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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Simulation and Postmortem Analysis of Angeles Forest Disturbance Event

Multiple unexpected solar photovoltaic (PV) plant responses in the California region following contingencies in recent years warrant postmortem analysis leveraging digital fault recorder (DFR) data for a better understanding of such events and preventing similar events in the future. Most utilities in US, in general, possess transient stability (TS) phasor-domain models of the power grid. Since traditional phasor-based transient stability planning models cannot perform such analysis, this paper presents an approach to extract a region of such models and convert it to Electromagnetic transient (EMT) models. The approach is based on the determination of the minimum impedance-weighted spanning tree between the fault location and affected PV plants in a Western Electricity Coordinating Council (WECC) planning model followed by conversion of this region into an EMT model. The accuracy of the proposed approach is validated against DFR records obtained from the 2018 Angeles Forest disturbance event.

Samanta, Sayan↗
DOE OSTI2023

On the Investigation of Phase Fault Classification in Power Grid Signals: A Case Study for Support Vector Machines, Decision Tree and Random Forest

In monitoring the power grid, an ability to differentiate between fault types is essential to ensuring electrical safety. Accordingly, this study introduces a fault detection and classification method by considering different machine learning (ML) and feature extraction (FE) methods combinations. Specifically, the proposed method is established in two classification layers; the first layer determines the fault, and the second layer distinguishes the type of fault. Based on the proposed system model, this study seeks to determine the influential data attributes in a power grid signal using FE methods, including fast Fourier transform, power spectral density (PSD), auto-correlation, and wavelet transform (WT). A cross-comparison of the effectiveness of the Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF) is also performed to accomplish the classification layers of the proposed method. The designed algorithm is analyzed under the various combinations of FE and ML methods, and outcomes are presented by considering the trade-off between computational complexity and prediction accuracy. The results reveal that the RF-based ML algorithm shows the most accurate classification performance with PSD, and the most time-saving of the models is the DT WT. Also, SVM emerges superior on a subsequent test of the simulated models on real-world signals.

Galbraith, Kelli↗
DOE OSTI2023

Prescribed fire selects for a pyrophilous soil sub‐community in a northern California mixed conifer forest

Abstract Prescribed fire is a critical strategy for mitigating the effects of catastrophic wildfires. While the above‐ground response to fire has been well‐documented, fewer studies have addressed the effect of prescribed fire on soil microorganisms. To understand how soil microbial communities respond to prescribed fire, we sampled four plots at a high temporal resolution (two burned, two controls), for 17 months, in a mixed conifer forest in northern California, USA. Using amplicon sequencing, we found that prescribed fire significantly altered both fungal and bacterial community structure. We found that most differentially abundant fungal taxa had a positive fold‐change, while differentially abundant bacterial taxa generally had a negative fold‐change. We tested the null hypothesis that these communities assembled due to neutral processes (i.e., drift and/or dispersal), finding that >90% of taxa fit this neutral prediction. However, a dynamic sub‐community composed of burn‐associated indicator taxa that were positively differentially abundant was enriched for non‐neutral amplicon sequence variants, suggesting assembly via deterministic processes. In synthesizing these results, we identified 15 pyrophilous taxa with a significant and positive response to prescribed burns. Together, these results lay the foundation for building a process‐driven understanding of microbial community assembly in the context of the classical disturbance regime of fire.

Microbiology↗
DOE OSTI2020

Biomass increases attributed to both faster tree growth and altered allometric relationships under long‐term carbon dioxide enrichment at a temperate forest

