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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

New tree-ring data from Canadian boreal and hemi-boreal forests provide insight for improving the climate sensitivity of terrestrial biosphere models

Understanding boreal/hemi-boreal forest growth sensitivity to seasonal variations in temperature and water availability provides important basis for projecting the potential impacts of climate change on the productivity of these ecosystems. Our best available information currently comes from a limited number of field experiments and terrestrial biosphere model (TBM) simulations of varying predictive accuracy. Here, we assessed the sensitivity of annual boreal/hemi-boreal forest growth in Canada to yearly fluctuations in seasonal climate variables using a large tree-ring dataset and compared this to the climate sensitivity of annual net primary productivity (NPP) estimates obtained from fourteen TBMs. We found that boreal/hemi-boreal forest growth sensitivity to fluctuations in seasonal temperature and precipitation variables changed along a southwestern to northeastern gradient, with growth limited almost entirely by temperature in the northeast and west and by water availability in the southwest. We also found a lag in growth climate sensitivity, with growth largely determined by the climate during the summer prior to ring formation. Analyses of NPP sensitivity to the same climate variables produced a similar southwest to northeast gradient in growth climate sensitivity for NPP estimates from all but three TBMs. However, analyses of growth from tree-ring data and analyses of NPP from TBMs produced contrasting evidence concerning the key climate variables limiting growth. While analyses of NPP primarily indicated a positive relationship between growth and seasonal temperature, tree-ring analyses indicated negative growth relationships to temperature. Also, the positive effect of precipitation on NPP derived from most TBMs was weaker than the positive effect of precipitation on tree-ring based growth: temperature had a more important limiting effect on NPP than tree-ring data indicated. These mismatches regarding the key climate variables limiting growth suggested that characterization of tree growth in TBMs might need revision, particularly regarding the effects of stomatal conductance and carbohydrate reserve dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Soil Candidate Phyla Radiation Bacteria Encode Components of Aerobic Metabolism and Co-occur with Nanoarchaea in the Rare Biosphere of Rhizosphere Grassland Communities

Here, we investigated overlooked microbes in soil, candidate phyla radiation (CPR) bacteria and Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, and Nanohaloarchaeota (DPANN) archaea, by size fractionating small particles from soil, an approach typically used for the recovery of viral metagenomes. Concentration of these small cells (<0.2 μm) allowed us to identify these organisms as part of the rare soil biosphere and to sample genomes that were absent from non-size-fractionated metagenomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Influence of Vegetation Canopy Architecture on Dynamics of Spatiotemporal Light Distribution and its Effect on Land-Biosphere-Atmosphere Fluxes of Energy, Carbon, and Water

The dynamic spatiotemporal distribution of light and micro climatic variables (wind speed, atmospheric CO 2 concentration, humidity, pressure, and air temperature) within the plant canopy as determined by the canopy architecture play a critical role in land-biosphere-atmosphere (LBA) photosynthetic carbon uptake, transpiratory water loss and energy partitioning. Vegetation models that include effects of sun and shade flecks, leaf temperature and energy balance partitioning between sensible and latent heat fluxes, and reduced turbulent mixing in dense vegetation canopies can accurately predict canopy performance, particularly its shaded leaves, which can constitute 80% of leaf area and contribute up to 50% of carbon update and 65% of water loss. However, current vegetation models with their bulk characterization of shaded leaves poorly represent the complex three dimensional (3D) canopy architecture are insufficient to capture the spatiotemporal dynamics of shaded leaves. Here, we propose to employ an x-ray computed tomography (XCT) imaging technique in combination with an automated, high throughput, image processing pipeline (3DArch, to be developed) to obtain an explicit 3D triangulated surface mesh of a plant canopy (Fig 1). 3DArch would provide a much needed technological jump in 3D LBA modeling where computer generated artificial 3D models suffer from lack of high resolution detailed canopy architecture parameters. The 3D canopy surface mesh output from 3DArch is coupled with an explicit 3D forward ray tracing model (fastTracer) to obtain a high resolution representation of the dynamic spatiotemporal light environment within the canopy over the course of a day (Fig 1). The results from the light attenuation model are then coupled with a process based multi-scale bio-physical canopy and leaf model of photosynthesis (PlantGro) to get fluxes of carbon, water and energy at the leaf and canopy scale, in addition to estimating whole plant carbon uptake, and water loss. Our proposed model framework would be the first of its kind to provide a breakthrough capability in the field of process-based plant modeling that bridges the key technological gap in shaded leaf modeling through explicit representation of 3D canopy architecture. Computer generated artificial 3D model canopy simulations on grasses show that the canopy light distribution does not follow an exponential behavior as assumed in most 1D vegetation models, but rather exhibits a heterogeneous behavior, with a small but significant portion of interior canopy leaves experiencing peak light levels due to sun flecks while the rest of the canopy receives substantially lower light levels. These results indicate a bias in traditional models that overestimates shaded leaf contribution towards whole canopy photosynthesis by up to 15% and underestimate transpiration by up to 12% with an associated increase in sensible heat fluxes since photosynthesis, transpiration and energy partitioning are tightly coupled processes. However, these test results need to be validated using the 3D architecture obtained from a real plant imaged in 3D using 3DArch, rather than an artificial model plant. Our proposed model framework would allow us to identify inefficiencies in canopy light distribution and prescribe optimal canopy architectures (leaf optical properties, leaf area, leaf angles, row spacing, planting density, etc.) to traditional and genetic engineering based crop breeders, for maximizing target functions such as light use efficiency, water use efficiency, drought tolerance, crop yield, crop resilience etc., with important applications in biofuel crops such as sorghum, and switchgrass. Our model can also be applied for designing optimal canopy architecture that increase surface albedo as a mitigation strategy for global warming and projections of crop yield for future food and water security under climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model

