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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 1,657 records · Page 92

Complementary effects of supplemental feeding and straw retention on winter biodiversity in rice agroecosystems

Rice paddies are both major food-production systems and critical winter habitats for wildlife. In the Civilian Control Zone (CCZ) adjoining the Korean Demilitarized Zone (DMZ), post-harvest interventions such as supplementary grain feeding and straw retention are promoted through agronomic and conservation incentives. These measures differ in ecological scope: feeding provides direct, concentrated energetic subsidies, whereas straw management alters habitat structure and resource bases. We clarified whether these pathways function in complementary or substitutive ways to support resilient, long-term conservation strategies in rice agroecosystems. Using camera traps, we evaluated the effects of three straw treatments (chopped-straw, whole-straw, straw-removed) and supplemental feeding on winter bird and mammal communities across 48 rice fields in the CCZ. Our results demonstrate that feeding produced strong, localized increases in bird abundance and richness, driven mainly by cranes (Grus japonensis and Antigone vipio) and geese (Anser spp.), with limited effects on Shannon diversity or functional structure. Among non-feeding fields, chopped-straw paddies consistently supported higher richness and Shannon diversity than whole-straw or straw-removed fields, while centroid shifts in taxonomic and functional space were modest. Mammal abundance and diversity were largely insensitive to feeding or straw regimes, varying instead with road and forest distance and regional context. Supplemental feeding and straw retention are therefore not interchangeable tools: feeding concentrates a few avian guilds, whereas chopped-straw retention enhances baseline diversity across farmland. Collectively, our findings suggest integrating low-input straw retention with targeted feeding offers a more robust pathway for sustaining winter biodiversity in rice agroecosystems.

60 APPLIED LIFE SCIENCES↗

Current and Projected Future Distribution of Plant Community Types for the Southern Seward Peninsula, Alaska

Landscape scale maps of plant community distribution at 5 m resolution were developed for southern Seward Peninsula. A Random Forest based environmental niche model was developed using topographic and climate data sets. Models were trained for the 2010-2019 period and applied to develop plant community distributions for contemporary (2010-2019) period. Trained model was applied to project the plant community distributions under future climate. Using downscaled projections for RCP8.5 scenario from five climate models (CCSM4, GFDL-CM3, GISS-E2-R, IPSL-CM5A-LR, MRI-CGCM3) and multi-model mean, a six member ensemble of plant community distribution were developed for current decade (2010-2019) and for future decades (2020-2029, 2030-2039, 2040-2049, 2050-2059). Contains *.tif and *.sh files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Embracing Open Source for NASA's Earth Science Data Systems

The overarching purpose of NASAs Earth Science program is to develop a scientific understanding of Earth as a system. Scientific knowledge is most robust and actionable when resulting from transparent, traceable, and reproducible methods. Reproducibility includes open access to the data as well as the software used to arrive at results. Additionally, software that is custom-developed for NASA should be open to the greatest degree possible, to enable re-use across Federal agencies, reduce overall costs to the government, remove barriers to innovation, and promote consistency through the use of uniform standards. Finally, Open Source Software (OSS) practices facilitate collaboration between agencies and the private sector. To best meet these ends, NASAs Earth Science Division promotes the full and open sharing of not only all data, metadata, products, information, documentation, models, images, and research results but also the source code used to generate, manipulate and analyze them. This talk focuses on the challenges to open sourcing NASA developed software within ESD and the growing pains associated with establishing policies running the gamut of tracking issues, properly documenting build processes, engaging the open source community, maintaining internal compliance, and accepting contributions from external sources. This talk also covers the adoption of existing open source technologies and standards to enhance our custom solutions and our contributions back to the community. Finally, we will be introducing the most recent OSS contributions from NASA Earth Science program and promoting these projects for wider community review and adoption.

