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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 73 records · Page 4

Outage Cause Classification of Power Distribution Systems with Machine Learning and Real-World Data

Power distribution systems are geographically dispersed by nature. It may be affected by various factors, such as vegetation, weather, animal and human behaviors. Present response procedures to an outage event massively rely on expert experience and thus tend to be time-consuming. Automatic outage event detection and classification will help to reduce the responding and restoration time. However, this issue is less addressed with existing research done in this area. In this applied research, a set of waveform pre-processing techniques are first proposed to prepare the waveform data for being used as inputs to the classification algorithm. Further, a machine learning-based algorithm is proposed to classify the outage events according to their root causes, e.g. tree contact, animal contact, lightning, etc. Available data include three phase current & voltage waveforms and contextual information during the distribution system outages. The proposed machine learning algorithm takes the current and voltage waveforms as direct inputs in search of features that humans are unable to capture. Real data provided by a distribution company in the East Tennessee region is used to test the proposed pre-processing techniques and the classification algorithm.

Sun, Haoyuan↗

Ecological and genomic variation in ectomycorrhizal fungal exploration types

Ectomycorrhizal fungi (EMF) produce mycelia with variable extension and complexity, which can be classified according to soil ‘exploration types’ (ETs). ETs have received attention as one of the few mycorrhizal trait frameworks, but without an empirical classification of ET functional diversity and environmental preferences, understanding and interpreting EMF biogeographic patterns has been difficult. We conducted a synthesis combining: comparative EMF genomics to describe functional divergence in decomposition and nutrient cycling genes across ETs; and EMF trait distribution modeling across continental Europe, pairing soil and root EMF surveys to establish biogeographic ET niche profiles. We demonstrate a signature of ETs encoded in EMF genomes, which is independent from phylogeny and linked to biomass production strategies. EMF ET relative abundances were separated by soil, root, and dominant tree leaf type habitats and exhibited unique correlations with forest biotic (e.g. plant productivity and plant pathogen densities) and abiotic (e.g. nitrogen deposition and soil pH) conditions. These findings support a theory that EMF niche partitioning can be partially explained by extraradical mycelial traits, with underlying variation in ET biogeography likely arising from distinct decomposition and nutrient cycling potentials. We also identify important limitations to this trait framework and provide a guided outlook for future research.

biogeography↗

Five PMI Isolates from Populus Deltoides and Populus Trichocarpa

Five bacterial isolates were isolated from the roots of poplar trees (Populus deltoides and P. trichocarpa), which are model organisms and a main focus of the Plant-Microbe Interfaces (PMI) project at ORNL. These strains belong to genera are not well represented and give a more complete view of the microbial community and bacterial interactions with poplar trees. These strains will support future studies and contribute to the broader PMI goal of understanding microbe-microbe and plant-microbe interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Soil Water Potentials (1990-2018) from a calibrated ELM-FATES, and rooting depth analyses scripts, PA-BCI, Panama

This dataset has ELM-FATES simulation outputs and scripts that accompany and reproduce the manuscript, Chitra-Tarak et al. (2021) Hydraulically-vulnerable trees survive on deep-water access during droughts in a tropical forest. New Phytologist. https: //doi.org/10.1111/nph.17464”. This dataset is organized into four parts: (1) source code for the model, Energy Exascale Earth System Land Model-Functionally Assembled Advanced Terrestrial simulator (ELM-FATES) (2) R scripts associated with ELM-FATES simulations: to prepare files for parameter ensemble simulation runs, calibrate the model with observed hydrological fluxes observed at BCI, re-run the model with tuned parameters and obtain long-term soil matric potentials by depth (3) ELM-FATES hydrological simulation outputs at PA-BCI, Panama (1990-2018, daily), and (4) R scripts for inverse rooting depth modeling and post-processing: prepare datasets and inversely model tree rooting depths at BCI, test hypotheses about the relationship of rooting depths with plant hydraulic traits and drought-induced mortality, and reproduce the manuscript itself. n.b. 1. Data needed to run R scripts in (2) and (4) and thus to reproduce the manuscript are sourced from various public datasets. Refer to the data availability section of the accompanying manuscript. 2. This dataset version (prepared on May 12, 2021) matches the revised and published version of the accompanying manuscript (published May 16, 2021) replacing a previous version. In the publication, this dataset is cited as follows: Chitra-Tarak R, Xu C, Aguilar S, Anderson-Teixeira K, Chambers J, Detto M, Faybishenko B, Fisher R, Knox R, Koven C et al. 2020. Soil water potentials (1990–2018) from a calibrated ELM-FATES, and rooting depth analyses scripts, PA-BCI, Panama. 2.0. NGEE Tropics Data Collection. doi: 10.15486/ngt/1696806

