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At least 37 records · Page 2

Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data

The problem of distinguishing between green vegetation, nonphotosynthetic vegetation (NPV, such as dry grass, leaf litter, and woody material), and soils in imaging-spectrometer data is addressed by analyzing an image taken by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over the Jasper Ridge Biological Preserve (California) on September 20, 1989, using spectral mixture analysis. Over 98 percent of the spectral variation could be explained by linear mixtures of three endmembers, green vegetation, shade, and soil. NPV, which could not be distinguished from soil when included as an endmember, was discriminated by residual spectra that contained cellulose and lignin absorptions. Distinct communities of green vegetation were distinguished by (1) nonlinear mixing effect caused by transmission and scattering by green leaves, (2) variations in a derived canopy-shade spectrum, and (3) the fraction of NPV.

Roberts, D. A.↗

Using AVIRIS images to measure temporal trends in abundance of photosynthetic and nonphotosynthetic canopy components

The Jasper Ridge Biological Preserve, Stanford, California is a good example of hardwood rangeland ecosystems in California. Structurally, it is composed of a mosaic of serpentine grasslands, oak savannah, coastal chaparral, and mixed evergreen woodland, representing a broad cross-section of physiognomic classes. The Mediterranean climate produces an extended seasonal drought lasting throughout most of the growing season and has significant impact on the expression of divergent phenological patterns related to contrasting ecological strategies of these taxa. The region is well understood biologically due to the rich history of ecological research at the site. Thus, community characteristics, physiological characteristics, phenology, and temporal dynamics are reasonably well understood for many of the dominant species. Because of its proximity to NASA Ames Research Center, it has been subject to a large number of aircraft data acquisitions over many years. A more complete examination of this database would provide an opportunity to test current remote sensing hypotheses for measurement and detection of ecological attributes, particularly those involving canopy chemistry and physiology. Better definition of ecological rules might permit development of remotely sensed surrogate variables for biological properties that cannot be directly measured or measured with sufficient accuracy.

Ustin, Susan L.↗

Temporal variation in spectral detection thresholds of substrate and vegetation in AVIRIS images

The ability to map changes over large surface areas over time is one of the advantages in using remote sensing as a monitoring tool. Temporal changes in the surface may be gradual, making them difficult to detect in the short-term, and because they commonly occur at the subpixel scale, they may be difficult to detect in the long-term as well. Also, subtle changes may be real or merely an artifact of image noise. It is, therefore, necessary to understand the factors that limit the detection of surface materials in evaluating temporal data. The spectral detectability of vegetation and soil in the 1990 July and October Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of Jasper Ridge, CA was evaluated and compared.

Sabol, Donald E., Jr.↗

Evaluation of the photochemical reflectance index in AVIRIS imagery

In this paper, we evaluate the potential for extracting the 'photochemical reflectance index' (PRI; previously called the 'physiological reflectance index') from AVIRIS data. This index, which is derived from narrow-band reflectance at 531 and 570 nm, has proven to be a useful indicator of photosynthetic function at the leaf and canopy scales. At the leaf level, PRI varies with photosynthetic capacity, radiation-use efficiency, and vegetation type (unpublished data). This finding is consistent with the hypothesis that vegetation types exhibiting chronically reduced photosynthesis during periods of stress (e.g. drought-tolerant evergreens) invest proportionally more in photoprotective processes than vegetation with high photosynthetic capacity (e.g. crops or deciduous perennials). Vertical transects in tropical and boreal forest canopies have indicated declines in PRI associated with downregulation of photosynthesis at the canopy tops under sunny, dry midday conditions (unpublished data). This reduced PRI in upper canopy levels provides a further basis for examining this signal with the 'view from above' afforded by aircraft overflights. Although many factors could confound interpretation of a subtle physiological signal at the landscape scale, we conducted a preliminary examination of PRI extracted from existing, AVIRIS imagery of Stanford University's Jasper Ridge Biological Preserve obtained on the June 2nd, 1992, overflight. The goal was to use the hyperspectral capabilities of AVIRIS to evaluate the potential of this index for obtaining useful physiological data at the landscape scale. The expectation based on leaf- and canopy-level studies was that regions containing vegetation of reduced photosynthetic capacity (e.g. chaparral or evergreen woodland) would exhibit lower PRI values than regions of high capacity (e.g. deciduous woodland).

