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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Gridded Vegetation and Land Unit Datasets over North America (1km x 1km) for E3SM Land Model, Version 2

Gridded 1 km land-surface-property dataset for Energy Exascale Earth System Model Land Model (ELM) simulations over North America. Thirty-metre NALCMS land cover is aggregated to the Daymet grid; vegetation classes are cross-walked to ELM plant functional types using mean-temperature-of-the-coldest-month (MTCO) rules. NetCDF includes PFT and land-unit fractions, counts, and MTCO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 4.

To address the need for a centralized root trait database, we compiled the Fine-Root Ecology Database (FRED) from published and unpublished data sources. We have continued to add to the FRED database since the release of FRED 1.0 in 2017, followed by 2.0 in 2018, and 3.0 in 2021. This new release of FRED 4.0 now has 213,941 observations of 238 root traits, for a combined total of roughly 3.4 million data fields for root traits and ancillary data together. FRED 4.0 has 39.8% more root trait observations than FRED 3.0 and a 34.4% increase in unique data sources. This release of FRED 4.0 also includes significant increases in geographic regions that have long been underrepresented in global datasets, notably in the tropical low latitudes. Ancillary data on associated site, vegetation, edaphic, and climatic conditions from across the globe have also increased concurrently with root trait observations. FRED is focused on fine roots (traditionally defined as roots less than 2 mm in diameter), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations. Despite this fine-root focus, FRED accepts data collected from roots of all sizes and contains observations of many root classes including coarse roots. Data collection will continue for the foreseeable future. The FRED4_Entire_Database_2026.csv file is the flat csv data file for FRED 4.0, and the FRED4_dd.csv file is the data dictionary of all columns available in FRED, including column IDs, column names, definitions, and unit (where applicable).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for Regier et al. (2025), "Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest"

Rising sea levels and intensifying storms increase flooding pressure on coastal forests, but the mechanisms that drive coastal forest mortality remain unclear. This study used an ecosystem-scale manipulation (TEMPEST, Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments) to simulate hurricane-level flooding of a coastal forest and explore the individual and interactive impacts of inundation and salinity. This dataset comprises the results reported by Regier et al. (2025) in their paper "Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest." It consists of measurements of:- Belowground conductance- Soil dissolved oxygen and redox- Soil and tree greenhouse gas fluxes- Leaf photosynthesis, stomatal conductance, and intercellular carbon dioxide- Sap flux- Soil volumetric water content and electrical conductivityAll files are plain-text CSV (comma separated value) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

SPRUCE: Shrub-Layer Vegetation Biomass Collection Metadata, Marcell Experimental Forest, Minnesota, August 2025

This data set contains metadata associated with shrub-layer vegetation samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. See below under 7 Sample Access. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B069L. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.

Birkebak, Joshua [ORNL] (ORCID:0009000955611494)↗
DOE OSTI2021

Process-based Neural Network to Forecast Vegetation Dynamics

This white paper calls for an AI-based emulator of DOE’s dynamic vegetation model that is computationally efficient and accommodates/parameterizes the governing processes built in the model. This AI-based emulator is needed for model calibration, sensitivity analysis, prediction, uncertainty quantification, and decision making. This AI-based emulator will incorporate physics and biological information in the form of conservation laws and constitutive relationships.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Predicting Switchgrass Biomass Yields Using a Spectral Vegetation Index Derived from Multispectral Satellite Imagery

