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101 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Leaf-level physiological strategies related to productivity and plasticity of Populus in the Southeastern United States

Introduction: Populus and its hybrids are attractive bioenergy crops and the southeastern United States has broad ability to supply bioenergy markets with woody biomass. Breeding and hybridization have led to superior eastern cottonwood (Populus deltoides W. Bartram ex Marshall) and hybrid poplars adapted to a wide variety of site types not suited for agricultural production. In order to maximize productivity and minimize inputs, genotypes need to efficiently use available site resources and tolerate environmental stresses. In addition, we need to determine plasticity of traits and their coordination across sites to select traits that will broadly characterize genotypes. Therefore, our study objectives were to determine (1) which leaf traits were correlated with growth, (2) if traits and genotypes exhibited significant plasticity across sites, and (3) how traits were coordinated within and across sites and Populus taxa. Methods: We measured trees at two sites in northeastern Mississippi, United States: one upland and one alluvial terrace site. Genotypes included eastern cottonwoods as well as F 1 crosses of eastern cottonwood and P. maximowiczii (Henry), P. nigra (L.) and P. trichocarpa (Torr. & Gray). Results: We found that sites differed in which leaf traits were correlated with productivity; with water use efficiency specifically being positively correlated with growth at an alluvial terrace site, but negatively correlated with growth at an upland site. Tree height growth, leaf isotope composition (δ 13 C and δ 15 N), as well as leaf mass per area (LMA) exhibited the least plasticity across sites, while physiological gas exchange parameters and leaf nitrogen concentration exhibited the highest plasticity. Broadly across taxa, leaf carbon isotope ratios were correlated with intrinsic water use efficiency, and stomatal conductance was positively correlated with photosynthetic nitrogen use efficiency across sites, while leaf nitrogen isotope ratios exhibited contrasting relationships with leaf nitrogen concentration. Discussion: Overall, these results allow us to refine selections of productive genotypes based on site conditions and site-specific relationships with physiological parameters to better match Populus taxa with sites and landowner objectives.

bioenergy feedstocks↗
DOE OSTI2025

Constraining non-standard neutrino interactions with neutral current events at long-baseline oscillation experiments

We explore, for the first time, neutral-current events at long-baseline experiments to constrain vector and axial-vector neutrino non-standard interactions (NSI) with quarks. We leverage the flavor dependence of NSIs to perform an oscillation analysis in the neutral- current channel. We first introduce a framework to parametrize the effect of NSI on the cross section. Then, as an example, we analyze NOvA neutral-current data which provides significantly improved constraints on the axial-vector NSI parameters $ {\varepsilon}_{\mu \mu}^A $,$ {\varepsilon}_{\tau \tau}^A $ and $ {\varepsilon}_{e\mu}^A $. This is highly complementary to constraints from SNO data, which, differently from long-baseline neutral current data, is not sensitive to isospin conserving NSIs $ {\varepsilon}_u^A $ = $ {\varepsilon}_d^A $. Additionally, we disfavor large values of the diagonal vectorial NSI $ {\varepsilon}_{\mu \mu}^{VV} $ and $ {\varepsilon}_{\tau \tau}^V $ which originate from the LMA-Dark solution. We also highlight the complementarity between NSI searches at oscillation experiments using charged current and neutral current channels.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Leaf Nitrogen and Carbon Content, and Leaf Mass Per Area, Kougarok Road, Seward Peninsula, Alaska, 2018

Nitrogen and carbon content, leaf mass per area (LMA) and leaf water content (LWC) of leaves sampled from locations on the Kougarok mile marker 64 NGEE Arctic site, Seward Peninsula, Alaska. Samples were collected in July 2018 from Alnus viridis, Betula nana, Betula glandulosa, Arctostaphylos alpina and Salix pulchra. This data package includes leaf sample information and trait data (*.csv). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA207_flmd.csv. See data package NGA208 "Full spectrum 350-2500 nm canopy spectral reflectance, Seward Peninsula, Alaska, 2018" for linked canopy spectral reflectance data, dGPS locations and sample photographs. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Full Spectrum, 350 - 2500 nm, Leaf and Canopy Spectral Reflectance, Seward Peninsula, Alaska, 2017