54 ENVIRONMENTAL SCIENCES↗

Test of model of equivalence of tree height growth and transpiration rates in percolation-based phenomenology for root-soil interaction

We recently introduced a phenomenological model to represent root-soil interactions that accounts for variability in tree growth on local scales and within species (Hunt et al., 2020). Here, using publicly available datasets, we examine the developed model to provide additional empirical evidence, which also gives novel insight into two particular tree species, Eucalyptus regnans and Eucalyptus sieberri. In particular, we discovered two novel aspects of the model: a power-law time dependence with a different power-law exponent than usually heretofore applied, and apparently a direct equivalence of results for transpiration and growth rates. Also, although our original expectation was that growth and transpiration were merely proportional, comparison of the entire BAAD data set (Falster et al., 2015) for tree height with our model (Hunt et al., 2020; Fig. 1) already suggested approximate equality of these disparate measurements (volume/area, height). In this present manuscript we find further evidence for equivalence of the two measurements and provide additional theoretical basis for a model assumption regarding constancy of sap flow rates.

54 ENVIRONMENTAL SCIENCES↗

Using Boosted Decision Trees to Select High Quality Measurements in the Mu2e Experiment at Fermilab

This thesis presents the implementation and evaluation of a Boosted Decision Tree (BDT) model to improve the selection of high-quality track measurements in the Mu2e experiment at Fermilab. The Mu2e experiment is a high-energy physics experiments seeking to observe a rare theoretical physics process known as Charged Lepton Flavor Violation. A significant challenge faced by the Mu2e experiment are so-called background events, which are events whose data mimics that of the rare physics process the experiment seeks to observe. Without a mechanism to reduce background, it would be impossible to know whether Charged Lepton Flavor Violation occurred or not. To this end, high-quality track measurements must be distinguished from low-quality track measurements. A track can be conceived of as the reconstructed path of a particle that traveled through the Mu2e detector. In addition to other data, data about such tracks is stored using a C++-based framework, specific to the domain of high-energy physics, known as ROOT. A boosted decision tree model was trained using ROOT’s Toolkit For Multivariate Analysis by leveraging variables ancillary to track quality. In evaluation, the BDT achieves a ROC-AUC of 0.927 in discriminating good-quality tracks from poor-quality tracks. Such a score is indicative of both strong discrimination and strong generalization. Subsequently, it is shown that applying a BDT-based quality cut to the distribution of particle momenta significantly enhances the signal-to-background distinction for signal electrons, paving the way for improved sensitivity to Charged Lepton Flavor Violation.

Mullany, Brendan T. [Drew U.] (ORCID:0009000818888↗

Acquisitive root exploration strategies help maintain higher peak sap flux rates during summer drought, but more root biomass does not

Roots are responsible for soil water uptake, yet little is known about how variation in fine-root traits relates to whole-tree water movement, particularly during periods of drought. By combining a 3-yr dataset monitoring sap flow rates with measures of fine-root biomass, length, and morphology across 10 tree species, we addressed hypotheses concerning the role of fine-root system size and morphology in determining tree responses to summer drought as well as potential changes in their relative importance under more severe droughts. Greater fine-root biomass and length did not enable trees to maintain high rates of sap flow during drought, whereas the morphological traits, specific root length and specific root area, were linked to sustained sap flow rates during drought. We found that all species, irrespective of root traits, progressively reduced their sap flow under more extreme drought conditions, although more acquisitive root morphology was still associated with smaller reductions. Our results run counter to long-standing assumptions that larger root systems are better able to access soil water and maintain photosynthetic activity during drought. Instead, we find evidence that root morphology at least partially determines the capacity for water uptake and movement as soil moisture declines.

