soil, the plantlets were gradually brought into full sunlight where they showed a brief vegetative growth with production of mature leaves, and flowered.

Ball, E. A.↗

NASA NTRS1987

On the role of convective motion during dendrite growth: Experiments under variable gravity, revised

Experiments show the effect of self induced convection on individual dendrite growth in uniformly supercooled samples and solidification of the resulting mush under conditions of high and low g. Convection is visualized by a Schlieren optical system or a Mach Zender interferometer. For ice crystals growing from the vapor in air, a slight reduction in linear growth rate occur under low g. For ice crystals growing from NaCl solution, dendrite tip velocities are unchanged, but subsequent mush solidification is enhanced through drainage channels under higher g. By contrast, sodium sulfate decahydrate dendrites growing from solution produce convective plumes which lead to higher tip growth rate only as the crystal growth direction approaches that of gravity. Convective plumes are laminar for small crystals under conditions of these experiments; the rise velocity of such plumes is greater than individual vortex rings under identical conditions. Convection effects are only present in solution under a critical supercooling less than about 5 C for sodium sulfate and 2 C for ice in NaCl since at higher supercooling the crystallization velocity, proportional to the square of the supercooling, exceeds the convective velocity, proportional to the square root of the supercooling. The role of convective velocity in bulk solidification is to give a large scale flow which under extreme cases may lead to extensive secondary crystal production, which alters the resulting crystal texture of the completely solidified melt.

Hallett, J.↗

NASA NTRS1994

Immunolocalization of an annexin-like protein in corn

Although calcium has been proposed to be an important regulatory element in plant gravitropic growth, as yet no specific function of Ca2(+) in growth regulation has been discovered. Our recent studies on a Ca2(+)-binding protein in pea seedlings called p35 indicate that it is a member of the annexin family of proteins and may play a key role in growth regulation through its function in delivering polysaccharides needed for wall construction. We previously reported the isolation of p35 from pea plumules and the production of polyclonal antibodies to it. Immunolocalization analyses of p35 in pea tissues revealed high levels of staining in secretory cell types such as developing vascular cells and outer root cap cells. To test how general was the occurrence and distribution of this annexin-like protein in plant cells we initiated an analysis of annexins in the monocot corn using immunological techniques. Our results indicate the immunochemical properties and localization of corn annexins are very similar to those reported for pea. They are consistent with the postulate that annexins may play a general role in the regulation of the secretion of wall polysaccharides needed for growth, and thus could be an important target of calcium action during gravitropic growth.

Clark, G. B.↗

NASA NTRS2022

Evaluation of High Mountain Asia-Land Data Assimilation System (version 1) from 2003 to 2016: 2. The impact of assimilating satellite-based snow cover and freeze/thaw observations into a land surface model

This second paper of the two-part series focuses on demonstrating the impact of assimilating satellite-based snow cover and freeze/thaw observations into the hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0.01° (∼1 km) model simulations forced by different precipitation forcings, with and without the dual assimilation scheme enabled, at point-scale, basin-scale, and domain-scale. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent (SWE), and total runoff. First, the point-scale assessment is mainly conducted via evaluating against ground-based measurements. In general, the assimilation enabled estimates are better than no-assimilation counterparts. Second, the basin-scale runoff assessment demonstrates that across three snow-dominated basins, the assimilation enabled experiment yields systematic improvements in all goodness-of-fit statistics through mitigating the negative effects brought by the fixed long-term precipitation correction factors. For example, when forced by the bias-corrected precipitation, the assimilation-enabled experiment improves the bias by 69%, the root-mean-squared error by 30%, and the unbiased root-mean-squared error by 18% (relative to the no-assimilation counterpart). Finally, the domainscale assessment is conducted via evaluating against satellite-based SWE and skin temperature products. Both sets of domain-scale analysis further corroborate the findings in the point-scale evaluations. Overall, this study suggests the benefits of the proposed multi-variate assimilation system in improving the cryospherichydrological process within a land surface model for use in HMA.

Yuan Xue↗

DOE OSTI2023

Amino mapping: possibility to visualize amino-N compounds in the rhizosphere of Zea Mays L.

Abstract Understanding N uptake by plants, the N cycle, and their relationship to soil heterogeneity has generated a great deal of interest in the distribution of amino-N compounds in soil. Visualization of the spatial distribution of amino-N in soil can provide insights into the role of labile N in plant-microbial mechanisms of N acquisition and plant N uptake, but until now, it has remained technically challenging. Here, we describe a novel technique to visualize the amino-N distribution at the root-soil interface. The technique is based on time-lapse amino mapping (TLAM) using membranes saturated with the fluorogenic OPAME reagent (O-phthalaldehyde and β-mercaptoethanol). OPAME in the membrane reacts with organic compounds containing a NH 2 functional group at the membrane-soil interface, generating a fluorescent product visible under UV light and detectable by a digital camera. The TLAM amino-mapping technique was applied to visualize and quantify the concentration of amino-N compounds in the rhizosphere of maize (Zea MaysL.). A ten times greater amino-N concentration was detected in the rhizosphere compared to non-rhizosphere soil. The high content of amino-N was mainly associated with the root tips and was 3 times larger than the average amino-N content at seminal roots. The amino-N rhizosphere was 2 times broader around the root tips than around other parts of the roots. We concluded that TLAM is a promising approach for monitoring the fate of labile N in soils. However, the technique needs to be standardized for different soil types, plant species, and climate conditions to allow wider application.

