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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

AmeriFlux FLUXNET-1F US-xSP NEON Soaproot Saddle (SOAP)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xSP NEON Soaproot Saddle (SOAP). This is the FLUXNET version of the carbon flux data for the site US-xSP NEON Soaproot Saddle (SOAP) produced by applying the standard ONEFlux (1F) software. Site Description - The Soaproot Saddle is a complex terrain of coarse hills, steep slopes and narrow drainages. With an elevation of 3274 - 4537’ this site encompasses 1438 acres of mixed conifer forests that are experiencing high levels of mortality due to native Pine beetles. At the core of this site stands a 171’ tall flux tower that collects physical and chemical properties of atmosphere and related process. Soaproot Saddle also hosts an array of sensor measurements along with field observations collected by highly trained NEON staff. The automated instrument measurements and some of the terrestrial observational safor this field site are colocted with NEON's aquatic site, Upper Big Creek, which is located just north of Soaproot Saddle's site boundaries.

Network), NEON (National Ecological Observatory [N↗
DOE OSTI2026

AmeriFlux FLUXNET-1F PR-xGU NEON Guanica Forest (GUAN)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site PR-xGU NEON Guanica Forest (GUAN). This is the FLUXNET version of the carbon flux data for the site PR-xGU NEON Guanica Forest (GUAN) produced by applying the standard ONEFlux (1F) software. Site Description - The Guanica Forest (GUAN) site is located on the southwest corner of the main island of Puerto Rico in a protected forest with primary phenological species of Gymnanthes lucida, Pisonia albida, and Bursera simaruba. The mean canopy height is approximately 10 m.

Network), NEON (National Ecological Observatory [N↗
DOE OSTI2025

Competition and cooperation: The plasticity of bacterial interactions across environments

Bacteria live in diverse communities, forming complex networks of interacting species. A central question in bacterial ecology is whether species engage in cooperative or competitive interactions. But this question often neglects the role of the environment. Here, we use genome-scale metabolic networks from two different open-access collections (AGORA and CarveMe) to assess pairwise interactions of different microbes in varying environmental conditions (provision of different environmental compounds). By computationally simulating thousands of environments for 10,000 pairs of bacteria from each collection, we found that most pairs were able to both compete and cooperate depending on the availability of environmental resources. This modeling approach allowed us to determine commonalities between environments that could facilitate the potential for cooperation or competition between a pair of species. Namely, cooperative interactions, especially obligate, were most common in less diverse environments. Further, as compounds were removed from the environment, we found interactions tended to degrade towards obligacy. However, we also found that on average at least one compound could be removed from an environment to switch the interaction from competition to facultative cooperation or vice versa. Together our approach indicates a high degree of plasticity in microbial interactions in response to the availability of environmental resources.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Tracking animal movements via collaborative acoustic telemetry networks: Multiscale habitat use, phenology, and management insights

Abstract Estuaries support diverse fish and invertebrate communities, including resident species that rely on estuarine habitats year‐round and transient migratory species. The unique movement patterns of these animals connect habitats within and far beyond the estuary and are integrally linked to fisheries management objectives. With a focus on Chesapeake Bay, this study leveraged data from collaborative acoustic telemetry networks in the northwest Atlantic to assess habitat use and phenology of movements for seven species of fish (cownose rays, dusky sharks, smooth dogfish, alewife, striped bass, common carp, and blue catfish) and one invertebrate (horseshoe crabs). A total of 288 acoustically tagged individuals were detected >3.2 million times (6,743 to 2,095,717 detections per species) on receivers across ~20.5 degrees of latitude spanning the North American Atlantic seaboard from Florida, USA, to New Brunswick, Canada. Common metrics of movement and phenology grouped these species as resident (common carp, blue catfish, horseshoe crabs), primarily resident in estuaries (juvenile striped bass), and coastal migrant (cownose rays, dusky sharks, smooth dogfish, alewife); maximum distance traveled varied by three orders of magnitude among these species. Further analysis of phenology for coastal migrants elucidated the timing and duration of these species' use of Chesapeake Bay. Collectively, movements linked habitats within Chesapeake Bay and connected the estuary to coastal ecosystems both to the north (e.g., alewife) and south (e.g., cownose rays), creating networks of fisheries management jurisdictions that varied in complexity and identified opportunities for enhancement to current management or co‐management of some species. Our results elucidate the importance of estuaries to species with diverse movement behaviors, identify scales and pathways of habitat connectivity via animal movements, and highlight the utility of collaborative acoustic telemetry networks for quantifying movements relevant to both ecological research and fisheries management.