drought↗

Performing optimized collective operations in a irregular subcommunicator of compute nodes in a parallel computer

In a parallel computer, performing optimized collective operations in an irregular subcommunicator of compute nodes may be carried out by: identifying, within the irregular subcommunicator, regular neighborhoods of compute nodes; selecting, for each neighborhood from the compute nodes of the neighborhood, a local root node; assigning each local root node to a node of a neighborhood-wide tree topology; mapping, for each neighborhood, the compute nodes of the neighborhood to a local tree topology having, at its root, the local root node of the neighborhood; and performing a one way, rooted collective operation within the subcommunicator including: performing, in one phase, the collective operation within each neighborhood; and performing, in another phase, the collective operation amongst the local root nodes.

Davis, Kristan Suzanne D.↗

Ectomycorrhizal and Dark Septate Fungal Associations of Pinyon Pine Are Differentially Affected by Experimental Drought and Warming

Changing climates can cause shifts in temperature and precipitation, resulting in warming and drought in some regions. Although each of these factors has been shown to detrimentally affect forest ecosystems worldwide, information on the impacts of the combined effects of warming and drought is lacking. Forest trees rely on mutualistic root-associated fungi that contribute significantly to plant health and protection against climate stresses. We used a six-year, ecosystem-scale temperature and precipitation manipulation experiment targeted to simulate the climate in 2100 in the Southwestern United States to quantify the effects of drought, warming and combined drought and warming on the root colonization (abundance), species composition and diversity of ectomycorrhizal fungi (EMF), and dark septate fungal endophytes in a widespread woodland tree, pinyon pine (Pinus edulis E.). Our results show that pinyon shoot growth after 6 years of these treatments was reduced more by drought than warming. The combined drought and warming treatment reduced the abundance and diversity of EMF more than either treatment alone. Individual ectomycorrhizal fungal taxa, including the drought tolerant Cenococcum geophilum, were present in all treatments but the combined drought and warming treatment. The combined drought and warming treatment also reduced the abundance of dark septate endophytes (DSE), but did not affect their diversity or species composition. The current year shoot growth of the trees correlated positively with ectomycorrhizal fungal diversity, highlighting the importance of diversity in mutualistic relationships to plant growth. Our results suggest that EMF may be more important than DSE to aboveground growth in P. edulis, but also more susceptible to the negative effects of combined climate stressors.

59 BASIC BIOLOGICAL SCIENCES↗

Root identification in minirhizotron imagery with multiple instance learning

In this study, multiple instance learning (MIL) algorithms to automatically perform root detection and segmentation in minirhizotron imagery using only image-level labels are proposed. Root and soil characteristics vary from location to location, and thus, supervised machine learning approaches that are trained with local data provide the best ability to identify and segment roots in minirhizotron imagery. However, labeling roots for training data (or otherwise) is an extremely tedious and time-consuming task. This paper aims to address this problem by labeling data at the image level (rather than the individual root or root pixel level) and train algorithms to perform individual root pixel level segmentation using MIL strategies. Three MIL methods (multiple instance adaptive cosine coherence estimator, multiple instance support vector machine, multiple instance learning with randomized trees) were applied to root detection and compared to non-MIL approaches. The results show that MIL methods improve root segmentation in challenging minirhizotron imagery and reduce the labeling burden. In our results, multiple instance support vector machine outperformed other methods. The multiple instance adaptive cosine coherence estimator algorithm was a close second with an added advantage that it learned an interpretable root signature which identified the traits used to distinguish roots from soil and did not require parameter selection.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling the mechanisms of conifer mortality under seawater exposure

Summary Relative sea level rise (SLR) increasingly impacts coastal ecosystems through the formation of ghost forests. To predict the future of coastal ecosystems under SLR and changing climate, it is important to understand the physiological mechanisms underlying coastal tree mortality and to integrate this knowledge into dynamic vegetation models. We incorporate the physiological effect of salinity and hypoxia in a dynamic vegetation model in the Earth system land model, and used the model to investigate the mechanisms of mortality of conifer forests on the west and east coast sites of USA, where trees experience different form of sea water exposure. Simulations suggest similar physiological mechanisms can result in different mortality patterns. At the east coast site that experienced severe increases in seawater exposure, trees loose photosynthetic capacity and roots rapidly, and both storage carbon and hydraulic conductance decrease significantly within a year. Over time, further consumption of storage carbon that leads to carbon starvation dominates mortality. At the west coast site that gradually exposed to seawater through SLR, hydraulic failure dominates mortality because root loss impacts on conductance are greater than the degree of storage carbon depletion. Measurements and modeling focused on understanding the physiological mechanisms of mortality is critical to reducing predictive uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗

Mechanisms of regulation of the rhizosphere, roots and shoots of naive poplars

Trees are associated with a broad range of microorganisms colonising the diverse tissues of their host. However, the early dynamics of the microbiota assembly microbiota from the root to shoot axis and how it is linked to root exudates and metabolite contents of tissues remain unclear. Here, we characterised how fungal and bacterial communities are altering root exudates as well as root and shoot metabolomes in parallel with their establishment in poplar cuttings (Populus tremula x tremuloides clone T89) over 30 days of growth. Sterile poplar cuttings were planted in natural or gamma irradiated soils. Bulk and rhizospheric soils, root and shoot tissues were collected from day 1 to day 30 to track the dynamic changes of fungal and bacterial communities in the different habitats by DNA metabarcoding. Root exudates and root and shoot metabolites were analysed in parallel by gas chromatography-mass spectrometry.

09 BIOMASS FUELS↗

Hydraulic redistribution supplies a major water subsidy and improves water status of understory species in a longleaf pine ecosystem

Hydraulic redistribution (HR) is a common phenomenon in water-limited ecosystems; however, it remains unclear how the volume of water transported via HR compares to other components of the hydrologic budget and how HR influences water availability for understory plant communities. In this study, we investigate the absolute and relative magnitude of HR on a forest water budget and identify potential impacts of this water subsidy to understory plant communities. We scaled tree-level estimates of transpiration and HR of three common tree species naturally occurring in a longleaf pine woodland with plot-level measurements of basal area to determine their magnitude at the stand scale. We trenched plots containing understory vegetation but devoid of mature trees and their connected roots to exclude HR subsidies to understory plant species. We analysed soil water isotopes and assessed leaf water potential (Ψ L ) in trenched and control plots to determine if HR results in mixing of water among soil strata and improves understory plant moisture status. Water inputs from HR were equivalent to >30% of total rainfall for the site during the observation period and ~40% of total tree water uptake, depending on species. A stable isotope mixing model confirmed that soil water within HR-exposed plots was more similar to groundwater, whereas soil water within trenched plots was more similar to precipitation. Exclusion of HR via trenching decreased soil moisture and pre-dawn Ψ L for all understory species. These three lines of evidence suggest that HR from overstory trees redistributes a sizable portion of water from deeper to shallower soil profiles and that this water subsidy enhances understory plant water status.

54 ENVIRONMENTAL SCIENCES↗

A new phenomenological model to describe root-soil interactions based on percolation theory

In his paper on net primary productivity of terrestrial communities predicted from climatological data, Rosenzweig (1968) argued that variability in productivity is well accounted for by (evapo)-transpiration, and that water from transpiration is, on global scales, the most variable component in the photosynthesis reaction. The goal of this paper is to investigate whether variability in plant growth on local scales and within species is primarily related to transpiration under several scenarios including different terrain curvature, slope aspect, soil characteristics, and climate ranges. Here, we test the hypothesis that this relationship exists because root growth into the surface soil layers (0–2 m) tends to follow paths with minima in resistance, which in turn maximizes water flow and nutrient delivery rates that regulate growth. The set of all connected paths with individual pore-to-pore flow resistances less than a critical, percolating, value forms a cluster with mass fractal dimensionality, d f . We propose that roots follow paths through the 2D percolation cluster, defining the set of all optimal flow paths, making the 2D value of d f from percolation relevant to root fractal dimensionality. The tortuosity of such optimal paths as defined in percolation theory should then relate root length to root radial extent, linking the parameters of root tortuosity and plant productivity. Our analysis of large data sets across species implies that root radial extent and tree height are both proportional to cumulative transpiration until trees approached maximum height, and their growth rates are proportional to the transpiration rate, not to the moisture content. Local variations in tree height as functions of the variables investigated appear generally consistent with deduced variations in transpiration. Here this correlation is investigated more closely in the context of studies addressing individual tree species.

