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At least 217 records · Page 12

Spectral characterization of biophysical characteristics in a boreal forest - Relationship between Thematic Mapper band reflectance and leaf area index for Aspen

Results from analysis of a data set of simultaneous measurements of Thematic Mapper band reflectance and leaf area index are presented. The measurements were made over pure stands of Aspen in the Superior National Forest of northern Minnesota. The analysis indicates that the reflectance may be sensitive to the leaf area index of the Aspen early in the season. The sensitivity disappears as the season progresses. Based on the results of model calculations, an explanation for the observed relationship is developed. The model calculations indicate that the sensitivity of the reflectance to the Aspen overstory depends on the amount of understory present.

Badhwar, G. D.↗

Coupling of high-resolution mass spectrometer and photosynthesis system for comprehensive leaf volatile metabolite profiling

Background Leaf-level biogenic volatile organic compounds (BVOCs) emissions represent a major source of organic gases in the atmosphere, influencing both climate and air quality. These emissions are strongly driven by environmental perturbations, which affect individual plant- to ecosystem-level processes. Uncovering all the BVOCs and understanding how their emissions respond to altered environmental conditions provide critical insights into vegetation-driven changes in atmospheric chemistry. We developed a tandem instrumentation setup that integrates a proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) with parts-per-trillion detection limits and a photosynthetic infrared gas exchange system for the untargeted survey of all the BVOCs. This novel system enables simultaneous, real-time monitoring of BVOC emissions and photosynthetic parameters at the leaf level, offering new opportunities to disentangle the physiological and environmental drivers of VOC release. Furthermore, we established the VOC Analysis and Processing Optimization Resource (VAPOR), an open-access software tool designed for rapid data post-processing and the analysis of the variability of hundreds of BVOCs. We assessed the performance of the tandem system under varying background conditions, using standard gas mixtures and a range of environmental factors. Results Blank emissions were substantially lower for major BVOCs (e.g., isoprene) compared to those observed in plant emissions. Despite this, the observation of background-level VOCs highlights the importance of routinely acquiring and accounting for blank measurements in analyses using the coupled instrumentation. Introduction of known VOC concentrations to the system demonstrated a linear response across different compounds with varying molecular compositions, indicating minimal gas loss regardless of chemical moieties within the coupled instrumentation. We applied the optimized system to investigate the physiological mechanisms driving BVOC emissions across different genotypes of poplar and pennycress. The high mass resolution capabilities of the PTR-ToF-MS, coupled with comprehensive VAPOR-driven data analysis, enabled the identification of several important BVOCs, including methanol and methanethiol; these BVOCs displayed substantial variation across pennycress genotypes and showed concentrations ~ 100–350% higher than the blank. Moreover, isoprene emissions varied significantly among poplar genotypes grown in different potting media. Conclusions Tandem instrumentation offers a powerful tool for profiling volatile molecular markers and elucidating their genetic and environmental underpinnings. This approach enhances our ability to predict BVOC emissions in response to genotype by environmental interactions and contributes to a deeper understanding of vegetation responses to environmental changes.

Biogenic volatile organic compounds↗

The Ecosystem as Super-Organ/ism, Revisited: Scaling Hydraulics to Forests under Climate Change

Synopsis Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO2) uptake and water vapor loss, important for predicting and managing the future of Earth’s ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for organs and organisms to enable and interpret measurements at ecosystem-level. We focus on three community-scale versions of water relations traits that have potential to provide mechanistic insight into climate change responses of forest CO2 and H2O gas exchange and productivity: leaf water potential (Ψcanopy), pressure volume curves (eco-PV), and hydraulic conductance (Keco). These analyses can reveal additional ecosystem-scale parameters analogous to those typically quantified for leaves or plants (e.g., wilting point and hydraulic vulnerability) that may act as thresholds in forest responses to drought, including growth cessation, mortality, and flammability. We unite these concepts in a novel framework to predict Ψcanopy and its approaching of critical thresholds during drought, using measurements of Keco and eco-PV curves. We thus delineate how the extension of water relations concepts from organ- and organism-scales can reveal the hydraulic constraints on the interaction of vegetation and climate and provide new mechanistic understanding and prediction of forest water use and productivity.