Livernois, Mariah C.↗
NASA NTRS2007

Solutions Network Formulation Report. Visible/Infrared Imager/Radiometer Suite and Landsat Data Continuity Mission Simulated Data Products for the Great Lakes Basin Ecological Team

The proposed solution would simulate VIIRS and LDCM sensor data for use in the USGS/USFWS GLBET DST. The VIIRS sensor possesses a spectral range that provides water-penetrating bands that could be used to assess water clarity on a regional spatial scale. The LDCM sensor possesses suitable spectral bands in a range of wavelengths that could be used to map water quality at finer spatial scales relative to VIIRS. Water quality, alongshore sediment transport and pollutant discharge tracking into the Great Lakes system are targeted as the primary products to be developed. A principal benefit of water quality monitoring via satellite imagery is its economy compared to field-data collection methods. Additionally, higher resolution satellite imagery provides a baseline dataset(s) against which later imagery can be overlaid in GIS-based DST programs. Further, information derived from higher resolution satellite imagery can be used to address public concerns and to confirm environmental compliance. The candidate solution supports the Public Health, Coastal Management, and Water Management National Applications.

Estep, Leland↗
NASA NTRS1998

Predicting lettuce canopy photosynthesis with statistical and neural network models

An artificial neural network (NN) and a statistical regression model were developed to predict canopy photosynthetic rates (Pn) for 'Waldman's Green' leaf lettuce (Latuca sativa L.). All data used to develop and test the models were collected for crop stands grown hydroponically and under controlled-environment conditions. In the NN and regression models, canopy Pn was predicted as a function of three independent variables: shootzone CO2 concentration (600 to 1500 micromoles mol-1), photosynthetic photon flux (PPF) (600 to 1100 micromoles m-2 s-1), and canopy age (10 to 20 days after planting). The models were used to determine the combinations of CO2 and PPF setpoints required each day to maintain maximum canopy Pn. The statistical model (a third-order polynomial) predicted Pn more accurately than the simple NN (a three-layer, fully connected net). Over an 11-day validation period, average percent difference between predicted and actual Pn was 12.3% and 24.6% for the statistical and NN models, respectively. Both models lost considerable accuracy when used to determine relatively long-range Pn predictions (> or = 6 days into the future).

Non-NASA Center↗
NASA NTRS2002

The Use of Remote Sensing for Monitoring, Prediction, and Management of Hydrologic, Agricultural, and Ecological Processes in the Northern Great Plains

The NASA-EPSCoR program in South Dakota is focused on the enhancement of NASA-related research in earth system science and corresponding infrastructure development to support this theme. Hence, the program has adopted a strategy that keys on research projects that: a) establish quantitative links between geospatial information technologies and fundamental climatic and ecosystem processes in the Northern Great Plains (NGP) and b) develop and use coupled modeling tools, which can be initialized by data from combined satellite and surface measurements, to provide reliable predictions and management guidance for hydrologic, agricultural, and ecological systems of the NGP. Building a partnership network that includes both internal and external team members is recognized as an essential element of the SD NASA-EPSCoR program. Hence, promoting and tracking such linkages along with their relevant programmatic consequences are used as one metric to assess the program's progress and success. This annual report first summarizes general activities and accomplishments, and then provides progress narratives for the two separate, yet related research projects that are essential components of the SD NASA-EPSCoR program.

Farwell, Sherry O.↗
NASA NTRS2007

Unofficial Road Building in the Brazilian Amazon: Dilemmas and Models for Road Governance

Unofficial roads form dense networks in landscapes, generating a litany of negative ecological outcomes, but unofficial roads in frontier areas are also instrumental in local livelihoods and community development. This trade-off poses dilemmas for the governance of unofficial roads. Unofficial road building in frontier areas of the Brazilian Amazon illustrates the challenges of 'road governance.' Both state-based and community based governance models exhibit important liabilities for governing unofficial roads. Whereas state-based governance has experienced difficulties in adapting to specific local contexts and interacting effectively with local interest groups, community-based governance has a mixed record owing to social inequalities and conflicts among local interest groups. A state-community hybrid model may offer more effective governance of unofficial road building by combining the oversight capacity of the state with locally grounded community management via participatory decision-making.

