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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effects of Cinnamomum camphora coppice planting on soil fertility, microbial community structure and enzyme activity in subtropical China

Cinnamomum camphora ( C. camphora ) is a broad-leaved evergreen tree cultivated in subtropical China. Currently, the use of C. camphora clonal cuttings for coppice management has become popular. However, the effects of C. camphora coppice planting on soil abiotic and biotic variances remained unclear. In this study, we collected soil from three points in the seven-year C. camphora coppice planting land: under the tree canopy (P15), between trees (P50), and abandoned land (Control) to investigate the effects of C. camphora coppice planting on soil fertility, microbial community structure and enzyme activity. The results revealed that C. camphora coppice planting significantly increased soil fertility in the point under the tree canopy (P15) and point between trees (P50), and P15 had more significant effects than P50. Meanwhile, in P15 and P50, soil bacterial, fungal alpha-diversity were improved and microbial community structures were also changed. And the changes of soil organic carbon and total nitrogen promote the transformation of soil bacterial, fungal community structures, respectively. In addition, C. camphora coppice planting significantly ( p < 0.05) increased soil urease (UE), polyphenol oxidase, and peroxidase activities, while significantly decreased soil ACP activity. This study demonstrated that the C. camphora coppice planting could improve soil fertility in subtropical China, which promoted the transformation of soil microbial community from oligotrophs ( K -strategist) to copiotrophs ( r -strategist). Thus, this work can provide a theoretical basis for soil nutrient variation and productive management of C. camphora coppice plantation in subtropical China.

Sun, Luyuan↗
DOE OSTI2022

3D structure and in situ arrangements of CatSper channel in the sperm flagellum

The sperm calcium channel CatSper plays a central role in successful fertilization as a primary Ca 2+ gateway. Here, we applied cryo-electron tomography to visualize the higher-order organization of the native CatSper complex in intact mammalian sperm. The repeating CatSper units form long zigzag-rows along mouse and human sperm flagella. Above each tetrameric channel pore, most of the extracellular domains form a canopy that interconnects to a zigzag-shaped roof. Murine CatSper contains an additional wing-structure connected to the tetrameric channel. The intracellular domains link two neighboring channels to a diagonal array, suggesting a dimer formation. Fitting of an atomic model of isolated monomeric CatSper to the in situ map reveals supramolecular interactions and assembly of the CatSper complex. Loss of EFCAB9-CATSPERζ alters the architecture and interactions of the channels, resulting in fragmentation and misalignment of the zigzag-rows and disruption of flagellar movement in Efcab9 -/- sperm. This work offers unique insights into the structural basis for understanding CatSper regulation of sperm motility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes

About 40% of the Brazilian Amazon has been deforested or suffered changes in forest structure through degradation (selective logging, fires, and fragmentation). The impact of forest degradation on the forest’s sensitivity to climate extremes has not been fully explored because of a lack of data and the complex interplay of forest structure and climate drivers. Here, we combined forest structure data from 545 airborne lidar transects (375 ha each) across the Brazilian Amazon with the Ecosystem Demography Model (ED2). We explore the forest’s functional response to near-present (1981–2019) climate extremes under observed forest structure from lidar ( Control ) and two forest structure change scenarios: (1) forest recovery by excluding all future deforestation and degradation ( Recovery ) and (2) expansion of selective logging and deforestation ( Degradation ). Using the Control simulation, we found a close and positive association between local forest aboveground biomass and the predicted gross primary productivity (GPP) and evapotranspiration (ET). Moreover, both GPP and ET respond negatively to extremes in vapor pressure deficit and downwelling shortwave irradiance in degraded forests in Eastern and Southern Amazon, indicating high sensitivity to droughts. Locally high-biomass forest patches showed little or no negative response of GPP and ET to extreme drought conditions whereas low-biomass forest patches in the same locations—typically degraded forest canopies—responded negatively to higher moisture stress. The results from the Recovery scenario showed similar results to simulations with observed structure; however, under the Degradation scenario, low-biomass forest patches became more abundant, resulting in more regions where GPP and ET are negatively impacted by hot drought conditions according to the ED2 model. Our results suggest that local forest structure is a critical determinant of an ecosystem’s response to climate variability, and that the loss of canopy trees in the Amazon through forest degradation could increase and expand forest vulnerability to droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Leaf structural and chemical traits, and BNL field campaign sample details, San Lorenzo, Panama, 2020