Zoology↗

The role of ethylene in the development of constant-light injury of potato and tomato

The role of ethylene in the development of constant-light injury of potato (Solanum tuberosum L.) and tomato (Lycopersicon esculentum Mill.) was investigated. In one study, silver thiosulfate (STS) was applied to the foliage of four potato cultivars growing under constant light. Leaf area and shoot dry mass of 'Kennebec' and 'Superior', cultivars normally injured by constant light, were greater (P < 0.05) than those of control plants given foliar applications of distilled water. Examination of STS-treated 'Kennebec' leaflets revealed significantly less injury (necrotic spotting and reduced starch content) than the water-treated controls. 'Norland' and 'Denali', cultivars tolerant of constant light, exhibited no differences in growth between treatments. In a second study, injury (necrotic spotting and reduced starch content) was induced in leaflets of 'Denali' when exposed to spray applications of 0.5 mmol L-1 ethephon or air containing 0.5 to 0.8 microL L-1 ethylene. In a third study, three genotypes of 'Ailsa Craig' tomato were grown under constant light. Leaves of the normal 'Ailsa Craig' exhibited epinasty, reduced chlorophyll concentration, and reduced starch content. Leaves of a mutant 'Ailsa Craig', containing the Never ripe mutation, did not exhibit epinasty but exhibited the same amount of reduced chlorophyll concentration and starch content as normal plants. Leaves of a transgenic 'Ailsa Craig', containing an antisense gene of 1-aminocyclopropane 1-carboxylate (ACC) oxidase, were epinastic, but chlorophyll concentration and starch content were greater than in leaves of normal and mutant plants. These results suggest that transgenic plants were more tolerant of constant light than the other genotypes. Evidence from these studies indicates that ethylene, combined with constant light, has an important role in the development of constant-light injury.

Non-NASA Center↗

Light Spectral Quality Effects on the Growth of Potato (Solanum Tuberosum L.) Nodal Cuttings in Vitro

The effects of light spectral quality on the growth of in vitro nodal cuttings of potato (Solanum tuberosum L.) cultivars Norland, Superior, Kennebec, and Denali were examined. The different light spectra were provided by Vita-Lite fluorescent (VF) (a white light control), blue fluorescent (BF), red fluorescent (RF), low-pressure sodium (LPS), and a combination of low-pressure sodium plus cool-white fluorescent lamps (LPS/CWF). For cultivars, stem lengths after 4 wks were longest under LPS, follow by RF, LPS/CWF, VF, and BF (in descending order). Microscopic studies revealed that cells were shortest when cultured in BF or VF environments, and were longest in RF or LPS lamp environments. The highest number axillary branches occurred on plantlets grown with LPS or LPS/CWF, whereas the lowest number occurred with BF. No leaf or stem edema (callus or gall-like growths) occurred iwth LPS or LPS/cwf lighting, and no edema occurred on cv. Norland plantlets, regardless of lighting. Results suggest that shoot morphologic development of in vitro grown potato plants can be controlled by controlling irradiant spectral quality.

Wilson, Deborah A.↗

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗

Crop Characteristics Research: Growth and Reflectance Analysis

Much of the early research in remote sensing follows along developing spectral signatures of cover types. It was found, however, that a signature from an unknown cover class could not always be matched to a catalog value of known cover class. This approach was abandoned and supervised classification schemes followed. These were not efficient and required extensive training. It was obvious that data acquired at a single time could not separate cover types. A large portion of the proposed research has concentrated on modeling the temporal behavior of agricultural crops and on removing the need for any training data in remote sensing surveys; the key to which is the solution of the so-called 'signature extension' problem. A clear need to develop spectral estimaters of crop ontogenic stages and yield has existed even though various correlations have been developed. Considerable effort in developing techniques to estimate these variables was devoted to this work. The need to accurately evaluate existing canopy reflectance model(s), improve these models, use them to understand the crop signatures, and estimate leaf area index was the third objective of the proposed work. A synopsis of this research effort is discussed.