In spite of the importance of land ecosystems in offsetting carbon dioxide emissions released by anthropogenic activities into the atmosphere, the spatiotemporal dynamics of terrestrial carbon fluxes remain largely uncertain at regional to global scales. Over the past decade, data assimilation (DA) techniques have grown in importance for improving these fluxes simulated by terrestrial biosphere models (TBMs), by optimizing model parameter values while also pinpointing possible parameterization deficiencies. Although the joint assimilation of multiple data streams is expected to constrain a wider range of model processes, their actual benefits in terms of reduction in model uncertainty are still under-researched, also given the technical challenges. In this study, we investigated with a consistent DA framework and the ORCHIDEE-LMDz TBM–atmosphere model how the assimilation of different combinations of data streams may result in different regional to global carbon budgets. To do so, we performed comprehensive DA experiments where three datasets (in situ measurements of net carbon exchange and latent heat fluxes, spaceborne estimates of the normalized difference vegetation index, and atmospheric CO 2 concentration data measured at stations) were assimilated alone or simultaneously. We thus evaluated their complementarity and usefulness to constrain net and gross C land fluxes. We found that a major challenge in improving the spatial distribution of the land C sinks and sources with atmospheric CO 2 data relates to the correction of the soil carbon imbalance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Accessing the Subsurface Biosphere Within Rocks Undergoing Active Low-Temperature Serpentinization in the Samail Ophiolite (Oman Drilling Project)

The Oman Drilling Project established an “Active Alteration” multi-borehole observatory in peridotites undergoing low-temperature serpentinization in the Samail Ophiolite. The highly serpentinized rocks are in contact with strongly reducing fluids. Distinct hydrological regimes, governed by differences in rock porosity and fracture density, give rise to steep redox (Eh +200 to –750 mV) and pH (pH range 8.5–11.2) gradients within the 300–400 m deep boreholes. The serpentinites and fluids host an active subsurface ecosystem. Microbial cell abundances in serpentinite vary at least six orders of magnitude, from ≤3.5 × 10 1 to 2.9 × 10 7 cells/g. Low levels of biological sulfate reduction (2–1,000 fmol/cm 3 /day) can be detected in rock cores, particularly in rocks in contact with reduced groundwaters with pH < 10.5. Thermodesulfovibrio is the predominant sulfate reducer identified via metagenomic sequencing of adjacent groundwater communities. Here, we infer that transport and reaction of microbially generated sulfide with the serpentine and brucite assemblages gives rise to optical darkening and sulfide overprinting, including the formation of tochilinite-vallerite group minerals, potentially serving as an indicator that this system is inhabited by microbial life. Olivine mesh-cores replaced with ferroan brucite and minor awaruite, abundant veins containing hydroandradite garnet and polyhedral serpentine, and late-stage carbonate veins are suggested as targets for future spatially resolved life-detection investigations. The high-quality whole-round core samples that have been preserved can be further probed to define how life distributes itself and functions within a system where chemical disequilibria are sustained by low-temperature water/rock interaction, and how biosignatures of in situ microbial activity are generated.