This data package includes leaf traits, canopy traits and sample details for leaves from 71 species sampled from the San Lorenzo forest canopy crane site, Panama (PA-SLZ) during the BNL field campaign in January to March 2020. Each leaf sample is described with species, phenological stage and location within vertical canopy profiles. Leaf area index (LAI) and height is presented for each canopy profile location. Leaf mass per area (LMA), leaf water content (LWC) and leaf carbon and nitrogen content are included for a subset of the samples. This data package includes sample details, processed data for leaf traits and LAI (*.csv), LAI raw data (compressed as *.zip) and digital camera images (*.jpg, compressed as *.zip) of the leaf samples. Metadata files include data descriptions (_dd.csv) for tabular data, a list of all species sampled during the campaign (*.csv) and a detailed description of the field campaign protocol and methods (*.pdf). See related datasets for leaf gas exchange, leaf water potential and leaf spectral measurements made on the samples described here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Ecosystem-Level Energy and Water Budgets Are Resilient to Canopy Mortality in Sparse Semiarid Biomes

Climate-driven woody vegetation mortality is a defining feature of semiarid biomes that drives fundamental changes in ecosystem structure. However, the observed impacts of woody mortality on ecosystem-scale energy and water budgets and the responses of surviving vegetation are highly variable among studies in water-limited environments. A previous girdling manipulation experiment in a piñon-juniper woodland suggested that although ecosystem-scale evapotranspiration was not altered by large-scale piñon mortality, soil water content decreased and the surviving juniper experienced greater water stress than juniper in an undisturbed woodland. Here we experimentally explored to what extent mortality-induced changes in energy balance components can explain these results. We compared energy fluxes measured above two adjacent piñon-juniper woodlands where piñon girdling was implemented at one site and the other subsequently experienced large-scale natural piñon mortality. We found that the mortality-induced decrease in canopy area was not sufficient to alter surface reflectance, roughness, and partitioning between energy budget components at both sites. A radiative transfer model estimated that because of the sparse premortality canopy, surface reflectance is more sensitive to a large increase in understory leaf area than further loss of crown area. Increased water stress in the remaining juniper following both mortality events can be explained by an increase in radiation on the ground that promoted higher soil temperature and evaporation. We found similar responses of ecosystem and tree-level functions to both girdling and natural mortality. This suggests that girdling is an appropriate approach to explore the impact of tree mortality on ecosystem structure, function, and energy balance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery

Canopy height models (CHMs) with sufficient resolution to distinguish individual trees are useful for a variety of applications. However, standard techniques to acquire such data, such as airborne lidar surveying, are often prohibitively expensive. Deep learning techniques for generating CHMs from high-resolution imagery are an attractive option to reduce costs. To date, success with these methods has been demonstrated using multichannel aerial photography and specialized satellite data products derived from multiple sensors, neither of which is commonly available at temporal resolutions finer than one year. Here we demonstrate a method to generate sub-meter resolution CHMs in three forests in California using a more abundant data source: sub-meter resolution, panchromatic satellite imagery from a single sensor. We show that phenology and species composition play important roles in model transferability; when trained using imagery from a single conifer forest in autumn, the model performs well on autumn imagery from a second conifer forest several hundred kilometers distant with no re-training. With modest additions to the training dataset, the same model generates minimally biased estimates of canopy height in both conifer and deciduous forests during multiple seasons. Because the model operates on satellite data with global coverage and a relatively short return interval, we propose its suitability to extrapolate tree-level canopy height data to remote regions and conduct high-temporal resolution monitoring of forest structure. We furthermore demonstrate the workflow’s applicability to fire modeling by conducting simulations in forests populated by trees measured using both this approach and airborne lidar surveying. We find minimal differences in fire behavior relative to a baseline case in which only statistical distributions of tree height and crown area are known. This result underscores the value of forest structural information derived from our workflow for improving the fidelity of wildland fire simulations, among other ecological applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Accelerated Self-Healing and Property Recovery in Brush Particle Solids Featuring Brush Dispersity