Earth Science↗

Using Methyl Bromide for Interspecies Cell–Cell Signaling and As a Reporter in a Model Soil Consortium

Synthetic microbial communities are emerging as model systems for studying consortia-scale phenotypes. To establish synthetic biology tools for studying these communities in hard-to-image environmental materials, we evaluated whether a single member of a model soil consortium (MSC) can be programmed to report on gene expression without requiring matrix disruption. For these studies, we targeted a five member MSC that includes Dyadobacter fermentans, Ensifer adhaerens, Rhodococcus sp003130705, Streptomyces sp001905665, and Variovorax beijingensis. By coupling the expression of a methyl halide transferase to a constitutive promoter, we show that Variovorax beijingensis can be programmed to synthesize methyl halides that accumulate in the soil headspace at levels that are ≥24-fold higher than all other MSC members across a range of environmentally-relevant hydration conditions. We find that methyl halide production can report on a MSC promoter that is activated by changes in water potential, and we demonstrate that a synthetic gas signal can be read out directly using gas chromatography and indirectly using a soil-derived Methylorubrum that is programmed to produce a visual output in response to methyl halides. Finally, these tools will be useful for future studies that investigate how MSC respond to dynamic hydration conditions, such as drought and flood events induced by climate change, which can alter soil water potential and induce the release of stored carbon.

59 BASIC BIOLOGICAL SCIENCES↗

Resilience in soil bacterial communities of the boreal forest from one to five years after wildfire across a severity gradient

Wildfires can represent a major disturbance to ecosystems, including soil microbial communities belowground. Furthermore, fire regimes are changing in many parts of the world, altering and often increasing fire severity, frequency, and size. The boreal forest and taiga plains ecoregions of northern Canada are characterized by naturally-occurring stand-replacing wildfires on a 40–350 year basis. We previously studied the effects of wildfire on soil microbial communities one year post-fire across 40 sites, spanning a range of burn severity. Here, we return to the same sites five years post-fire to test a series of hypotheses about the effects of fire on bacterial community composition. We ask questions on two themes: which factors control bacterial community composition during post-fire recovery, and how does the importance of different fire-responsive traits change during post-fire recovery? We find the following: Five years post-fire, vegetation community, moisture regime, pH, total carbon, texture, and burned/unburned all remained significant predictors of bacterial community composition with similar predictive value (R 2 ). Bacterial communities became more similar to unburned sites five years post-fire, across the range of severity, suggesting resilience, while general structure of co-occurrence networks remained similar one and five years post-fire. Fast growth potential, as estimated using predicted 16S rRNA copy numbers, was no longer significantly correlated with burn severity five years post-fire, indicating the importance of this trait for structuring bacterial community composition may be limited to relatively short timescales. Many taxa that were enriched in burned sites one year post-fire remained enriched five years post-fire, although the degree to which they were enriched generally decreased. Specific taxa of interest from the genera Massilia, Blastococcus, and Arthrobacter all remained significantly enriched, suggesting that they may have traits that allow them to continue to flourish in the post-fire environment, such as tolerance to increased pH or ability to degrade pyrogenic organic matter. This hypothesis-based work expands our understanding of the post-fire recovery of soil bacterial communities and raises new hypotheses to test in future studies.

59 BASIC BIOLOGICAL SCIENCES↗

NASA EOSDIS: Enabling Science by Improving User Knowledge

Lessons learned and impacts of applying these newer methods are explained and include several examples from our current efforts such as the interactive, on-line webinars focusing on data discovery and access including tool usage, informal and informative data chats with data experts across our EOSDIS community, data user profile interviews with scientists actively using EOSDIS data in their research, and improved conference and meeting interactions via EOSDIS data interactively used during hyper-wall talks and Worldview application. The suite of internet-based, interactive capabilities and technologies has allowed our project to expand our user community by making the data and applications from numerous Earth science missions more engaging, approachable and meaningful.