Agriculture↗

NASA NTRS2018

Recent Updates in the SMAP Level-4 Soil Moisture Algorithm

The NASA Soil Moisture Active Passive (SMAP) mission generates, among other data sets, the Level-4 Soil Moisture (L4_SM) product. The L4_SM data are published with a mean latency of ~2.5 days from the time of observation and provide global, three-hourly, 9-km resolution estimates of surface and root-zone soil moisture and related land surface states and fluxes. The L4_SM algorithm is based on the assimilation of SMAP radiometer brightness temperature observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter (EnKF). In 2018, the L4_SM algorithm was upgraded from Version 3 to Version 4. Underlying the new version is a revised modeling system that includes improved input parameter datasets for land cover, topography, and vegetation height that are based on recent, high-quality, space-borne remote sensing observations. Additionally, SMAP Level-2 soil moisture retrievals and in situ soil moisture measurements were used to calibrate a particular Catchment model parameter that governs the recharge of surface soil moisture from below under non-equilibrium conditions, which brings the model's surface soil moisture more in line with the SMAP Level-2 and in situ soil moisture. Moreover, the calibration of the assimilated SMAP brightness temperatures changed substantially from Version 3 to Version 4, and the "catchment deficit" model variable was removed from the EnKF state vector to avoid degrading the model's groundwater estimates.Considerable effort went into the version upgrade, creating an expectation that the new version is improved over the old version. Indeed, some aspects of the new version are clearly better. However, other aspects are not. In this presentation we summarize the skill of the new and old versions vs. independent in situ measurements and in terms of data assimilation diagnostics, including, for example, the statistics of the (soil moisture) analysis increments and the observation-minus-forecast (brightness temperatures) residuals. We share our experience with trying to improve to the L4_SM product and the lessons learned from the effort.

Reichle, Rolf H.↗

DOE OSTI2024

Drilling Down I/O Bottlenecks with Cross-layer I/O Profile Exploration

I/O performance monitoring tools such as Darshan and Recorder collect I/O-related metrics on production systems and help understand the applications' behavior. However, some gaps prevent end-users from seeing the whole picture when it comes to detecting and drilling down to the root causes of I/O performance slowdowns and where those problems originate. These gaps arise from limitations in the available metrics, their collection strategy, and the lack of translation to actionable items that could advise on optimizations. This paper highlights such gaps and proposes solutions to drill down to the source code level to pinpoint the root causes of I/O bottlenecks scientific applications face by relying on cross-layer analysis combining multiple performance metrics related to I/O software layers. We demonstrate with two real applications how metrics collected in high-level libraries (which are closer to the data models used by an application), enhanced by source-code insights and natural language translations, can help streamline the understanding of I/O behavior and provide guidance to end-users, developers, and supercomputing facilities on how to improve I/O performance. Using this cross-layer analysis and the heuristic recommendations, we attained up to 6.9× speedup from run-as-is executions.

Ather, Hammad↗

DOE OSTI2023

Improved Biofuel Production through Discovery and Engineering of Terpene Metabolism in Switchgrass

Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.

09 BIOMASS FUELS↗

NASA NTRS1987

Occurrence and metabolism of 7-hydroxy-2-indolinone-3-acetic acid in Zea mays

7-Hydroxy-2-indolinone-3-acetic acid was identified as a catabolite of indole-3-acetic acid in germinating kernels of Zea mays and found to be present in amounts of ca 3.1 nmol/kernel. 7-Hydroxy-2-indolinone-3-acetic acid was shown to be a biosynthetic intermediate between 2-indolinone-3-acetic acid and 7-hydroxy-2-indolinone-3-acetic acid-7'-O-glucoside in both kernels and roots of Zea mays. Further metabolism of 7-hydroxy-2-[5-3H]-indolinone-3-acetic acid-7'-O-glucoside occurred to yield tritiated water plus, as yet, uncharacterized products.

NASA Program Space Biology↗

NASA NTRS2012

Automated Sequence Processor: Something Old, Something New

High productivity required for operations teams to meet schedules Risk must be minimized. Scripting used to automate processes. Scripts perform essential operations functions. Automated Sequence Processor (ASP) was a grass-roots task built to automate the command uplink process System engineering task for ASP revitalization organized. ASP is a set of approximately 200 scripts written in Perl, C Shell, AWK and other scripting languages.. ASP processes/checks/packages non-interactive commands automatically.. Non-interactive commands are guaranteed to be safe and have been checked by hardware or software simulators.. ASP checks that commands are non-interactive.. ASP processes the commands through a command. simulator and then packages them if there are no errors.. ASP must be active 24 hours/day, 7 days/week..