54 ENVIRONMENTAL SCIENCES↗

Microbiome Variation Across Two Hemlock Species With Hemlock Woolly Adelgid Infestation

The hemlock woolly adelgid ( Adelges tsugae , HWA), an invasive insect, is devastating native hemlock populations in eastern North America, and management outcomes have so far had limited success. While many plant microbiomes influence and even support plant immune responses to insect herbivory, relatively little is known about the hemlock microbiome and its interactions with pathogens or herbivores such as HWA. Using 16S rRNA and ITS gene amplicon sequencing, we characterized the needle, branch, root, and rhizosphere microbiome of two hemlock species, Tsuga canadensis and T. sieboldii , that displayed low and high levels of HWA populations. We found that both archaeal/bacterial and fungal needle communities, as well as the archaeal/bacterial branch and root communities, varied in composition in both hemlock species relative to HWA population levels. While host species and plant-associated habitats explained a greater proportion of the variance in the microbiome than did HWA population level, high HWA populations were associated with enrichment of 100 likely fungal pathogen sequence variants across the four plant-associated habitats (e.g., needle, branch, root, rhizosphere) compared to trees with lower HWA populations. This work contributes to a growing body of literature linking plant pathogens and pests with the changes in the associated plant microbiome and host health. Furthermore, this work demonstrates the need to further investigate plant microbiome effects across multiple plant tissues to understand their influences on host health.

16S rRNA↗

23_POPLAR_EXUDATES

This data is derived from sampling poplar trees at the GWAS common garden in Clatskanie, Oregon. This is intermediate level data from LCMS experiments that were done at ORNL from root tissue and soluble root exudates collected from 24 trees in the common garden in October of 2022.

CBI↗

Root-derived inputs are major contributors to soil carbon in temperate forests, but vary by mycorrhizal type

Roots promote the formation of slow-cycling soil carbon (C), yet we have a limited understanding of the magnitude and controls on this flux. We hypothesised arbuscular mycorrhizal (AM)- and ectomycorrhizal (ECM)-associated trees would exhibit differences in root-derived C accumulation in the soil, and that much of this C would be transferred into mineral-associated pools. We installed δ 13 C-enriched ingrowth cores across mycorrhizal gradients in six Eastern U.S. forests (n = 54 plots). Overall, root-derived C was 54% greater in AM versus ECM-dominated plots. This resulted in nearly twice as much root-derived C in putatively slow-cycling mineral-associated pools in AM compared to ECM plots. Finally, given that our estimates of root-derived inputs were often equal to or greater than leaf litter inputs, our results suggest that variation in root-derived soil C accumulation due to tree mycorrhizal dominance may be a key control of soil C dynamics in forests.

54 ENVIRONMENTAL SCIENCES↗

Persistence and Plasticity in Conifer Water–Use Strategies

The selective use of seasonal precipitation by vegetation is critical to understanding the residence time and flow path of water in watersheds, yet there are limited datasets to test how climate alters these dynamics. Here, we use measurements of the seasonal cycle of tree ring δ 18 O for two widespread conifer species in the Rocky Mountains of North America to provide a multi-decadal depiction of the seasonal origins of forest water use. The results show that while the conifer tree stands had a dominant preference for use of snowmelt, there were multi-annual periods over the last four decades when use of summer precipitation was preferential. Utilization of summer rain emerged during years with increased snowfall and tree growth, suggesting that summer rain enhanced the transpiration stream only during the periods of highest water use. We hypothesize this could be explained through shallowing of the root profile during wetter periods and/or through the influence of changing water table depths on the residence time of summer precipitation in the root zone. We suggest the tree ring proxy approach used here could be applied in other watersheds to provide critical insight into the temporal dynamics of plant water use that could not be inferred from short measurement campaigns. Furthermore, these data on the seasonal origins of forest water are critical for understanding forest vulnerability to drought, the processes that affect precipitation pathways and residence time in watersheds and the interpretation of tree ring proxy data.

59 BASIC BIOLOGICAL SCIENCES↗