Perz, Stephen G.↗
NASA NTRS2005

Online fault adaptive control for efficient resource management in Advanced Life Support Systems

This article presents the design and implementation of a controller scheme for efficient resource management in Advanced Life Support Systems. In the proposed approach, a switching hybrid system model is used to represent the dynamics of the system components and their interactions. The operational specifications for the controller are represented by utility functions, and the corresponding resource management problem is formulated as a safety control problem. The controller is designed as a limited-horizon online supervisory controller that performs a limited forward search on the state-space of the system at each time step, and uses the utility functions to decide on the best action. The feasibility and accuracy of the online algorithm can be assessed at design time. We demonstrate the effectiveness of the scheme by running a set of experiments on the Reverse Osmosis (RO) subsystem of the Water Recovery System (WRS).

NASA Discipline Life Support Systems↗
DOE OSTI2024

Biogeochemical and community ecology responses to the wetting of non-perennial streams

Transitions between dry and wet hydrologic states are the defining characteristic of non-perennial rivers and streams, which constitute the majority of the global river network. Although past work has focused on stream drying characteristics, there has been less focus on how hydrology, ecology and biogeochemistry respond and interact during stream wetting. Wetting mechanisms are highly variable and can range from dramatic floods and debris flows to gradual saturation by upwelling groundwater. This variation in wetting affects ecological and biogeochemical functions, including nutrient processing, sediment transport and the assembly of biotic communities. Here, in this work, we synthesize evidence describing the hydrological mechanisms underpinning different types of wetting regimes, the associated biogeochemical and organismal responses, and the potential scientific and management implications for downstream ecosystems. This combined multidisciplinary understanding of wetting dynamics in non-perennial streams will be key to predicting and managing for the effects of climate change on non-perennial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Changes in microbial community and network structure precede shrub degradation in a desert ecosystem

Large-scale restoration is intended to promote ecological recovery. Improvements in plant and microbial conditions, however, may slow or even reverse in late succession. To better understand long-term restoration outcomes and underlying drivers of successional pathways, we tracked plant, bacterial and fungal, and soil conditions across a 40-year shrub plantation that was intended to stabilize desertified land in northern China. Here, we found that planted Haloxylon ammodendron shrubs developed and then subsequently became degraded after 30–40 years. Bacterial abundance and α-diversity were much higher than those of fungi, but no significant differences in composition and structure were found in different plantation ages. In contrast, the dominant taxa of fungal communities shifted from symbiotroph and saprotroph species towards pathotroph species with increased soil nutrients in the plantation chronosequence after two decades. The changes in fungal dominant species led to a transition in microbial network structure and function, with an increase in negative linkages among taxa that began in the middle stages of succession. Changes in fungal community structure had direct and indirect negative effects on shrub leaf physiology, root activity, and biomass. Our results highlight the preceding role of a breakdown in soil microbial community composition and network structure on the degradation of shrub performance in long-term desert succession. Our study emphasizes the importance of understanding soil-microbial-plant linkages on restoration outcomes, and mechanisms that can slow or reverse the recovery of ecosystems.

Bacterial and fungal community composition↗
NASA NTRS1991

Communications infrastructure requirements for telemedicine/telehealth in the context of planning for and responding to natural disasters: Considering the need for shared regional networks

During the course of recent years the frequency and magnitude of major disasters - of natural, technological, or ecological origin - have made the world community dramatically aware of the immense losses of human life and economic resources that are caused regularly by such calamities. Particularly hard hit are developing countries, for whom the magnitude of disasters frequently outstrips the ability of the society to cope with them. In many cases this situation can be prevented, and the recent trend in disaster management has been to emphasize the importance of preparedness and mitigation as a means of prevention. In cases of disaster, a system is needed to respond to relief requirements, particularly the delivery of medical care. There is no generic telecommunications infrastructure appropriate for the variety of applications in medical care and disaster management. The need to integrate telemedicine/telehealth into shared regional disaster management telecommunications networks is discussed. Focus is on the development of infrastructure designed to serve the needs of disaster prone regions of the developing world.