Abstract Increases in atmospheric carbon dioxide (CO 2 ) concentrations are expected to lead to increases in the rate of tree biomass accumulation, at least temporarily. On the one hand, trees may simply grow faster under higher CO 2 concentrations, preserving the allometric relations that prevailed under lower CO 2 concentrations. Alternatively, the allometric relations themselves may change. In this study, the effects of elevated CO 2 (eCO 2 ) on tree biomass and allometric relations were jointly assessed. Over 100 trees, grown at Duke Forest, NC, USA, were harvested from eight plots. Half of the plots had been subjected to CO 2 enrichment from 1996 to 2010. Several subplots had also been subjected to nitrogen fertilization from 2005 to 2010. Allometric equations were developed to predict tree height, stem volume, and aboveground biomass components for loblolly pine ( Pinus taeda L.), the dominant tree species, and broad‐leaved species. Using the same diameter‐based allometric equations for biomass, it was estimated that plots with eCO 2 contained 21% more aboveground biomass, consistent with previous studies. However, eCO 2 significantly affected allometry, and these changes had an additional effect on biomass. In particular, P. taeda trees at a given diameter were observed to be taller under eCO 2 than under ambient CO 2 due to changes in both the allometric scaling exponent and intercept. Accounting for allometric change increased the treatment effect of eCO 2 on aboveground biomass from a 21% to a 27% increase. No allometric changes for the nondominant broad‐leaved species were identified, nor were allometric changes associated with nitrogen fertilization. For P. taeda , it is concluded that eCO 2 affects allometries, and that knowledge of allometry changes is necessary to accurately compute biomass under eCO 2 . Further observations are needed to determine whether this assessment holds for other taxa.

Kim, Dohyoung↗
DOE OSTI2024

Defining blood hematology reference values in female pig-tailed macaques ( Macaca nemestrina ) using the Isolation Forest algorithm

Background: Pig-tailed macaques (PTMs) are commonly used as preclinical models to assess antiretroviral drugs for HIV prevention research. Drug toxicities and disease pathologies are often preceded by changes in blood hematology. To better assess the safety profile of pharmaceuticals, we defined normal ranges of hematological values in PTMs using an Isolation Forest (iForest) algorithm. Methods: Eighteen female PTMs were evaluated. Blood was collected 1–24 times per animal for a total of 159 samples. Complete blood counts were performed, and iForest was used to analyze the hematology data to detect outliers. Results: Median, IQR, and ranges were calculated for 13 hematology parameters. From all samples, 22 outliers were detected. These outliers were excluded from the reference index. Conclusions: Using iForest, we defined a normal range for hematology parameters in female PTMs. This reference index can be a valuable tool for future studies evaluating drug toxicities in PTMs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Short-term variation in leaf-level water use efficiency in a tropical forest

Here we report the representation of stomatal regulation of transpiration and CO 2 assimilation is key to forecasting terrestrial ecosystem responses to global change. Given its importance in determining the relationship between forest productivity and climate, accurate and mechanistic model representation of the relationship between stomatal conductance (g s ) and assimilation is crucial. We assess possible physiological and mechanistic controls on the estimation of the g 1 (stomatal slope, inversely proportional to water use efficiency) and g 0 (stomatal intercept) parameters, using diurnal gas exchange surveys and leaf level response curves of six tropical broadleaf evergreen tree species. g 1 estimated from ex-situ response curves averaged 50% less than g 1 estimated from survey data. While g 0 and g 1 varied between leaves of different phenological stages, the trend was not consistent among species. We identified a diurnal trend associated with g 1 and g 0 that significantly improved model projections of diurnal trends in transpiration. The accuracy of modelled g s can be improved by accounting for variation in stomatal behavior across diurnal periods, and between measurement approaches, rather than focusing on phenological variation in stomatal behavior. Additional investigation into the primary mechanisms responsible for diurnal variation in g 1 will be required to account for this phenomena in land surface models.