Brush particles, hybrid materials consisting of polymer chains tethered to particle surfaces, offer tunable properties that make them promising candidates for advanced functional materials. This study investigated the role of chain dispersity in the viscoelastic self-healing of poly (methyl acrylate) (PMA)-based brush particle solids. Increasing the molecular weight dispersity of grafted chains significantly enhanced both strain-to-fracture and toughness of brush particle solids, while the elastic modulus and glass transition temperature were independent of chain dispersity. Cut-and-adhere testing revealed a significant acceleration of the rate of toughness recovery in high-dispersity systems as compared to low-dispersity analogs for which toughness recovery markedly lagged the recovery of Young’s modulus. The results suggest that structure and property recovery in brush particle solids are sensitive to the dynamical heterogeneity of brush canopies and highlight the role of molecular weight dispersity as a design parameter to enable hybrid materials with advanced self-healing ability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Estimating Leaf Area Index in Row Crops Using Wheel-Based and Airborne Discrete Return Light Detection and Ranging Data

Leaf area index (LAI) is an important variable for characterizing plant canopy in crop models. It is traditionally defined as the total one-sided leaf area per unit ground area and is estimated by both direct and indirect methods. This paper explores the effectiveness of using light detection and ranging (LiDAR) data to estimate LAI for sorghum and maize with different treatments at multiple times during the growing season from both a wheeled vehicle and Unmanned Aerial Vehicles. Linear and nonlinear regression models are investigated for prediction utilizing statistical and plant structure-based features extracted from the LiDAR point cloud data with ground reference obtained from an in-field plant canopy analyzer (indirect method). Results based on the value of the coefficient of determination ( R 2 ) and root mean squared error for predictive models ranged from ∼0.4 in the early season to ∼0.6 for sorghum and ∼0.5 to 0.80 for maize from 40 Days after Sowing to harvest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Localized and Collective Dynamics in Liquid-like Polyethylenimine-Based Nanoparticle Organic Hybrid Materials

In this work, broadband dielectric spectroscopy, rheology, and nuclear magnetic resonance spectroscopy are employed to study molecular dynamics in a nanoparticle organic hybrid materials(NOHMs)system comprising 20 wt% silica nanoparticles ionically-bonded to a polyethylenimine canopy. By comparing the neat polymer (used as a canopy) to the derivative NOHMs, we find that timescales characterizing segmental dynamics in the NOHM are identical to those for the neat polymer. Detailed analysis of the carbon-spin lattice relaxation times yields mechanistic insights into localized and collective dynamics, in quantitative agreement with dielectric results. Interestingly, the NOHMs retain liquid-like characteristics unlike conventional polymer nanocomposites but exhibit higher viscosity due to additional contributions from tethered polymer chains, and mesoscopic structuring. These findings demonstrate the potential of achieving unique and desired material properties via NOHMs by an informed choice of the canopy material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Dynamic Mixing Behaviors of Ionically Tethered Polymer Canopy of Nanoscale Hybrid Materials in Fluids of Varying Physical and Chemical Properties

An emerging area of sustainable energy and environmental research is focused on the development of novel electrolytes that can increase the solubility of target species and improve subsequent reaction performance. Electrolytes with chemical and structural tunability have allowed for significant advancements in flow batteries and CO 2 conversion integrated with CO 2 capture. Liquid-like nanoparticle organic hybrid materials (NOHMs) are nanoscale fluids that are composed of inorganic nanocores and an ionically tethered polymeric canopy. NOHMs have been shown to exhibit enhanced conductivity making them promising for electrolyte applications, though they are often challenged by high viscosity in the neat state. In this study, a series of binary mixtures of NOHM-I-HPE with five different secondary fluids, water, chloroform, toluene, acetonitrile, and ethyl acetate, were prepared to reduce the fluid viscosity and investigate the effects of secondary fluid properties (e.g., hydrogen bonding ability, polarity, and molar volume) on their transport behaviors, including viscosity and diffusivity. We report our results revealed that the molecular ratio of secondary fluid to the ether groups of Jeffamine M2070 ($λ_{\text{SF}}$) was able to describe the effect that secondary fluid has on transport properties. Our findings also suggest that in solution, the Jeffamine M2070 molecules exist in different nanoscale environments, where some are more strongly associated with the nanoparticle surface than others, and the conformation of the polymer canopy was dependent on the secondary fluid. This understanding of the polymer conformation in NOHMs can allow for the better design of an electrolyte capable of capturing and releasing small gaseous or ionic species.