58 GEOSCIENCES↗
DOE OSTI2020

Automated Integration of Continental-Scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interactions

The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new machine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are already building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance.

Durden, David J.↗
DOE OSTI2024

Nutrient Dynamics in a Coupled Terrestrial Biosphere and Land Model (ELM-FATES-CNP)

We present a representation of nitrogen and phosphorus cycling in the Functionally Assembled Terrestrial Ecosystem Simulator, a demographic vegetation model within the Energy Exascale Earth System land model. This representation is modular, and designed to allow testing of multiple hypothetical approaches for carbon-nutrient coupling in plants. Novel model hypotheses introduced in this work include, (a) the controls on plant acquisition of aqueous mineralized nutrients in the soil and (b) fairly straight forward methods of allocating nutrients to specific plant organs and their losses through live plant turnover as well as litter fluxes generated through plant mortality. This combines the new with pre-existing hypotheses (such as nitrogen fixation and soil decomposition) into a system that can accommodate plant-soil dynamics for a large number of size- and functional-type-resolved plant cohorts within a time-since-disturbance-resolved ecosystem. Root uptake of nutrients is governed by fine root biomass, and plants vary in their fine root biomass allocation in order to balance carbon and nutrient limitations to growth. We test the sensitivity of the model to a wide range of parameter variations and structural representations, and in the context of observations at Barro Colorado Island, Panama. A key model prediction is that plants in the high-light-availability canopy positions allocate more carbon to fine roots than plants in low-light understory environments, given the widely different carbon versus nutrient constraints of these two niches within a given ecosystem. This model provides a basis for exploring carbon-nutrient coupling with vegetation demography within Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Lipid analysis of CO 2 -rich subsurface aquifers suggests an autotrophy-based deep biosphere with lysolipids enriched in CPR bacteria

Sediment-hosted CO 2 -rich aquifers deep below the Colorado Plateau (USA) contain a remarkable diversity of uncultivated microorganisms, including Candidate Phyla Radiation (CPR) bacteria that are putative symbionts unable to synthesize membrane lipids. The origin of organic carbon in these ecosystems is unknown and the source of CPR membrane lipids remains elusive. We collected cells from deep groundwater brought to the surface by eruptions of Crystal Geyser, sequenced the community, and analyzed the whole community lipidome over time. Characteristic stable carbon isotopic compositions of microbial lipids suggest that bacterial and archaeal CO 2 fixation ongoing in the deep subsurface provides organic carbon for the complex communities that reside there. Coupled lipidomic-metagenomic analysis indicates that CPR bacteria lack complete lipid biosynthesis pathways but still possess regular lipid membranes. These lipids may therefore originate from other community members, which also adapt to high in situ pressure by increasing fatty acid unsaturation. An unusually high abundance of lysolipids attributed to CPR bacteria may represent an adaptation to membrane curvature stress induced by their small cell sizes. Our findings provide new insights into the carbon cycle in the deep subsurface and suggest the redistribution of lipids into putative symbionts within this community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Causal interaction in high frequency turbulence at the biosphere–atmosphere interface: Structural behavior

High-frequency (e.g., 10 Hz) eddy covariance measurements are typically used to estimate fluxes at the land–atmosphere interface at timescales of 15–60 min. These multivariate data contain information about the interdependency at high frequency between the interacting variables such as wind, humidity, temperature, and CO 2⁠ . We use data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US, which offers an opportunity to move beyond the traditional spectral analyses to explore causal dependency among variables. In this study, we quantify the structure of inter-dependencies of interacting variables at high frequency represented by a directed acyclic graph (DAG). We compare DAGs to investigate changes in structural differences in causal interactions. We then apply a distance-based classification and -means clustering approach to identify the evolution of the causal structure represented by a DAG. Our method selects an unbiased number of clusters of similar structures and characterizes the similarities and differences between them. We explore a range of dynamic behavior using data from a clear sky day and during a solar eclipse in 2017. Our results show well-defined clusters of similar causal dependencies as the system evolves. Furthermore, our approach provides a methodological framework to understand how causal dependence in turbulence manifests in high-frequency data when represented through a DAG.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Predominance of Methanomicrobiales and diverse hydrocarbon–degrading taxa in the Appalachian coalbed biosphere revealed through metagenomics and genome–resolved metabolisms