Gamon, John A.↗

Black Hills Wildfires: Mapping Post-fire Conifer Regeneration using Snow-on Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high-severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled additional reforestation sites planted in 2001–2013. In Google Earth Engine (GEE), the field data and imagery were used to train a Random Forest (RF) model. The RF model classified 2021 conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3%. Approximately 45.9% of the high-severity burn had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration.

Casey Menick​↗

Black Hills Wildfires: Mapping Post-Fire Conifer Regeneration using Snow-On Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high-severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled additional reforestation sites planted in 2001–2013. In Google Earth Engine (GEE), the field data and imagery were used to train a Random Forest (RF) model. The RF model classified 2021 conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3%. Approximately 45.9% of the high-severity burn had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration.

Casey Menick↗

Mapping Post-fire Conifer Regeneration using Snow-on Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled reforestation sites planted from 2001–2013. The field data and imagery were used to train a Random Forest (RF) model in Google Earth Engine. The RF model classified conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3% for 2021. Approximately 45.9% of the high-severity burn area had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration in a post-wildfire landscape.

Yeshey Seldon↗

Comparison of the Forward and Reverse Photocycle Dynamics of Two Highly Similar Canonical Red/Green Cyanobacteriochromes Reveals Unexpected Differences

Cyanobacteriochromes (CBCRs) are cyanobacterial photoreceptors that exhibit photochromism between two states: a thermally stable dark-adapted state and a metastable light-adapted state with bound linear tetrapyrrole (bilin) chromophores possessing 15Z and 15E configurations, respectively. The photodynamics of canonical red/green CBCRs have been extensively studied; however, the time scales of their excited-state lifetimes and subsequent ground-state evolution rates widely differ and, at present, remain difficult to predict. Here, we compare the photodynamics of two closely related red/green CBCRs that have substantial sequence identity (~68%) and similar chromophore environments: AnPixJg2 from Anabaena sp. PCC 7120 and NpR6012g4 from Nostoc punctiforme. Using broadband transient absorption spectroscopy on the primary (125 fs to 7 ns) and secondary (7 ns to 10 ms) time scales together with global analysis modeling, our studies revealed that AnPixJg2 and NpR6012g4 have comparable quantum yields for initiating the forward ( 15Z P r → 15E P g ) and reverse ( 15E P g → 15Z P r ) reactions, which proceed through monotonic and nonmonotonic mechanisms, respectively. In addition to small discrepancies in the kinetics, the secondary reverse dynamics resolved unique features for each domain: intermediate shunts in NpR6012g4 and a Meta-Gf intermediate red-shifted from the 15Z P r photoproduct in AnPixJg2. Altogether, this study supports the conclusion that sequence similarity is a useful criterion for predicting pathways of the light-induced evolution and quantum yield of generating primary intermediate Φ p within subfamilies of CBCRs, but more studies are still needed to develop a comprehensive molecular level understanding of these processes.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic Interfacial Architectures: Cruciferin‐Stabilized Oil/Water Interfaces for Sustainable Emulsions

Stabilizing oil-water interfaces in emulsions by plant-based proteins provides sustainable and tunable ways for designing emulsions with specific properties, for food, healthcare, and pharmaceuticals. Cruciferin, a protein from rapeseed, has great potential as green emulsifier, but details about its structure and mobility at oil-water interfaces are largely unknown. Here, these properties are studied with small angle neutron and x-ray scattering, and neutron spin echo spectroscopy, analyzed by atomistic modelling of scattering curves and coarse-grained modelling, to gain insight into interface coverage, and molecular conformation and mobility at the interface. Cruciferin assumes trimeric conformations at the interface, as in solution, but with its protrusions from the central core of the subunits (“arms”) more compressed. Interfacial mobility is only marginally lower than in solution, indicating the arms still transiently extend and preserve a network, for the first time revealing the mechanism how cruciferin forms highly elastic 2d gel-like oil-water interfaces, as observed in macroscopic rheology. The high interfacial mobility may help in self-repairing non-stabilized interfacial fractions, reducing coalescence. These findings provide a deeper molecular level understanding of proteins at oil-water interfaces, which can stimulate development of new plant-based emulsion products, and contribute to the global protein transition.

cruciferin↗

Characterization of a Mo-Nitrogenase Variant Containing a Citrate-Substituted Cofactor