Full-range (350 - 2500 nm) leaf and canopy reflectance spectra of various Arctic tundra ecosystem endmembers, including species-level leaf reflectance, canopy-scale species endmember spectra, plot-scale spectra, and transect spectra as well as non-vegetated surface (NVS) spectra. The datasets were collected at the three core NGEE-Arctic watersheds, Kougarok, Teller, and Council within the larger Seward Peninsula, Alaska region. The data were collected in the months of July and August of 2017 using a full-range Spectra Vista Corporation (SVC) HR-1024i spectroradiometer. Leaf-level spectra were collected with the original SVC leaf clip/plant probe connected to the spectrometer through a 1.15 meter long fiber optic cable, while canopy-scale reflectance was collected with an 8-degree field-of-view (FOV) foreoptic lens. All spectral measurements were collected as calibrated surface radiance and converted to surface reflectance using a 99.99% reflective Spectralon white reference standard. For those canopy spectra collected with associated functional trait data, the FOV of the instrument was positioned to include the same leaves harvested for functional trait measurements, including leaf mass per area (LMA) and foliar carbon and nitrogen content (see associated dataset). This data package includes 26 files in a variety of formats including processed canopy and leaf spectra (*.csv), processed dGPS locations (*.csv and *.kmz), digital photographs of spectral targets (*.jpg) and raw data from spectroradiometer and dGPS instruments (compressed as tar.gz). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA110_flmd.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Full spectrum (350-2500 nm) canopy spectral reflectance, Seward Peninsula, Alaska, 2018

Full-range (350-2500 nm) canopy reflectance spectra of various Arctic tundra ecosystem endmembers, including canopy-scale species endmember spectra, plot-scale spectra, and transect spectra as well as non-vegetated surface (NVS) spectra. The datasets were collected at the three core NGEE-Arctic watersheds, Kougarok, Teller, and Council, as well as the supplemental Kougarok Mile 80 site within the larger Seward Peninsula, Alaska region. The data were collected in July 2018 using a full-range Spectra Vista Corporation (SVC) HR-1024i spectroradiometer. Canopy-scale reflectance was collected with an 8-degree field-of-view (FOV) foreoptic lens. All spectral measurements were collected as calibrated surface radiance and converted to surface reflectance using a 99.99% reflective Spectralon white reference standard. For those canopy spectra collected with associated functional trait data, the FOV of the instrument was positioned to include the same leaves harvested for functional trait measurements, including leaf mass per area (LMA) and foliar carbon and nitrogen content (see associated dataset). Species included in the spectra and functional trait dataset include Alnus viridis, Betula nana, Betula glandulosa, Arctous alpina, and Salix pulchra. This data package includes 35 files in a variety of formats including processed canopy spectra (*.csv), processed dGPS locations (*.csv and *.kmz), digital photographs of spectral targets (*.jpg) and raw data from spectroradiometer and dGPS instruments (compressed as tar.gz). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA208_flmd.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Leaf structural and chemical traits, and vegetation temperature and height, Seward Peninsula, Alaska, 2019.

Leaf nitrogen and carbon content, leaf water content (LWC) and leaf mass per area (LMA) of leaves, and vegetation height and temperatures sampled from locations on the Teller MM 27, Kougarok MM 64 and Kougarok MM 80 NGEE Arctic sites, Seward Peninsula, Alaska. These data were collected in support of ongoing NASA ABoVE AVIRIS data synthesis work. Samples were collected in July 2019 from 24 species. This data package includes leaf sample information and vegetation trait data (*.csv). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA210_flmd.csv. See data package NGA212 "Full spectrum 350-2500 nm leaf and canopy spectral reflectance, Seward Peninsula, Alaska, 2019" for linked spectral reflectance data. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Full spectrum (350-2500 nm) leaf and canopy spectral reflectance, Seward Peninsula, Alaska, 2019

Full-range (350 - 2500 nm) leaf and canopy reflectance spectra of various Arctic tundra ecosystem endmembers, including species-level leaf reflectance, canopy-scale species endmember spectra, plot-scale spectra, and transect spectra. These data were collected in support of ongoing NASA ABoVE AVIRIS data synthesis work. The datasets were collected at the NGEE-Arctic watershed sites, Kougarok MM64 and MM80, and Teller MM27 on the Seward Peninsula, Alaska. The data were collected in July 2019 using a full-range Spectra Vista Corporation (SVC) HR-1024i spectroradiometer. Leaf-level spectra were collected with the original SVC leaf clip/plant probe connected to the spectrometer through a 1.15 meter long fiber optic cable, while canopy-scale reflectance was collected with an 8-degree field-of-view (FOV) foreoptic lens. All spectral measurements were collected as calibrated surface radiance and converted to surface reflectance using a 99.99% reflective Spectralon white reference standard. For those canopy spectra collected with associated functional trait data, the FOV of the instrument was positioned to include the same leaves harvested for functional trait measurements, including leaf mass per area (LMA) and foliar carbon and nitrogen content (see leaf trait data package for these data). Canopy spectra were obtained for 23 different species, and leaf spectra for 8 species. This data package includes processed canopy and leaf spectra (*.csv), processed dGPS locations (*.csv and *.kmz), digital photographs of spectral targets (*.jpg) and raw data from spectroradiometer and dGPS instruments (compressed as tar.gz). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA212_flmd.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Leaf mass area, leaf carbon and nitrogen content, Utqiagvik, Alaska, 2021-2022