Successful scaling of perennial bioenergy crop production requires a landscape design that optimizes the benefits of finite lands for people, communities, and environments. Utilizing marginal areas is the key to sustainable bioenergy crop production (Ssegane et al., 2015, 2016). Marginal areas are often small-sized lands and unevenly distributed across the agricultural landscape (Ssegane et al., 2016); thus, a systematic, semi-automated remote sensing method is needed as an effective means of estimating bioenergy crop yields across landscapes. Argonne National Laboratory (Argonne) is currently developing a tool, Scaling Up Perennial Bioenergy Economics and Ecosystem Services Tool (SUPERBEEST), to identify marginal agricultural lands and quantify environmental and economic effects of perennial bioenergy crop production systems. The tool aims to provide users a path to foster the sustainable and productive integration of bioenergy crops in the Midwestern agricultural landscape. Reliable, cost-effective, and timely estimation of bioenergy crop yields using remote sensing would help calculate and track the success of integrated bioenergy crops in the landscape for those communities. Argonne previously conducted feasibility studies for estimating biomass yields for bioenergy feedstock, corn and perennial grass using spectral vegetation indices (SVIs)1 derived from optical imagery (Hamada et al., 2015, 2021). In both studies, SVIs, more specifically those sensitive to plant chlorophyll or nitrogen contents, showed potential for estimating or predicting biomass yields with a correlation of determination (R2) ranging from 0.54 to 0.96, indicating a value for further investigation as a viable means of quantifying bioenergy feedstock production across large landscapes. Thus, the goal of this study is to evaluate the feasibility of use of SVIs as a means of estimating or predicting switchgrass biomass yields at harvest using publicly available multispectral satellite imagery. The feasibility analysis was performed using four study areas of mature switchgrass located in Virginia. Objectives are to (1) examine the SVIs and establish their relationships with switchgrass biomass yields at harvest, (2) develop a parsimonious image processing model for predicting at-harvest yields by applying the relationships with the most promising spectral index and (3) map switchgrass yields predicted by the image processing model across the study sites. The calibration to field data will rely on switchgrass biomass yields determined by the baling method, representing a potential challenge to the analysis but an important practical aspect for future applications. With this research design, the study aimed to gain insights into enabling remote sensing-based estimation of bioenergy crop yields in a reliable, cost- effective, and timely manner across large, heterogeneous landscapes.

09 BIOMASS FUELS↗
DOE OSTI2024

Methane dynamics described through vegetation-soil interactions in bald cypress and other bottomland hardwood forests

Past estimates of CH4 fluxes from forested swamps ranged from 10 to 106 mg C m-2 d-1 in temperate regions and 44 to144 mg C m-2 d-1 in subtropical and tropical regions. However, climate change could alter these rates in wetlands where efflux is predominantly controlled by water level, temperature, and plant composition. While the Lower Mississippi Alluvial Valley has experienced the largest loss of forested wetlands in the U.S, supporting 21 to 25 million acres of bottomland hardwoods before European settlement, an estimated 5 million acres remain. This landscapes remain under-studied from a CH4 flux perspective, particularly in determining woody vegetation contributions to landscape CH4 emissions. Our overarching objective are to (1) improve our understanding of the controls on CH4 fluxes in forested mineral soil wetlands, and (2) to better understand the effects of landscape position and forest composition on the CH4 fluxes between terrestrial ecosystems and the atmosphere. Our main goal is to elucidate the

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Using satellite data to assess Hurricane Helene’s impact on vegetation by land use in the CSRA

Many regions within Georgia, South Carolina, and North Carolina experienced record-breaking rainfall and catastrophic winds due to Hurricane Helene. Helene made landfall on Florida’s big bend on September 26 th , 2024, as a category 4 hurricane, and tracked northward through Georgia and the southern Appalachian Mountains before dissipating on September 29 th , 2024. One significant impact of the hurricane was severe damage to tree canopies across the southeastern United States. This study utilizes satellite-based remotely sensed data provided by the National Aeronautical and Space Administration (NASA) to examine the resilience of these tree canopies following the hurricane. Specifically, the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Land Cover Type, Soil Moisture Active Passive (SMAP), and the Global Precipitation Measurement (GPM) mission datasets were employed to study the tree canopy’s response to such events in the Central Savannah River Area (CSRA). A significant increase was observed in the LAI in November of 2024. This increase in LAI was likely influenced by warmer-than-average temperatures throughout October of 2024, along with a second record-breaking rainfall event in the CSRA on November 6th, 2024. The LAI increase was then broken down into land cover type to understand which areas contributed most. The complex nature and resilience of trees became evident, offering opportunities for further exploration and application in urban planning, emergency response, and environmental management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hanford Site Post-Fire Vegetation Monitoring Report for Calendar Year 2025

The Hanford Site and the surrounding greater Columbia Basin is comprised of an expanse of shrub-steppe habitats that provides exceptional ecological value to plants and animals. The U.S. Department of Energy, Hanford Field Office (HFO)-managed portion of the Hanford Site, referred to from herein as Central Hanford, has experienced repeated wildfires resulting in profound, often adverse, effects on the landscape. This report summarizes these fires and fire monitoring efforts that occurred in calendar year (CY) 2025 and analyzes the post-fire vegetation recovery in restored areas to inform future post-fire response actions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 3.