Nitrogenase converts N 2 to NH 3 , and CO to hydrocarbons, at its cofactor site. In this work, we report a biochemical and spectroscopic characterization of a Mo-nitrogenase variant expressed in an Azotobacter vinelandii strain containing a deletion of nifV, the gene encoding the homocitrate synthase. Designated NifDK Cit , the catalytic component of this Mo-nitrogenase variant contains a citrate-substituted cofactor analogue. Activity analysis of NifDK Cit reveals a shift of CO reduction from H 2 evolution toward hydrocarbon formation and an opposite shift of N 2 reduction from NH 3 formation toward H 2 evolution. Consistent with a shift in the Mo K-edge energy of NifDK Cit relative to that of its wild-type counterpart, EPR analysis demonstrates a broadening of the line-shape and a decrease in the intensity of the cofactor-originated S=3/2 signal, suggesting a change in the spin properties of the cofactor upon citrate substitution. These observations point to a crucial role of homocitrate in substrate reduction by nitrogenase and the possibility to tune product profiles of nitrogenase reactions via organic ligand substitution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Initiation and Carbene Induced Radical Chain Reactions in CH 2 F 2 Pyrolysis

High temperature dissociations of organic molecules typically involve a competition between radical and molecular processes. In this work, we use a modeling, experiment, theory (MET) framework to characterize the high temperature thermal dissociation of CH 2 F 2 , a flammable hydrofluorocarbon (HFC) that finds widespread use as a refrigerant. Initiation in CH 2 F 2 proceeds via a molecular elimination channel; CH 2 F 2 →CHF+HF. Here we show that the subsequent self-reactions of the singlet carbene, CHF, are fast multichannel processes and a facile source of radicals that initiate rapid chain propagation reactions. These have a marked influence on the decomposition kinetics of CH 2 F 2 . The inclusion of these reactions brings the simulations into better agreement with the present and literature experiments. Additionally, flame simulations indicate that inclusion of the CHF+CHF multichannel reaction leads to a noticeable enhancement in predictions of laminar flame speeds, a key parameter that is used to determine the flammability of a refrigerant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID-19 pandemic

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here, in this study, we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap-nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID-19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site-level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

54 ENVIRONMENTAL SCIENCES↗

“Third-body” collision parameters for hydrocarbons, alcohols, and hydroperoxides and an effective internal rotor approach for estimating them

Collision rate constants and third-body collision efficiencies are calculated for more than 300 alkanes, alcohols, and hydroperoxides, for the bath gases He, Ar, H 2 , and N 2 , and from 300 to 2000 K. The data set includes highly branched species and species with as many as 16 nonhydrogen atoms N , and it is analyzed to develop strategies for estimating collision properties more generally. Simple analytic formulas describing the Lennard-Jones collision parameters $σ$ and $ε$ are obtained for each of the three classes of systems as a function of N . Trends in the collision efficiency range parameter $α$ = $\langle$Δ E d $\rangle$ are more complicated, and a method is developed and validated for estimating $α$ based on the numbers and types of internal rotors and oxygen-containing groups. Specifically, the approach maps the expected value of $α$ for a branched alkane, alcohol, or hydroperoxide onto those for the corresponding normal (linear) series via an effective number of nonhydrogen atoms N eff . The prescription for N eff is based on counting internal rotor types and is shown to be insensitive to temperature and fairly insensitive to the identity of the bath gas. Together, these strategies allow for the ready estimation of the collision parameters $σ$, $ε$, and $α$ so long as results for the associated linear series are available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Calibration and uncertainty quantification for Davis Equation of State models for the High Explosive PBX 9501 products

Abstract This paper investigates the uncertainty in the parameters used in the calibration of an Davis Equation Of State (EOS) for the detonation products of the High Explosive PBX 9501. The procedure sought to make use of all available information about this HE to inform the best set of calibration parameters as well as the uncertainty in these parameters. The procedure made use of historical experimental data, the results from thermo‐chemical modeling as well as data on the best isentrope function fit to cylinder test experimental data. Combining all these heterogeneous data sources together in a Bayesian calibration, yielded a posterior mean and covariance. Sampling from the posterior distribution and evaluating an important Quantity Of Interest (QOI) in the EOS model, the detonation speed of a one‐inch rate stick, produced a distribution which showed variations which were in agreement with experiments. The uncertainty in the EOS was reported as eleven sets of model calibrations which spanned the range of this QOI.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Understanding Electrical Conduction and Nanopore Formation During Controlled Breakdown