Coalbed deposits are a unique subsurface environment and represent an underutilized resource for methane generation. Microbial communities extant in coalbed deposits are responsible for key subsurface biogeochemical cycling and could be utilized to enhance methane production in areas where existing gas wells have depleted methane stores, or in coalbeds that are unmined, or conversely be utilized for mitigation of methane release. Here we utilize metagenomics and metagenome-assembled genomes to identify extant microbial lineages and genome-resolved microbial metabolisms of coalbed produced water, which has not yet been explored in the Appalachian Basin. Our analyses resulted in the recovery of over 40 metagenome-assembled genomes (MAGs) from eight coalbed methane wells. The most commonly identified taxa among samples were hydrogenotrophic methanogens from the order Methanomicrobiales and these dominant MAGs were highly similar to one another. Conversely, low-abundance coalbed bacterial populations were taxonomically and functionally diverse, mostly belonging to a variety of Proteobacteria classes, and encoding various hydrocarbon solubilization and degradation pathways. Further, the data presented herein provides novel insights into Appalachian Basin coalbed microbial ecology, and our findings provide new perspectives on underrepresented Methanocalculus species and low-relative abundance bacterial assemblages in coalbed environments, and their potential roles in stimulation or mitigation of methane release.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Triose phosphate utilization limitation: an unnecessary complexity in terrestrial biosphere model representation of photosynthesis

Triose phosphates are the principal product of photosynthesis. They are used within the chloroplast for starch synthesis, or translocated to the cytosol where they are used to fuel sucrose synthesis. Use of triose phosphate releases inorganic phosphate, and is under strict metabolic control that matches the supply of triose phosphate from the Calvin-Benson cycle to the demand for carbon by sinks (Heldt & Heldt, 2011; McClain & Sharkey, 2019). However, a low rate of triose phosphate utilization (TPU) can deplete the phosphate pool, restrict ATP synthesis and reduce the availability of ATP to power the Calvin-Benson cycle, thereby limiting photosynthesis (Sharkey, 1985).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Advantages of Combining Morphological and Molecular Methods to Characterise Zooplankton Communities: A Case Study of the UNESCO Biosphere Reserve of the Berlengas Archipelago, Portugal

Understanding the ecological dynamics of zooplankton communities is crucial to precisely assessing the health of marine ecosystems and their management. Metabarcoding has contributed to a better understanding of biodiversity in marine environments. However, this methodology still requires protocol optimisation. Here, we used a complementary approach combining molecular and morphological identification methods to identify the zooplankton community inhabiting the Berlengas Archipelago, Portugal. The presence of non-indigenous species was also assessed. The results showed that the metabarcoding approach outperformed the classical morphological identification method, detecting more species with higher resolution. Nevertheless, the classical method was able to identify species that were not detected by the molecular approaches, probably due to a lack of reference data in the databases. The comparison between different molecular approaches showed that COI and bulk DNA gave better results than 18S rRNA and eDNA by detecting higher species diversity. However, complementarities were observed between them. Molecular tools also proved effective in identifying several potential non-indigenous species, identifying, for the first time, several potentially unreported NIS inhabiting the Portuguese marine ecosystems. Overall, our results confirmed the importance of combining both classical and molecular methods to obtain a more refined assessment of the zooplanktonic communities in marine environments.

Simões, Marco (ORCID:0000000179957304)↗
DOE OSTI2021

Utilizing Earth Observations of Soil Freeze/Thaw Data and Atmospheric Concentrations to Estimate Cold Season Methane Emissions in the Northern High Latitudes

The northern wetland methane emission estimates have large uncertainties. Inversion models are a qualified method to estimate the methane fluxes and emissions in northern latitudes but when atmospheric observations are sparse, the models are only as good as their a priori estimates. Thus, improving a priori estimates is a competent way to reduce uncertainties and enhance emission estimates in the sparsely sampled regions. Here, we use a novel way to integrate remote sensing soil freeze/thaw (F/T) status from SMOS satellite to better capture the seasonality of methane emissions in the northern high latitude. The SMOS F/T data provide daily information of soil freezing state in the northern latitudes, and in this study, the data is used to define the cold season in the high latitudes and, thus, improve our knowledge of the seasonal cycle of biospheric methane fluxes. The SMOS F/T data is implemented to LPX-Bern DYPTOP model estimates and the modified fluxes are used as a biospheric a priori in the inversion model CarbonTracker Europe-CH 4 . The implementation of the SMOS F/T soil state is shown to be beneficial in improving the inversion model’s cold season biospheric flux estimates. Our results show that cold season biospheric CH4 emissions in northern high latitudes are approximately 0.60 Tg lower than previously estimated, which corresponds to 17% reduction in the cold season biospheric emissions. This reduction is partly compensated by increased anthropogenic emissions in the same area (0.23 Tg), and the results also indicates that the anthropogenic emissions could have even larger contribution in cold season than estimated here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Microanalysis of Primary Biological Particles from Model Grass over Its Life Cycle