Scott, John Carver↗
NASA NTRS1991

Multispectral Image Processing for Plants

The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

Miles, Gaines E.↗
DOE OSTI2025

Breeding of microbiomes conferring salt tolerance to plants

Microbiome breeding through host-mediated selection is a technique to artificially select for microbiomes conferring beneficial properties to plants. Using a systematic selection protocol that maximises the heritability of microbiome effects, transmission fidelity, and microbiome stability through multiple selection cycles, we previously developed root-associated microbial communities conferring sodium and aluminium tolerance to Brachypodium distachyon, a model for cereal crops. Here, we explore the physiological mechanisms underlying our selected microbiomes’ effect on plant fitness and analyse how our selection protocol shaped the composition and structure of these microbiomes. We analysed the effects of our selected microbiomes on plant fitness and tissue-nutrient concentration, then used 16S rRNA amplicon sequencing to examine microbial community composition and co-occurrence network patterns. Our sodium-selected microbiomes reduced leaf sodium concentration by ~ 50%, whereas the aluminium-selected microbiomes had no effect on leaf-tissue nutrient concentration, suggesting different mechanisms underlying the microbiome-mediated stress tolerance. By testing the selected microbiomes in a cross-fostering experiment, we show that our artificially selected microbiomes attained (a) ecological robustness contributing to transplantability (i.e. inheritance) of microbiome-encoded effects between plants; and (b) network features identifying key bacteria promoting salt-stress tolerance. Combined, these findings elucidate critical mechanisms underlying host-mediated artificial selection as a framework to breed microbiomes with targeted benefits for plants under salt stresses, with significant implications for sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The role of emerging scientists in restoration ecology: insights from a SER2023 conference workshop

Emerging professionals are crucial in advancing ecological restoration by connecting newcomers with established leaders and blending new ideas with traditional practices. This paper highlights the vital role emerging scientists play in restoration ecology and the Society for Ecological Restoration (SER). A survey conducted during the SER2023 conference workshop, organized by the Students and Emerging Professionals committee, showed that emerging professionals contribute significantly to every stage of scientific work, from planning to publication. However, participants emphasized the scarcity of funding opportunities for non‐senior scientists, which limits academic growth. The workshop underscored the importance of nurturing emerging professionals to develop future leaders for SER and ensure continuity. Fostering non‐hierarchical and inclusive networking is key to engaging and empowering these professionals, ultimately contributing to the long‐term success of ecological restoration efforts.

Weidlich, Emanuela W. A.↗
DOE OSTI2025

A multifunctional sesquiterpene synthase integrates with cytochrome P450s to reinforce the terpenoid defense network in maize

Terpenoids, the largest and most structurally diverse class of plant natural products, play essential roles in maize defense and ecological interactions. In this study, we identified and functionally characterized a sesquiterpenoid-based defense pathway in maize centered on α-santalenoic acid, a pathogen-inducible sesquiterpenoid antibiotic. Using a combination of metabolite-based genome-wide association studies (mGWAS), linkage mapping, and heterologous expression assays, we identified ZmTPS9 as a multiproduct terpene synthase that primarily produces α-santalene and β-bisabolene. Sequence analysis and site-directed mutagenesis revealed that threonine at position 413 is critical for enzyme activity, with its deletion resulting in a complete loss of enzyme activity. The sesquiterpene hydrocarbons produced by ZmTPS9 are further oxidized by three cytochrome P450 monooxygenases, ZmCYP71Z16, ZmCYP71Z18, and ZmCYP71Z19, to yield antimicrobial metabolites including α-santalenoic acid, zealexin D1 (ZD1), and zealexin D2 (ZD2). Together, these findings demonstrate a convergent biosynthetic strategy in maize, where multiproduct terpene synthases and promiscuous P450s collaboratively generate a flexible and robust terpenoid defense network.

a-santalenoic acid↗
NASA NTRS2020

Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

radiative transfer↗
NASA NTRS2021

Coastal California Water Resources: Assessing Estuarine Ecosystems in California for Improved Wetland Monitoring and Management

Estuaries are vital ecosystems that serve important ecological functions. The Marine Life Protection Act aims to protect these ecosystems by establishing a network of marine protected areas (MPAs), in part by requiring regulatory agencies to monitor estuary extent and health. However, California has 23 estuarine MPAs (EMPAs) and approximately 440,000 total acres of estuarine habitat and, therefore, ground-based data collection can be time and resource intensive. This project used remotely sensed data to examine the health of California EMPAs in an effort to supplement ground-based field measurements. Specifically using Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), this project assessed mouth state, inundation extent, turbidity, Chlorophyll-a, and colored dissolved organic matter (CDOM) for estuaries observable with these sensors. The Normalized Water Difference Index (NDWI) from Sentinel-2 MSI was capable of capturing estuary mouth state and inundation extent. Meanwhile, Landsat 8 OLI and Sentinel-2 MSI indicated a capacity to capture differences in water quality metrics coinciding with changes to estuary mouth state using algorithms applied in Google Earth Engine (GEE). The GEE California Estuary Assessment (CEA) tools will allow project partners to better monitor and understand estuarine dynamics and health.

Karina Alvarez↗