Automated↗

NASA NTRS2015

Space Technology Mission Directorate: Game Changing Development

NASA and the aerospace community have deep roots in manufacturing technology and innovation. Through it's Game Changing Development Program and the Advanced Manufacturing Technology Project NASA develops and matures innovative, low-cost manufacturing processes and products. Launch vehicle propulsion systems are a particular area of interest since they typically comprise a large percentage of the total vehicle cost and development schedule. NASA is currently working to develop and utilize emerging technologies such as additive manufacturing (i.e. 3D printing) and computational materials and processing tools that could dramatically improve affordability, capability, and reduce schedule for rocket propulsion hardware.

Gaddis, Stephen W.↗

NASA NTRS2011

Modeling the Height of Young Forests Regenerating from Recent Disturbances in Mississippi using Landsat and ICESat data

Many forestry and earth science applications require spatially detailed forest height data sets. Among the various remote sensing technologies, lidar offers the most potential for obtaining reliable height measurement. However, existing and planned spaceborne lidar systems do not have the capability to produce spatially contiguous, fine resolution forest height maps over large areas. This paper describes a Landsat-lidar fusion approach for modeling the height of young forests by integrating historical Landsat observations with lidar data acquired by the Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud, and land Elevation (ICESat) satellite. In this approach, "young" forests refer to forests reestablished following recent disturbances mapped using Landsat time-series stacks (LTSS) and a vegetation change tracker (VCT) algorithm. The GLAS lidar data is used to retrieve forest height at sample locations represented by the footprints of the lidar data. These samples are used to establish relationships between lidar-based forest height measurements and LTSS-VCT disturbance products. The height of "young" forest is then mapped based on the derived relationships and the LTSS-VCT disturbance products. This approach was developed and tested over the state of Mississippi. Of the various models evaluated, a regression tree model predicting forest height from age since disturbance and three cumulative indices produced by the LTSS-VCT method yielded the lowest cross validation error. The R(exp 2) and root mean square difference (RMSD) between predicted and GLAS-based height measurements were 0.91 and 1.97 m, respectively. Predictions of this model had much higher errors than indicated by cross validation analysis when evaluated using field plot data collected through the Forest Inventory and Analysis Program of USDA Forest Service. Much of these errors were due to a lack of separation between stand clearing and non-stand clearing disturbances in current LTSS-VCT products and difficulty in deriving reliable forest height measurements using GLAS samples when terrain relief was present within their footprints. In addition, a systematic underestimation of about 5 m by the developed model was also observed, half of which could be explained by forest growth that occurred between field measurement year and model target year. The remaining difference suggests that tree height measurements derived using waveform lidar data could be significantly underestimated, especially for young pine forests. Options for improving the height modeling approach developed in this study were discussed.

Li, Ainong↗

DOE OSTI2026

Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning

Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.

Accumulated Local Effects↗

DOE OSTI2025

Code Generators for Floating-Point Unit Design in Integrated Circuits (OpenFloat) v1.0

This IP provides a comprehensive set of code generators for various floating-point units (FPUs) essential for integrated circuit design and integration, targeting a broad spectrum of applications, including machine learning and scientific computing. The suite includes FP adders, multipliers, subtractors, dividers, reciprocals, exponentials, square roots, trigonometric functions (sine, cosine, arctangent), and more. It supports customizable hardware design parameters, such as precision (16, 32, 64, and 128 bits) and pipeline depths, offering users enhanced flexibility and productivity. The generated code is in an industry-standard hardware description language, ensuring compatibility with standard design flows, including simulation, verification, synthesis, and implementation on both field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs).

Shalf, JohnM. [Lawrence Berkeley National Laborato↗

NASA NTRS1992

A model of the CO2 exchanges between biosphere and atmosphere in the tundra

A physical model of the soil thermal regime in a permafrost terrain has been developed and validated with soil temperature measurements at Barrow, Alaska. The model calculates daily soil temperatures as a function of depth and average moisture contents of the organic and mineral layers using a set of five climatic variables, i.e., air temperature, precipitation, cloudiness, wind speed, and relative humidity. The model is not only designed to study the impact of climate change on the soil temperature and moisture regime, but also to provide the input to a decomposition and net primary production model. In this context, it is well known that CO2 exchanges between the terrestrial biosphere and the atmosphere are driven by soil temperature through decomposition of soil organic matter and root respiration. However, in tundra ecosystems, net CO2 exchange is extremely sensitive to soil moisture content; therefore it is necessary to predict variations in soil moisture in order to assess the impact of climate change on carbon fluxes. To this end, the present model includes the representation of the soil moisture response to changes in climatic conditions. The results presented in the foregoing demonstrate that large errors in soil temperature and permafrost depth estimates arise from neglecting the dependence of the soil thermal regime on soil moisture contents. Permafrost terrain is an example of a situation where soil moisture and temperature are particularly interrelated: drainage conditions improve when the depth of the permafrost increases; a decrease in soil moisture content leads to a decrease in the latent heat required for the phase transition so that the heat penetrates faster and deeper, and the maximum depth of thaw increases; and as excepted, soil thermal coefficients increase with moisture.

Labgaa, Rachid R.↗