To address the need for a centralized root trait database, we compiled the Fine-Root Ecology Database (FRED) from published and unpublished data sources. We have continued to add to the FRED database since the release of FRED 2.0 in 2018, and a new version of FRED is now available. FRED 3.0 has more than 150,000 observations of more than 330 root traits, with data collected from more than 1400 data sources. FRED 3.0 has 45% more root trait observations than FRED 2.0, particularly in the categories of root anatomy, morphology, and microbial associations; ancillary data on associated site, vegetation, edaphic, and climatic conditions from across the globe have also increased concurrently. FRED is focused on fine roots (traditionally defined as roots less than 2 mm in diameter), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations. However, FRED accepts data collected from roots of all sizes, and already contains several observations of coarse roots. Data collection will continue for the foreseeable future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

SPRUCE Diurnal and Seasonal Patterns of Water Potential in S1 Bog and SPRUCE Experimental Plot Vegetation beginning in 2010

This data set reports on water potential from excised terminal shoots or leaves (Mainthemum only) of vegetation at the SPRUCE site located in the S1 bog. Pretreatment measurements were collected from outside plots within the S1 bog. Post treatments were collected from inside SPRUCE plots. Water potential was measured on the overstory canopy species, consisting of the evergreen Picea mariana (Mill.) B.S.P. (black spruce) and deciduous Larix laricina (Du Roi) K. Koch (tamarack) trees, and ericaceous shrubs < 1 m tall, consisting of the evergreen Rhododendron groenlandicum (Oeder) Kron & Judd (Labrador tea) and Chamaedaphne calyculata (L.) Moench. (leatherleaf). Some measurement campaigns also included the evergreen Kalmia polifolia, Wangenh. (bog laurel), the deciduous Vaccinium angustifolium (Aiton) (blueberry), and the herbaceous Maianthemum trifolium (L.) Sloboda (three-leaf false Solomon’s seal). This dataset contains one data file in comma-separated (*.csv) format. This is the second release of water potential data from the site with additional data from 2018 and 2019. These data cover 2010-06-22 to 2019-07-16. Further results will be added to this data set and released to the public periodically as quality assurance and publication of results are accomplished. There are 10 experimental plots in SPRUCE: five temperature treatments (+0, +2.25, +4.5, +6.75, +9°C) at ambient CO2, and the same five temperature treatments at elevated CO2 (+500 ppm). These data span the pre- and post-treatment periods when enclosed plots were exposed to warming and elevated carbon dioxide (CO2) within the SPRUCE experiment. The pretreatment samples were collected from south end of the S1 bog prior to SPRUCE boardwalk construction, then throughout the bog once the boardwalks were completed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Advanced monitoring of soil-vegetation co-dynamics reveals the successive controls of snowmelt on soil moisture and on plant seasonal dynamics in a mountainous watershed

Evaluating the interactions between above- and below-ground processes is important to understand and quantify how ecosystems respond differently to atmospheric forcings and/or perturbations and how this depends on their intrinsic characteristics and heterogeneity. Improving such understanding is particularly needed in snow-impacted mountainous systems where the complexity in water and carbon storage and release arises from strong heterogeneity in meteorological forcing and terrain, vegetation and soil characteristics. This study investigates spatial and temporal interactions between terrain, soil moisture, and plant seasonal dynamics at the intra- and inter-annual scale along a 160 m long mountainous, non-forested hillslope-to-floodplain system in the upper East River Watershed in the upper Colorado River Basin. To this end, repeated UAV-based multi-spectral aerial imaging, ground-based soil electrical resistivity imaging, and soil moisture sensors were used to quantify the interactions between above and below-ground compartments. Results reveal significant soil-plant co-dynamics. The spatial variation and dynamics of soil water content and electrical conductivity, driven by topographic and soil intrinsic characteristics, correspond to distinct plant types, with highest plant productivity in convergent areas. Plant productivity in heavy snow years benefited from more water infiltration as well as a shallow groundwater table depth. In comparison, low snowpack years with an early first bare-ground date, which are linked to an early increase in plant greenness, imply a short period of saturated conditions that leads to lower average and maximum greenness values during the growing season. Overall, these results emphasize the strong impact of snowpack dynamics, and terrain and subsurface characteristics on the heterogeneity in plant type and seasonal dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Mobilizing Vacuolar Sugar Increases Vegetative Triacylglycerol Accumulation