25 ENERGY STORAGE↗
DOE OSTI2025

Cryo-EM structures of the small-conductance Ca 2+ -activated K Ca 2.2 channel

Small-conductance Ca 2+ -activated K + (K Ca 2.1-K Ca 2.3) channels modulate neuronal and cardiac excitability. We report cryo-electron microscopy structures of the K Ca 2.2 channel in complex with calmodulin and Ca 2+ , alone or bound to two small molecule inhibitors, at 3.18, 3.50, 2.99 and 2.97 angstrom resolution, respectively. Extracellular S3-S4 loops in β-hairpin configuration form an outer canopy over the pore with an aromatic box at the canopy’s center. Each S3-S4 β-hairpin is tethered to the selectivity filter in the neighboring subunit by inter-subunit hydrogen bonds. This hydrogen bond network flips the aromatic residue (Tyr362) in the filter’s GYG signature by 180°, causing the outer selectivity filter to widen and water to enter the filter. Disruption of the tether by a mutation narrows the outer selectivity filter, realigns Tyr362 to the position seen in other K + channels, and significantly increases unitary conductance. UCL1684, a mimetic of the bee venom peptide apamin, sits atop the canopy and occludes the opening in the aromatic box. AP14145, an analogue of a therapeutic for atrial fibrillation, binds in the central cavity below the selectivity filter and induces closure of the inner gate. These structures provide a basis for understanding the small unitary conductance and pharmacology of K Ca 2.x channels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Characterizing Turbulence at a Forest Edge: Comparing Sub-Filter Scale Turbulence Models in Simulations of Flow over a Canopy

In wildfires, atmospheric turbulence plays a major role in the transfer of turbulent kinetic energy. Understanding how turbulence feeds back into a dynamical system is important, down to the varying small scales of fuel structures (i.e. pine needles, grass). Large eddy simulations (LES) are a common way of numerically representing turbulence. The Smagorinsky model (1963) serves as one of the most studied sub-grid scale representations in LES. In this investigation, the Smagorinsky model was implemented in HIGRAD/FIRETEC, LANL’s coupled fire-atmosphere model. This study was motivated by the need to quantitatively investigate the vorticity budget equation in HIGRAD/FIRETEC. The Smagorinsky turbulent kinetic energy (TKE) was compared to FIRETEC’s 1.5-order TKE eddy-viscosity subgrid-scale model, known as the Linn turbulence model. This was done in simulations of flow over flat terrain with a homogeneous, cuboidal canopy in the center of the domain. Examinations of the modeled vertical TKE profile and turbulent statistics at the leading edge, and throughout the canopy, show that the Smagorinsky model provides comparable results to that of the original closure model posed in FIRETEC.

58 GEOSCIENCES↗
DOE OSTI2021

Resistance, Resilience, and Recovery of Dryland Soil Bacterial Communities Across Multiple Disturbances

Dryland ecosystems are sensitive to perturbations and generally slow to recover post disturbance. The microorganisms residing in dryland soils are especially important as they contribute to soil structure and nutrient cycling. Disturbance can have particularly strong effects on dryland soil structure and function, yet the natural resistance and recovery of the microbial components of dryland soils has not been well documented. In this study, the recovery of surface soil bacterial communities from multiple physical and environmental disturbances is assessed. Samples were collected from three field sites in the vicinity of Moab, UT, United States, 6 to 7 years after physical and climate disturbance manipulations had been terminated, allowing for the assessment of community recovery. Additionally, samples were collected in a transect that included three habitat patches: the canopy zone soils under the dominant shrubs, the interspace soils that are colonized by biological soil crusts, and edge soils at the plot borders. Field site and habitat patch were significant factors structuring the bacterial communities, illustrating that sites and habitats harbored unique soil microbiomes. Across the different sites and disturbance treatments, there was evidence of significant bacterial community recovery, as bacterial biomass and diversity were not significantly different than control plots. There was, however, a small number of 16S rRNA gene amplicon sequence variants that distinguished particular treatments, suggesting that legacy effects of the disturbances still remained. Taken together, these data suggest that dryland bacterial communities may possess a previously unappreciated potential to recover within years of the original disturbance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Temporal covariance structure of multi-spectral phenotypes and their predictive ability for end-of-season traits in maize