Airborne biological aerosols are an integral part of the atmosphere–biosphere interface and significantly impact the environment and Earth’s climate. Primary biological particles such as fungal spores, bacteria, and fragments of plant debris are emitted directly from the biosphere into the atmosphere. The phyllosphere (aboveground plant surfaces) is one of the major habitats for different microbes. Here, atmospheric emissions of primary biological particles from model grass Brachypodium distachyon were monitored by online particle number concentration counting at eight principal growth stages starting from leaf development to senescence. Particles collected at each of the growth stages were then characterized using microspectroscopy techniques. Our findings indicate that the morphological and compositional characteristics of emitted biological particles are highly variable at the different growth stages. We identified fungal spores as the most abundant biological particles in the heading stage, while bacteria were most abundant in the flowering and fruit development stages. Understanding differences in the composition and morphology of biological particles during the plant life cycle provides more accurate and reliable insights on structural, functional, and biochemical properties of plant systems, as well as their interactions with microbial communities. This study also provides insights into Earth geoscience system models that represent primary biological particle emissions from the biosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Novel candidate taxa contribute to key metabolic processes in Fennoscandian Shield deep groundwaters

The continental deep biosphere contains a vast reservoir of microorganisms, although a large proportion of its diversity remains both uncultured and undescribed. In this study, the metabolic potential (metagenomes) and activity (metatranscriptomes) of the microbial communities in Fennoscandian Shield deep subsurface groundwaters were characterized with a focus on novel taxa. DNA sequencing generated 1270 de-replicated metagenome-assembled genomes and single-amplified genomes, containing 7 novel classes, 34 orders, and 72 families. The majority of novel taxa were affiliated with Patescibacteria, whereas among novel archaea taxa, Thermoproteota and Nanoarchaeota representatives dominated. Metatranscriptomes revealed that 30 of the 112 novel taxa at the class, order, and family levels were active in at least one investigated groundwater sample, implying that novel taxa represent a partially active but hitherto uncharacterized deep biosphere component. The novel taxa genomes coded for carbon fixation predominantly via the Wood–Ljungdahl pathway, nitrogen fixation, sulfur plus hydrogen oxidation, and fermentative pathways, including acetogenesis. These metabolic processes contributed significantly to the total community’s capacity, with up to 9.9% of fermentation, 6.4% of the Wood–Ljungdahl pathway, 6.8% of sulfur plus 8.6% of hydrogen oxidation, and energy conservation via nitrate (4.4%) and sulfate (6.0%) reduction. Key novel taxa included the UBA9089 phylum, with representatives having a prominent role in carbon fixation, nitrate and sulfate reduction, and organic and inorganic electron donor oxidation. These data provided insights into deep biosphere microbial diversity and their contribution to nutrient and energy cycling in this ecosystem.

Candidatus↗
DOE OSTI2020

Evaluating three evapotranspiration estimates from model of different complexity over China using the ILAMB benchmarking system

The land surface models range in complexity of terrestrial evapotranspiration, yet it is unknown how model complexity translates to accuracy of modeled evapotranspiration estimates. Here, we use the International Land Model Benchmarking system to assess ET estimates from three models of varying complexity driven by the same forcing datasets: an earth system model, a terrestrial biosphere model, and a stand-alone ET model. The performance assessment includes both temporal and spatial evaluation, and different plant functional types across China. Our results indicate that the most complex model, an earth system model, performed best against the benchmarking datasets and metrics. Terrestrial biosphere model performed best in simulating inter-annual variability of ET, while earth system model performed best in simulating the seasonal cycle. The more complex models (earth system model and terrestrial biosphere model) perform better in forest, shrub and crop ecosystems, while the simpler model (stand-alone ET model) perform better in grass ecosystems. Our study demonstrates the impact of model complexity on ET estimates and highlights directions for future ET model improvements.

54 ENVIRONMENTAL SCIENCES↗