EOSDIS↗

Carbon cycling across ecosystem succession in a north temperate forest: Controls and management implications

Despite decades of progress, much remains unknown about successional trajectories of carbon (C) cycling in north temperate forests. Drivers and mechanisms of these changes, including the role of different types of disturbances, are particularly elusive. To address this gap, we synthesized decades of data from experimental chronosequences and long-term monitoring at a well-studied, regionally representative field site in northern Michigan, USA. Our study provides a comprehensive assessment of changes in above- and belowground ecosystem components over two centuries of succession, links temporal dynamics in C pools and fluxes with underlying drivers, and offers several conceptual insights to the field of forest ecology. Our first advance shows how temporal dynamics in some ecosystem components are consistent across severe disturbances that reset succession and partial disturbances that slightly modify it: both of these disturbance types increase soil N availability, alter fungal community composition, and alter growth and competitive interactions between short-lived pioneer and longer-lived tree taxa. Further, these changes in turn affect soil C stocks, respiratory emissions, and other belowground processes. Second, we show that some other ecosystem components have effects on C cycling that are not consistent over the course of succession. For example, canopy structure does not influence C uptake early in succession but becomes important as stands develop, and the importance of individual structural properties changes over the course of two centuries of stand development. Third, we show that in recent decades, climate change is masking or overriding the influence of community composition on C uptake, while respiratory emissions are sensitive to both climatic and compositional change. In synthesis, we emphasize that time is not a driver of C cycling; it is a dimension within which ecosystem drivers such as canopy structure, tree and microbial community composition change. Changes in those drivers, not in forest age, are what control forest C trajectories, and those changes can happen quickly or slowly, through natural processes or deliberate intervention. Stemming from this view and a whole-ecosystem perspective on forest succession, we offer management applications from this work and assess its broader relevance to understanding long-term change in other north temperate forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Science, Engineering, Mathematics and Aerospace Academy

The Science, Engineering, Mathematics and Aerospace Academy (SEMAA) was established in September, 1993, by Cuyahoga Community College and the NASA Lewis Research Center. Funding for SEMAA was provided by NASA Headquarters' Office of Equal Employment Opportunities. SEMAA brought together five preexisting youth programs at Cuyahoga Community College. All the programs shared the common goals of 1) Increasing the participation of underrepresented/underserved groups in science, mathematics and engineering and technology careers. 2) Increasing "success" rates of all students interested in science and mathematics. 3) Developing partnerships to recognize and support students interested in these fields. 4) Supporting continued success of highly successful students. The framework for each preexisting program allowed SEMAA to have a student population ranging from kindergarten through the twelfth-grade. This connectivness was the foundation for the many decisions which would make SEMAA a truly innovative program.

Source record↗

Rapid Turn Around BRIC-PDFU Payload: A New Paradigm for Spaceflight Experiments

In 2009, NASA's Fundamental Space Biology program provided an opportunity for investigators to propose for a quick-turn-around multi-user spaceflight experiment that focused on the model plant species Arabidopsis thaliana. This was a passive payload with no on-orbit power or communications available. An NRA was rapidly written (8/09), released (NNH09ZTT004N; 9/09), proposals were received (11/09) and peer reviewed with 3 PI groups selected for flight (1/10): (1) A-L Paul, University of Florida, (2) E. Blancaflor, Noble Foundation, (3) J. Kiss, Miami University. The investigators flew Arabidopsis seeds or callus cultures of their choosing (plated onto 60 mm diameter Petri dishes containing agarsolidified media) on the STS-131 Space Shuttle mission (launched 4/5/10) and the resulting plant tissues returned to earth on 4/20/10. Each petri dish was placed inside its own Petri Dish Fixation Unit (PDFU), which was assembled and loaded with either formaldehyde, glutaraldehyde or RNAlater for crew-facilitated on-orbit fixation. Five PDFUs plus a temperature data logger were loaded into each of 8 BRIC-PDFUs (Biological Research In Canisters PDFU). All eight BRIC-PDFUs were loaded into a half tray along with actuator equipment that the crew used for the fixations. Pre-flight turn-over was 28 hours prior to launch. The BRIC-PDFU assemblies were removed from the orbiter and handed over to the investigator teams for processing 5-6 hours after landing. This payload demonstrated a rapid response turnaround for flying multiple peer-reviewed science investigations using previously flown hardware and minimal ISS-resources. The approach used reduced both hardware/certification and PI costs. The time waiting for a flight opportunity for the selected Pls was minimal. This new paradigm for spaceflight experiments may provide a model for future flight research opportunities. The ultimate goal is to fly as many investigators as rapidly as possible and reinvigorate the space biology community while obtaining high-quality, peer-reviewed science.