Vegetation indices (VIs) derived from multi-spectral imaging (MSI) platforms can be used to study properties of crop canopy, providing non-destructive phenotypes that could be used to better understand growth curves throughout the growing season. To investigate the amount of variation present in several VIs and their relationship with important end-of-season traits, genetic and residual (co)variances for VIs, grain yield and moisture were estimated using data collected from maize hybrid trials. The VIs considered were Normalized Difference Vegetation Index (NDVI), Green NDVI, Red Edge NDVI, Soil-Adjusted Vegetation Index, Enhanced Vegetation Index and simple Ratio of Near Infrared to Red (Red) reflectance. Genetic correlations of VIs with grain yield and moisture were used to fit multi-trait models for prediction of end-of-season traits and evaluated using within site/year cross-validation. To explore alternatives to fitting multiple phenotypes from MSI, random regression models with linear splines were fit using data collected in 2016 and 2017. Heritability estimates ranging from (0.10 to 0.82) were observed, indicating that there exists considerable amount of genetic variation in these VIs. Furthermore, strong genetic and residual correlations of the VIs, NDVI and NDRE, with grain yield and moisture were found. Considerable increases in prediction accuracy were observed from the multi-trait model when using NDVI and NDRE as a secondary trait. Finally, random regression with a linear spline function shows potential to be used as an alternative to mixed models to fit VIs from multiple time points.

59 BASIC BIOLOGICAL SCIENCES↗
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

Discerning the thermodynamic feasibility of the spontaneous coexistence of multiple functional vegetation groups

Can the Second Law of Thermodynamics explain why ecosystems naturally organize into a complex structure composed of multiple vegetation species and functional groups? Ecosystem structure, which refers to the number and type of plant functional groups, is the result of self-organization, or the spontaneous emergence of order from random fluctuations. By considering ecosystems as open thermodynamic systems, we model and study these fluctuations of throughput signatures on short timescales to determine the drivers and characteristics of ecosystem structure. This diagnostic approach allows us to use fluxes of energy and entropy to calculate an ecosystem’s estimated work and understand the thermodynamic behavior of the system. We use a multi-layer canopy-root-soil model to calculate the energy and entropy fluxes of different scenarios for field sites across various climates. At each site, scenarios comprised of native individual plant functional groups and a coexisting multi-group composition scenario including all functional groups observed at the site are compared. Ecosystem-scale calculations demonstrate that entropy fluxes and work efficiency—the work performed for the amount of radiation entering the ecosystem—are greatest in the multi-group scenario when its leaf area is significantly larger than each of its individual functional groups. Thus, we conclude that ecosystems self-organize towards the vegetation structure with the greatest outgoing entropy flux and work efficiency, resulting in the coexistence of multiple functional groups and performing the maximum amount of work within the constraints of locally available energy, water, and nutrients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Seasonal trends in leaf-level photosynthetic capacity and water use efficiency in a North American Eastern deciduous forest and their impact on canopy-scale gas exchange

Vegetative transpiration (E) and photosynthetic carbon assimilation (A) are known to be seasonally dynamic, with changes in their ratio determining the marginal water use efficiency (WUE). Despite an understanding that stomata play a mechanistic role in regulating WUE, it is still unclear how stomatal and nonstomatal processes influence change in WUE over the course of the growing season. As a result, limited understanding of the primary physiological drivers of seasonal dynamics of canopy WUE remains one of the largest uncertainties in earth system model projections of carbon and water exchange in temperate deciduous forest ecosystems. Here, we investigated seasonal patterns in leaf-level physiological, hydraulic, and anatomical properties, including the seasonal progress of the stomatal slope parameter (g 1 ; inversely proportional to WUE) and the maximum carboxylation rate (V cmax ). V cmax and g 1 were seasonally variable; however, their patterns were not temporally synchronized. g 1 generally showed an increasing trend until late in the season, while V cmax peaked during the midsummer months. Seasonal progression of V cmax was primarily driven by changes in leaf structural, and anatomical characteristics, while seasonal changes in g 1 were most strongly related to changes in V cmax and leaf hydraulics. Using a seasonally variable V cmax and g 1 to parameterize a canopy-scale gas exchange model increased seasonally aggregated A and E by 3% and 16%, respectively.

54 ENVIRONMENTAL SCIENCES↗