Photosynthetically derived sugars provide carbon skeletons for metabolism and carbon signals that favor anabolism. The amount of sugar available for fatty acid (FA) and triacylglycerol (TAG) synthesis depends on sugar compartmentation, transport, and demands from competing pathways. We are exploring the influence of sugar partitioning between the vacuole and cytoplasm on FA synthesis in Arabidopsis by building on our previous finding that reduced leaf sugar export in the sucrose-proton symporter2 (suc2) mutant, in combination with impaired starch synthesis in the ADP-glucose pyrophosphorylase (adg1) mutant, accumulates higher sugar levels and increased total FA and TAG compared to the wild type parent. Here we sought to relocalize sugar from the vacuole to the cytoplasm to drive additional FA/TAG synthesis and growth. Arabidopsis suc2 adg1 was therefore crossed with tonoplast monosaccharide transporter mutants tmt1 and tmt2 and overexpression of the sucrose/proton cotransporter SUC4 in which tmt1 tmt2 impairs sugar transport to the vacuole from the cytoplasm and SUC4 overexpression enhances sugar transport in the reverse direction from the vacuole to the cytoplasm. A resulting homozygous suc2 adg1 tmt1 tmt2 SUC4 line was used to test the hypothesis that increased intracellular carbon supply in the form of sugars would increase both FA and TAG accumulation. The data shows that relative to suc2 adg1, suc2 adg1 tmt1 tmt2 SUC4 significantly increases leaf total FA content by 1.29-fold to 10.9% of dry weight and TAG by 2.4-fold to 2.88%, supporting the hypothesis that mobilizing vacuolar sugar is a valid strategy for increasing vegetative oil accumulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Functional Diversification of Populus FLOWERING LOCUS D-LIKE3 Transcription Factor and Two Paralogs in Shoot Ontogeny, Flowering, and Vegetative Phenology

Both the evolution of tree taxa and whole-genome duplication (WGD) have occurred many times during angiosperm evolution. Transcription factors are preferentially retained following WGD suggesting that functional divergence of duplicates could contribute to traits distinctive to the tree growth habit. We used gain- and loss-of-function transgenics, photoperiod treatments, and circannual expression studies in adult trees to study the diversification of three Populus FLOWERING LOCUS D-LIKE (FDL) genes encoding bZIP transcription factors. Expression patterns and transgenic studies indicate that FDL2.2 promotes flowering and that FDL1 and FDL3 function in different vegetative phenophases. Study of dominant repressor FDL versions indicates that the FDL proteins are partially equivalent in their ability to alter shoot growth. Like its paralogs, FDL3 overexpression delays short day-induced growth cessation, but also induces distinct heterochronic shifts in shoot development—more rapid phytomer initiation and coordinated delay in both leaf expansion and the transition to secondary growth in long days, but not in short days. Our results indicate that both regulatory and protein coding sequence variation contributed to diversification of FDL paralogs that has led to a degree of specialization in multiple developmental processes important for trees and their local adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Investigations on the Thermal Stability and Kinetics of Biolubricants Synthesized from Different Types of Vegetable Oils

Petroleum-based lubricants raise environmental concerns due to their non-biodegradability and toxicity, whereas biobased lubricants underperform owing to low thermal stability. This study examined and compared three vegetable oils, along with their chemically modified versions, to better understand their suitability as biolubricants. High oleic soybean oil (HOSOY), regular soybean oil (RSOY), and waste cooking oil (WCO) were subjected to chemical modification, where isopropyl groups were attached to the fatty acid chains of the oils to produce branched oils, i.e., b-HOSOY, b-RSOY, and b-WCO. The detailed kinetic study of each regular and modified sample was investigated using thermogravimetric analysis. The kinetic parameters, such as the activation energies, reaction rate, and pre-exponential factor, were generated via Friedman methods. The differential thermal gravimetric (DTG) analysis showed low volatilization at the onset temperature in each modified oil as compared with the unmodified samples under an oxidative environment. Furthermore, the comparative kinetic studies demonstrated the enhanced thermoxidative stability of the modified products relative to their unaltered counterparts. Among the tested oils, the b-RSOY showed an average activation energy of 325 kJ/mol, followed by the b-WCO: 300 kJ/mol and the b-HOSOY: 251 kJ/mol, indicating the most stable modified product under an oxidative environment. For all the samples, the pre-exponential factors were in good agreement with the activation energies, which validates that finding the pre-exponential components is crucial to the kinetic analysis.