Levine, Howard G.↗

Defining weather scenarios for simulation-based assessment of thermal resilience of buildings under current and future climates: A case study in Brazil

In response to increasingly severe weather conditions, optimization of building performance and investment provides an opportunity to consider co-benefits of thermal resilience during energy efficiency retrofits. This work aims to assess thermal resilience of buildings using building performance simulation to evaluate the indoor overheating risk under nine weather scenarios, considering historical (2010s), mid-term future (2050s), and long-term future (2090s) typical meteorological years, and heat wave years. Such an analysis is based on resilience profiles that combine six integrated indicators. A case study with a district of 92 buildings in Brazil was conducted, and a combination of strategies to improve thermal resilience was identified. Results reflect the necessity of planning for resilience in the context of climate change. This is because strategies recommended under current conditions might not be ideal in the future. Therefore, an adaptable design should be prioritized. Cooling energy consumption could increase by 48 % by the 2050s, while excessive overheating issues could reach 37 % of the buildings. Simple passive strategies can significantly reduce the heat stress. A comprehensive thermal resilience analysis should ultimately be accompanied by a thorough reflection on the stakeholders’ objectives, available resources, and planning horizon, as well as the risks assumed for not being resilient.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Predictive Proxies of Present and Future Lightning in a Superparameterized Model

Abstract A superparameterized climate model is used to assess the global performance of several previously proposed proxies for lightning. In particular, predictors incorporating hydrometeor (ice, graupel) profiles and convective vertical velocities are compared to observations, then used to estimate changes in flash rates with global warming. The choice of microphysics parameterization is also investigated, with all predictors showing higher correlations with Lightning Imaging Sensor/Optical Transient Detector observations when using a 2‐moment scheme compared to a 1‐moment representation. All proxies generally agree in their response to warming over tropical land, with notable decreases in Africa, the Middle East, and northern South America, but disagree over oceans and the midlatitudes. The product of convective available potential energy and precipitation predicts increases over these latter areas, as do the 2‐moment ice‐based proxies, while those of the 1‐moment model tend to show decreases, highlighting the importance of cloud microphysics when using climate models to simulate lightning.

54 ENVIRONMENTAL SCIENCES↗

Prospects of federated machine learning in fluid dynamics

Physics-based models have been mainstream in fluid dynamics for developing predictive models. In recent years, machine learning has offered a renaissance to the fluid community due to the rapid developments in data science, processing units, neural network based technologies, and sensor adaptations. So far in many applications in fluid dynamics, machine learning approaches have been mostly focused on a standard process that requires centralizing the training data on a designated machine or in a data center. In this article, we present a federated machine learning approach that enables localized clients to collaboratively learn an aggregated and shared predictive model while keeping all the training data on each edge device. We demonstrate the feasibility and prospects of such a decentralized learning approach with an effort to forge a deep learning surrogate model for reconstructing spatiotemporal fields. Our results indicate that federated machine learning might be a viable tool for designing highly accurate predictive decentralized digital twins relevant to fluid dynamics.

36 MATERIALS SCIENCE↗

Comparing western (Megascops kennicottii) and whiskered (M. trichopsis) screech-owl microbiomes in southern Arizona using a novel 16S rRNA sequencing method

Microbiomes are essential to a host’s physiology and health. Despite the overall importance of microbiomes to animal health, they remain understudied in wildlife. Microbiomes function as physical barriers to invading pathogens, and changes in the diversity or composition of microbes within a host may disrupt this barrier. In order to use microbiomes in wildlife ecology, knowledge of the natural variation within and among species is essential. We compare the diversity and composition of two avian species that share the same habitat and niche in our study area, the western screech-owl (Megascops kennicottii) and the whiskered screech-owl (M. trichopsis). We used a targeted 16S sequencing method to improve the taxonomic resolution of microbiomes. We found similar measures of alpha diversity between species and sample types (cloacal samples vs. fecal samples). However, there were significant differences in bacterial species richness among nestlings from different nest boxes, and the composition differed between the two bird species and among nestlings from different nest boxes. Western screech-owls had more variation in alpha diversity and composition and had fewer bacterial species in their core microbiome than whiskered screech-owls. Siblings are likely to yield similar findings for microbiomes; thus, sampling nestlings from different nests may be most informative for monitoring population-level changes.