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↗
DOE OSTI2024

Carbon-phosphorus cycle models overestimate CO 2 enrichment response in a mature Eucalyptus forest

The importance of phosphorus (P) in regulating ecosystem responses to climate change has fostered P-cycle implementation in land surface models, but their CO 2 effects predictions have not been evaluated against measurements. Here, we perform a data-driven model evaluation where simulations of eight widely used P-enabled models were confronted with observations from a long-term free-air CO 2 enrichment experiment in a mature, P-limited Eucalyptus forest. We show that most models predicted the correct sign and magnitude of the CO 2 effect on ecosystem carbon (C) sequestration, but they generally overestimated the effects on plant C uptake and growth. We identify leaf-to-canopy scaling of photosynthesis, plant tissue stoichiometry, plant belowground C allocation, and the subsequent consequences for plant-microbial interaction as key areas in which models of ecosystem C-P interaction can be improved. Together, this data-model intercomparison reveals data-driven insights into the performance and functionality of P-enabled models and adds to the existing evidence that the global CO 2 -driven carbon sink is overestimated by models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Genome Sequences of Frankineae sp. Strain MT45 and Jatrophihabitans sp. Strain GAS493, Two Actinobacteria Isolated from Forest Soil

Frankiaceae are bacterial endosymbionts that are also found free-living in soil. Here, we present the genome sequences of two novel bacterial members of the order Frankiales , class Actinobacteria , isolated from temperate terrestrial forest soils. The genomes for MT45 and GAS493 indicate a genetic capacity for carbohydrate degradation but not nitrogen fixation.

DeAngelis, Kristen M.↗
DOE OSTI2020

Complementary Metagenomic Approaches Improve Reconstruction of Microbial Diversity in a Forest Soil

ABSTRACT Soil ecosystems harbor diverse microorganisms and yet remain only partially characterized as neither single-cell sequencing nor whole-community sequencing offers a complete picture of these complex communities. Thus, the genetic and metabolic potential of this “uncultivated majority” remains underexplored. To address these challenges, we applied a pooled-cell-sorting-based mini-metagenomics approach and compared the results to bulk metagenomics. Informatic binning of these data produced 200 mini-metagenome assembled genomes (sorted-MAGs) and 29 bulk metagenome assembled genomes (MAGs). The sorted and bulk MAGs increased the known phylogenetic diversity of soil taxa by 7.2% with respect to the Joint Genome Institute IMG/M database and showed clade-specific sequence recruitment patterns across diverse terrestrial soil metagenomes. Additionally, sorted-MAGs expanded the rare biosphere not captured through MAGs from bulk sequences, exemplified through phylogenetic and functional analyses of members of the phylum Bacteroidetes . Analysis of 67 Bacteroidetes sorted-MAGs showed conserved patterns of carbon metabolism across four clades. These results indicate that mini-metagenomics enables genome-resolved investigation of predicted metabolism and demonstrates the utility of combining metagenomics methods to tap into the diversity of heterogeneous microbial assemblages. IMPORTANCE Microbial ecologists have historically used cultivation-based approaches as well as amplicon sequencing and shotgun metagenomics to characterize microbial diversity in soil. However, challenges persist in the study of microbial diversity, including the recalcitrance of the majority of microorganisms to laboratory cultivation and limited sequence assembly from highly complex samples. The uncultivated majority thus remains a reservoir of untapped genetic diversity. To address some of the challenges associated with bulk metagenomics as well as low throughput of single-cell genomics, we applied flow cytometry-enabled mini-metagenomics to capture expanded microbial diversity from forest soil and compare it to soil bulk metagenomics. Our resulting data from this pooled-cell sorting approach combined with bulk metagenomics revealed increased phylogenetic diversity through novel soil taxa and rare biosphere members. In-depth analysis of genomes within the highly represented Bacteroidetes phylum provided insights into conserved and clade-specific patterns of carbon metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Effect of gap size on composition and structure of regeneration 19 years after harvest in a southeastern bottomland forest, USA