Sarker, Majher I. (ORCID:0000000299509274)↗
DOE OSTI2022

Consistent responses of vegetation gas exchange to elevated atmospheric CO 2 emerge from heuristic and optimization models

Elevated atmospheric CO 2 concentration is expected to increase leaf CO 2 assimilation rates, thus promoting plant growth and increasing leaf area. It also decreases stomatal conductance, allowing water savings, which have been hypothesized to drive large-scale greening, in particular in arid and semiarid climates. However, the increase in leaf area could reduce the benefits of elevated CO 2 concentration through soil water depletion. The net effect of elevated CO 2 on leaf- and canopy-level gas exchange remains uncertain. To address this question, we compare the outcomes of a heuristic model based on the Partitioning of Equilibrium Transpiration and Assimilation (PETA) hypothesis and three model variants based on stomatal optimization theory. Predicted relative changes in leaf- and canopy-level gas exchange rates are used as a metric of plant responses to changes in atmospheric CO 2 concentration. Both model approaches predict reductions in leaf-level transpiration rate due to decreased stomatal conductance under elevated CO 2 , but negligible (PETA) or no (optimization) changes in canopy-level transpiration due to the compensatory effect of increased leaf area. Leaf- and canopy-level CO 2 assimilation is predicted to increase, with an amplification of the CO 2 fertilization effect at the canopy level due to the enhanced leaf area. The expected increase in vapour pressure deficit (VPD) under warmer conditions is generally predicted to decrease the sensitivity of gas exchange to atmospheric CO 2 concentration in both models. The consistent predictions by different models that canopy-level transpiration varies little under elevated CO 2 due to combined stomatal conductance reduction and leaf area increase highlight the coordination of physiological and morphological characteristics in vegetation to maximize resource use (here water) under altered climatic conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Machine-learning-based estimates of global natural vegetated wetland methane emissions (2000–2025)

Wetlands are the largest natural source of atmospheric methane (CH 4 ), yet comprehensive global budgets are typically delayed by years, preventing a timely understanding of CH 4 sources, sinks, and trends. To reduce this delay, we present a model emulator-driven framework and accompanying workflow that enable timely, continuous emission updates using a machine-learning emulator to reconstruct spatially explicit monthly emission fields at 1° × 1° resolution. We apply this framework to a global dataset of natural vegetated wetland CH 4 emissions to extend the most recent Global Methane Budget (GMB; Saunois et al., 2025) record that covers the 2000–2020 emissions through 2025. In the test data (∼ 30 % of the total dataset), the emulator achieved a global R 2 of 0.65 ± 0.003 (mean ± 95 % CI, hereafter) and an RMSE of 5.49 ± 0.12×10 -3 Tg CH 4 yr −1 . The emulator is trained on 35 GMB model estimates, including 22 process-based models and 13 atmospheric inversions, paired with 10 ensemble realizations of 11 gridded climate predictor variables from atmospheric reanalyses. Our results show that the global mean predicted wetland CH 4 emissions for 2021–2025 (157.8 ± 2.4 Tg CH 4 yr −1 ) are not significantly higher (∼ 0.05 Tg CH 4 yr −1 ) than the 2000–2020 baseline. However, this stability masks a significant hemispheric redistribution of emissions. We detect an increase in Northern Hemisphere (NH) emissions in 2021–2025, with mid- and high-latitudes increasing by 0.76 ± 0.07 and 0.35 ± 0.03 Tg CH 4 yr −1 , respectively, while the tropics and Southern Hemisphere (SH) extratropics show offsetting negative trends (−0.95 ± 0.19 and -0.11 ± 0.02 Tg CH 4 yr −1 , respectively). The predicted emissions are able to capture the low emissions in 2023 in South America linked to El Niño-related drought, as reported by recent studies (Ciais et al., 2026; Quinn et al., 2025). Furthermore, we identify a distinct seasonal amplification of global emission trends that peaks in late boreal summer. This new modeled dataset and operational framework bridge the gap between the latest updated budgets and low-latency monitoring, providing a scalable capacity to frequently update global emission estimates and critical early warnings of regional wetland feedback loops. The data are publicly available at https://doi.org/10.5281/zenodo.18870108 (Li et al., 2026).

Li, Mengze [National University of Singapore (Sing↗