Leaf mass per area (LMA), and leaf carbon and nitrogen content of an Arctic graminoid, Carex aquatilis, from within warming chambers and paired control plots. The plants were sampled in July 2021 and July 2022 as part of the Zero Power Warming (ZPW) vegetation warming experiment conducted on the Barrow Environmental Observatory (BEO), Utqiagvik (formerly Barrow), Alaska. Samples include leaves used for gas exchange measurements and bulk harvests from each warming chamber and paired ambient plot. The files included in this data package are in .csv format, and include 3 data files and 4 metadata files. See related datasets for plant physiology, phenology, thaw depth and environmental conditions of the plots and warming chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Solar Neutrino Observations at the Sudbury Neutrino Observatory

The Sudbury Neutrino Observatory (SNO) is a 1000-tonne heavy water Cherenkov detector. Its usage of \dto as target allows the simultaneous measurements of the $\nu_e$ flux from $^8$B decay in the Sun and the total flux of all active neutrino species through the charged-current and the neutral-current interactions on the deuterons. Assuming the standard $^{8}$B shape, the $\nu_e$ component of the $^{8}$B solar neutrino flux is measured to be $\phi_e = 1.76^{+0.05}_{-0.05}{(stat.)}^{+0.09}_{-0.09} {(syst.)} x 10^6 {\rm cm}^{-2} {\rm s}^{-1}$ for a kinetic energy threshold of 5 MeV. The non-\nue component is found to be Φ μτ $\= 3.41^{+0.45}_{-0.45}{(stat.)}^{+0.48}_{-0.45} {(syst.)} x 10^6 {\rm cm}^{-2} {\rm s}^{-1}$. This $5.3\sigma$ difference provides strong evidence for $\nu_{e}$ flavor transformation in the solar neutrino sector. The total active neutrino flux is measured with the neutral-current reaction at a neutrino energy threshold of 2.2 MeV. This flux is determined to be $\phi_{NC} = 5.09^{+0.44}_{-0.43}{(stat.)}^{+0.46}_{-0.43} {(syst.)} x 10^6 {\rm cm}^{-2} {\rm s}^{-1}$, and is consistent with solar model predictions. Assuming an undistorted $^8$B spectrum, the night minus day rate is 14.0$\pm$6.3(stat.)$^{+1.5}_{-1.4}$(sys.)\% of the average rate in the charged-current channel. If the total active neutrino flux is constrained to have no asymmetry, the night-day asymmetry in the $\nu_e$ flux is found to be 7.0$\pm$4.9(stat.)$^{+1.3}_{1.2}$(sys.)\%. A global analysis of all the available solar neutrino data in terms of matter-enhanced oscillations of two active flavors strongly favors the Large Mixing Angle (LMA) solution.

Poon, A. W. P.↗
DOE OSTI2021

ORNL FACE Final Harvest, 2009, with data on leaf characteristics and tree mass

During the final year of the Oak Ridge National Laboratory (ORNL) free-air CO2 enrichment (FACE) experiment, 16 trees were felled and processed during July 2009. The trees had been grown for 12 years in ambient or elevated CO2. Two data sets are reported. Leaf characteristics (leaf mass per unit area, leaf thickness, average leaf size, carbon and nitrogen concentrations) are reported for each 1-meter section of the tree crowns in data set "Canopy_subsamples.csv". The measurements were made on approximately 20 subsamples collected from each 1-meter section of the canopy. Wood dry mass, total tree height, basal area, total leaf mass and leaf area are reported in "Tree_harvest.csv", based on field measurements of fresh mass and dry mass to fresh mass ratio of subsamples. The ORNL FACE experiment, including photos of the harvesting activity, is described at: https://richnorby.org/home/face-home/.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression

Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices. One application of PLSR enables leaf traits to be estimated from hyperspectral optical reflectance data, facilitating rapid, high-throughput, non-destructive plant phenotyping. This technique is of interest and importance in a wide range of contexts including crop breeding and ecosystem monitoring. The lack of a consensus in the literature on how to perform PLSR means that interpreting model results can be challenging, applying existing models to novel datasets can be impossible, and unknown or undisclosed assumptions can lead to incorrect or spurious predictions. We address this lack of consensus by proposing best practices for using PLSR to predict plant traits from leaf-level hyperspectral data, including a discussion of when PLSR is applicable, and recommendations for data collection. Further, we provide a tutorial to demonstrate how to develop a PLSR model, in the form of an R script accompanying this manuscript. This practical guide will assist all those interpreting and using PLSR models to predict leaf traits from spectral data, and advocates for a unified approach to using PLSR for predicting traits from spectra in the plant sciences.

54 ENVIRONMENTAL SCIENCES↗