Following timber harvests in bottomland mixed-oak (Quercus L.) stands, desirable oak advance regeneration can be overgrown by shade-intolerant pioneer species. We investigated the effects of group selection opening size on composition of tree regeneration 19 years postharvest in an oak-dominated bottomland forest and compared results with earlier findings to evaluate development trends. In response to six opening sizes (7–40 m radii), we evaluated regeneration density and dominance of four tree species groups: conifers, hard mast, shade-intolerant hardwoods, and shade-tolerant hardwoods. Our objectives were to determine the optimum gap size for regenerating oaks and test the delayed oak dominance hypothesis, in which oaks slowly gain dominance as pioneer species undergo self-thinning. Opening size influenced conifer regeneration but minimally affected hardwoods. Hard mast species density was less than that of either intolerant or tolerant species regardless of opening size. Future stem density trends suggest increasing intolerant species and constant mast and tolerant species. Modeled future height trends suggest increasing mast species dominance over intolerant pioneers after 30 years. Furthermore, our results suggest that gap-based silviculture can be used to regenerate bottomland hardwood stands with desirable species including oaks; larger gaps favor conifers but there was no optimum size to enhance oak regeneration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Bayesian calibration of stochastic agent based model via random forest

SAND2024-11403O The Bayesian Calibration of Stochastic Agent-based Model via Random Forest is a code that was developed in concurrence with an article by the same name that was written for a journal. The code reproduces simulation results and plots from the article. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2024

Feature Pathway Graphs using Random Forest Regressors

SAND2025-04671O Feature Pathway Graphs using Random Forest Regressors is a software tool that uses machine learning to determine pathways of influence between features in data sets. It can be used as a surrogate method for casual discovery. The output creates pathway graphs between features of interest. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Peterson, Matthew↗
DOE OSTI2021

Climatology of Linear Mesoscale Convective System Morphology in the United States based on Random Forests Method

This study uses machine learning methods, specifically the random forest (RF), on a radar-based mesoscale convective system (MCS) tracking dataset to classify the five types of linear MCS morphology in the contiguous United States during the period 2004-2016. The algorithm is trained using radar- and satellite-derived spatial and morphological parameters, and reanalysis environmental information from 5-26yr manually identified nonlinear and five linear MCS modes. The algorithm is then used to automate the classification of linear MCSs over 8 years with high accuracy, providing a systematic, long-term climatology of linear MCSs. Results reveal that nearly 40% of MCSs are classified as linear MCSs, in which half of the linear events belong to the type of system having a leading convective line. The occurrence of linear MCSs shows large annual and seasonal variations. On average, 113 linear MCSs occur annually during the warm season (through March to October), with most of these events clustered from May through August in the central eastern Great Plains. MCS characteristics, including duration, propagation speed, orientation, and system cloud size, have large variability among the different linear modes. The systems having a trailing convective line and the systems having a back-building area of convection typically move more slowly and have higher precipitation rate, and thus have higher potential in producing extreme rainfall and flash flooding. Analysis of the environmental conditions associated with linear MCSs show that the storm-relative flow is of most importance in determining the organization mode of linear MCSs.

Cui, Wenjun↗
DOE OSTI2024

Case study of UAS ignition of prescribed fire in a mixedwood on the William B. Bankhead National Forest, Alabama

Abstract Background For at least four decades, practitioners have recognized advantages of aerial versus ground ignition for maximizing the effectiveness of prescribed fires. For example, larger areas can be ignited in less time, or ignition energy may be variously targeted over an area in accordance with the uneven distribution of fuels. The maturation of wireless communication, geopositioning systems, and unmanned aerial systems (UAS) has enhanced those advantages, and UAS approaches also provide further advantages relative to helicopter ignitions, such as reduced risk to human safety, lower operating costs, and higher operational flexibility. In a long running study at the Bankhead National Forest in northcentral Alabama, prescribed fire has been used for nearly 20 years. Most of the burns have been hand-ignited via drip torches, while some have been aerially ignited via helicopter. In March 2022, for the first time, a UAS was used to ignite prescribed fires across a landscape that included a long-term research stand. This field note relates comparisons of both fire behavior and fuel consumption metrics for the UAS-ignited burn versus previous burns on the same stand, and versus burns of other research stands in the same year. Results The UAS-ignited prescribed fire experienced burn effects similar to those from ground-ignited prescribed fires on the same stand in previous years, as well as those from ground-ignited prescribed fires on other stands in the same year. Conclusion This post hoc analysis suggests that UAS ignition approaches may be sufficient for achieving prescribed burn goals, thereby enabling practitioners to realize the advantages offered by that ignition mode.