Controlled breakdown has recently emerged as a highly appealing technique to fabricate solid-state nanopores for a wide range of biosensing applications. This technique relies on applying an electric field of approximately 0.4–1 V nm –1 across the membrane to induce a current, and eventually, breakdown of the dielectric. Although previous studies have performed controlled breakdown under a range of different conditions, the mechanism of conduction and breakdown has not been fully explored. Here, electrical conduction and nanopore formation in SiN x membranes during controlled breakdown is studied. It is demonstrated that for Si-rich SiN x , oxidation reactions that occur at the membrane-electrolyte interface limit conduction across the dielectric. However, for stoichiometric Si 3 N 4 the effect of oxidation reactions becomes relatively small and conduction is predominately limited by charge transport across the dielectric. Several important implications resulting from understanding this process are provided which will aid in further developing controlled breakdown in the coming years, particularly for extending this technique to integrate nanopores with on-chip nanostructures.

36 MATERIALS SCIENCE↗

Loads assessment of a fixed-bottom offshore wind farm with wake steering

Wake steering via deliberate yaw offset is an emerging wind farm control technique that has the potential to mitigate wake losses and further increase wind farm energy yield. The loads impact of this technique has been studied, but there is limited insight into wind-farm-wide impacts of wake steering. Understanding such impacts is crucial to determining the feasibility of using wake steering in commercial wind farms. To that end, this work investigates the impacts of wake steering on the loads of all turbine components across all turbines in a wind farm operating under a broad set of inflow conditions, including inflow velocity, shear exponent, turbulence class, and inflow angle. This was done by performing FAST.Farm simulations of a 12-turbine wind farm array, excerpted from a larger hypothetical wind farm. The International Energy Agency Wind 15-MW reference wind turbine was modeled atop a monopile substructure, an open-source model that closely approximates the properties of similar commercial options. Wake steering was included via yaw offsets that were computed using an offline optimization with the National Renewable Energy Laboratory tool FLORIS. For each inflow case, the 12-turbine array was simulated with and without wake steering. Results were compared in terms of time-averaged means, standard deviations, ultimate loads, and damage-equivalent loads. The findings show that because wake steering is generally applied at rated wind speeds and below, it is unlikely to drive ultimate loads. For fatigue loads, wake steering does increase the overall fatigue accumulation for some load channels, such as blade-root and shaft bending. This is to be expected when overall power yield increases but may cause the damage accumulation to be more uniform throughout the array. The significance of the added fatigue loading is dependent on how frequent wake steering is utilized in the overall set of inflow conditions across the wind rose.

17 WIND ENERGY↗

Bose-Einstein correlations of charged hadrons in proton-proton collisions at $\sqrt{s} =$ 13 TeV

Bose-Einstein correlations of charged hadrons are measured over a broad multiplicity range, from a few particles up to about 250 reconstructed charged hadrons in proton-proton collisions at $ \sqrt{s} $ = 13 TeV. The results are based on data collected using the CMS detector at the LHC during runs with a special low-pileup configuration. Three analysis techniques with different degrees of dependence on simulations are used to remove the non-Bose-Einstein background from the correlation functions. All three methods give consistent results. The measured lengths of homogeneity are studied as functions of particle multiplicity as well as average pair transverse momentum and mass. The results are compared with data from both CMS and ATLAS at $ \sqrt{s} $ = 7 TeV, as well as with theoretical predictions.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for a heavy pseudoscalar Higgs boson decaying into a 125 GeV Higgs boson and a Z boson in final states with two tau and two light leptons at $\sqrt{s}=$ 13 TeV

A search is performed for a pseudoscalar Higgs boson, A, decaying into a 125 GeV Higgs boson h and a Z boson. The h boson is specifically targeted in its decay into a pair of tau leptons, while the Z boson decays into a pair of electrons or muons. A data sample of proton-proton collisions collected by the CMS experiment at the LHC at $ \sqrt{s} $ = 13 TeV is used, corresponding to an integrated luminosity of 35.9 fb$^{−1}$. No excess above the standard model background expectations is observed in data. A model-independent upper limit is set on the product of the gluon fusion production cross section for the A boson and the branching fraction to Zh → ℓℓττ. The observed upper limit at 95% confidence level ranges from 27 to 5 fb for A boson masses from 220 to 400 GeV, respectively. The results are used to constrain the extended Higgs sector parameters for two benchmark scenarios of the minimal supersymmetric standard model.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