59 BASIC BIOLOGICAL SCIENCES↗

Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database

The Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database v1.0 is the output of a data availability assessment workflow that was developed by NETL to create a tool for spatial data availability assessment. This results database is the output of the first version of the workflow performed on the data with the CS TVA Database v2.0.

carbon storage↗

Comprehensive Chemical Fingerprinting by Multidimensional GC and Supervised Machine Learning

This project leverages advances in machine learning based data analysis techniques and untargeted omic analytical methods to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to identify and detect complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.

97 MATHEMATICS AND COMPUTING↗

Comprehensive Chemical Fingerprinting by Multidimensional GC and Supervised Machine Learning

This project leveraged advances in machine learning based data analysis techniques and untargeted analytical methods for organic analysis to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to detect and identify complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Position Papers for the ASCR Workshop on the Science of Scientific-Software Development and Use

Software is an increasingly important component in the pursuit of scientific discovery. Both its development and use are essential activities for many scientific teams. At the same time, very little scientific study has been conducted to understand, characterize, and improve the development and use of software for science. Computational science teams have diversified over time to include contributions from domain scientists who provide expertise in scientific and engineering disciplines, applied mathematicians and computer scientists who provide optimal algorithms and data structures, and software and data engineers who provide methodologies and tools adapted and adopted from other software domains. These diverse contributions have enabled tremendous advances in the pursuit of scientific discovery, even as models, computer architectures, and software environments have become more complicated. With this increasing diversity, we believe the next opportunity for qualitative improvement comes from applying the scientific method to understanding, characterizing, and improving how scientific software is developed and used. We believe that this pursuit requires expertise from computational scientists themselves, and from the cognitive and social sciences as well as the software engineering research community. As we look to increase the productivity and sustainability of the scientific-software-development-and-use cycle, a more systematic application of the scientific method to understand processes for software development and use will be a valuable tool to guide future work and result in more usable and sustainable software. This workshop will bring together computer scientists, software engineering researchers, computational scientists, applied mathematicians, social scientists, cognitive scientists, and others, to explore how we can conduct such systematic investigations, what can be learned, and how doing so will benefit the scientific enterprise. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees — from DOE, industry, and academia — will produce a report for ASCR that summarizes the findings of the workshop.

42 ENGINEERING↗

U.S. Department of Energy: National Virtual Biotechnology Laboratory (Technical Report)

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. The NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply shortages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. As part of the NVBL framework, DOE rapidly assembled five project teams to (1) identify new targets for medical therapeutics; (2) develop innovations in testing capabilities; (3) provide epidemiological and logistical support; (4) understand viral fate and transport in the environment; and (5) address supply chain bottlenecks by harnessing extensive additive manufacturing capabilities. Each research team was charged with defining high-impact projects that could be completed in a 6-month sprint while coordinating their developments with academia, other government agencies, and the private sector. Within months, NVBL teams used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported efforts by the U.S. Food and Drug Administration, Centers for Disease Control and Prevention, and U.S. Department of Defense to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. To minimize virus uptake and protect human health, NVBL teams studied how to control indoor virus movement. Researchers also produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment, creating nearly 1,000 new jobs. Through its NVBL framework, DOE has contributed significantly to the nation’s COVID response, demonstrating in only a few months the critical impact of its national laboratories. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development solutions. Going forward, the NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, DOE will continue to be an integral component of agency-wide efforts to prepare for and respond to biorisks and other crises. This technical report describes the goals, progress, and results of NVBL’s five project teams—Molecular Design for COVID-19 Therapeutics, COVID-19 Testing, Epidemiological Modeling, Viral Fate and Transport, and Materials and Manufacturing of Critical Supplies—and lists each team’s publications and research output.

42 ENGINEERING↗