Environmental Sciences & Ecology↗
DOE OSTI2020

Blodgett Forest CA Warming Experiment Soil Gas Well Data March 2014 to June 2017

These are soil gas data from the whole soil profile warming experiment at the University of California Blodgett Forest Research Station, in the Sierra Nevada foothills near Georgetown, CA at 1370 m above sea level. Mean annual precipitation is 1774 mm with most of it occurring from November through April and mean annual temperature is about 12.5°C . The experiment is in a thinned 80-year-old stand of mixed conifers including ponderosa pine (Pinus ponderosa), sugar pine (Pinus lambertiana), incense cedar (Calodefrus decurrens), white fir (Abies concolor), and douglas fir (Pseudotsuga menziesii). The soils are Holland series: fine-loamy, mixed, superactive, mesic Ultic Haploxeralfs of granitic origin with thick, >5 cm O horizons, minimal carbonates , and a pH that ranges from 5.6 to 6.5. The warming experiment warms the top meter of the soil profile to +4°C above ambient. These data include depth-resolved measurements of CO2 concentrations, 13CO2, apparent respiration quotients, soil temperature, and soil moisture (VWC). These data can be used to model CO2 production rates across the soil profile or to track how the sources and processes contributing to soil respiration change seasonally and with warming.

13C↗
DOE OSTI2021

Blodgett Forest CA Warming Experiment phospholipid fatty acid and branched glycerol dialkyl glycerol tetraethers data 2018 from: "Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil".

This data package contains phospholipid fatty acid and branched glycerol dialkyl glycerol tetraethers data used for the paper: “Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil”. SOIL, https://doi.org/10.5194/soil-2021-14.On April 2018 (after 4.5 years of warming), we collected soil cores down to 90 cm depth from the whole soil profile warming experiment at the University of California Blodgett Forest Research Station, in the Sierra Nevada foothills near Georgetown, CA at 1370 m above sea level. Cores were collected from 6 experimental plots (three replicated blocks); samples were collected in 10 cm increments from 0 to 90 cm depth.This data package includes a file in .csv format and a file in .xlsx format, which can be accessed and processed using MS Excel or R. Phospholipid fatty acid and branched glycerol dialkyl glycerol tetraethers concentrations are provided as processed data files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Chemistry data from soils and soil incubation experiments from the whole-soil warming experiment at Blodgett Forest, CA, 2018, from: “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile”

This dataset contains soil chemistry data of soils from the whole-soil warming experiment at Blodgett Forest in June 2018, and from laboratory incubation experiments conducted with a subset of those soils. Soil samples were collected at five different depths down to 80 cm from soil plots continuously heated by 4°C above ambient temperature for 4.5 years, and from the respective unheated control plots. Incubation experiments were conducted for 28 days with soils collected between 10-30 cm (“surface soils”) and 60-80 cm (“subsoils”) from heated and unheated field plots, amended in the laboratory with cellobiose (C, carbon amendment), or cellobiose plus ammonium and phosphate (CNP, combined carbon, nitrogen and phosphorus amendment). The dataset includes separate files for: (i) total carbon and nitrogen concentrations of initial field soils; (ii) carbon dioxide efflux rates at multiple times throughout the incubation experiments, and respective cumulative carbon dioxide efflux rates, as well as inorganic nitrogen concentrations at the beginning and end of the incubations, and net nitrogen mineralization rates and carbon use efficiency calculated at the end of the incubation. Analysis of these data has been published in Dove et al., (2021), “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile. Nat. Commun. 12:2089”, https://doi.org/10.1038/s41467-021-22408-5. This research was performed as part of the TES Belowground Biogeochemistry SFA project at Lawrence Berkeley National Laboratory.

54 ENVIRONMENTAL SCIENCES↗