Badhwar, G. D.↗

Measuring and modeling near surface reflected and emitted radiation fluxes at the FIFE site

Research was conducted during the four Intensive Field Campaigns (IFC) of the FIFE project in 1987. The research was done on a tall grass prairie with specific measurement sites on and near the Konza Prairie in Kansas. Measurements were made to help meet the following objectives: determination of the variability in reflected and emitted radiation fluxes in selected spectral wavebands as a function of topography and vegetative community; development of techniques to account for slope and sun angle effects on the radiation fluxes; estimation of shortwave albedo and net radiation fluxes using the reflected and emitted spectral measurements described; estimation of leaf and canopy spectral properties from calculated normalized differences coupled with off-nadir measurements using inversion techniques; estimation of plant water status at several locations with indices utilizing plant temperature and other environmental parameters; and determination of relationships between estimated plant water status and measured soil water content. Results are discussed.

Blad, Blaine L.↗

Field measurements, simulation modeling and development of analysis for moisture stressed corn and soybeans, 1982 studies

The experimental design, data acquisition and analysis procedures for agronomic and reflectance data acquired over corn and soybeans at the Sandhills Agricultural Laboratory of the University of Nebraska are described. The following conclusions were reached: (1) predictive leaf area estimation models can be defined which appear valid over a wide range of soils; (2) relative grain yield estimates over moisture stressed corn were improved by combining reflectance and thermal data; (3) corn phenology estimates using the model of Badhwar and Henderson (1981) exhibited systematic bias but were reasonably accurate; (4) canopy reflectance can be modelled to within approximately 10% of measured values; and (5) soybean pubescence significantly affects canopy reflectance, energy balance and water use relationships.

Blad, B. L.↗

Air temperature, Utqiagvik (Barrow), Alaska, July 15-17, 2022

Air temperature measured at 15 minute intervals using a HOBO 64K Pendant UA-001-64 housed in a solar radiation shield. Data were collected 15-27 July 2022, on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. The data package files are in .csv format, and include a data file and metadata file. These data were collected in support of stomatal response gas exchange measurements collected during this time period. See related data packages for leaf gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), and phenocamera images collected at the same time and location. 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↗

Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain

Microwave remote sensing of vegetated terrain has been studied. Vegetation is modeled so that backscattered radar signals can be used to infer parameters which characterize the vegetation and underlying ground. The vegetation is modeled by discrete lossy dielectric scatterers with prescribed characteristics. The goal of the modeling effort is to remotely sense vegetation type (classification), growth stage, and plant/ground moisture. This information can then be used as input into agricultural, forestry and global circulation models. The microwave frequency spectrum, particularly L and C bands, are especially appropriate for this purpose since the wavelength is comparable to plant leaf and stem size. The resulting resonant interaction leads to backscattered data highly depend on plant shape and orientation. In addition, the transparent nature of the atmosphere in this frequency regime allows for algorithm development which requires no atmospheric correction.

Lang, R. H.↗

Inferring spectral reflectances of plant elements by simple inversion of bidirectional reflectance measurements

Inverting previously developed explicit expressions for a vertical architecture, bidirectional reflectances measured over corn viewing from the solar quadrant at azimuths near the principal plane are used to determine the spectral reflectances of plant elements. The leaf reflectance values extracted in three visible bands at viewing zenith angles of 70 deg, 60 deg, and 45 deg agree closely with laboratory-measured reflectances of corn leaves. At viewing zenith angle of 30 deg, the inversion breaks down, inasmuch as the inferred plant element reflectances are too high. Satisfactory results are also achieved when the same approach is applied to bidirectional reflectances measured over potted balsam firs, but when applied to soybeans reflectances, the procedure yields unreasonably high leaf reflectances. The failure in this case is attributed to the nonvertical architecture of the soybean canopy; however, for this canopy, inversion based on horizontal architecture is possible. The bidirectional reflectances measured from the solar quadrant, at viewing angles appreciably far from 'hot spot' viewing, approximately equal in magnitude half of the leaf reflectance. The 0.5 ratio is predicted by a previous analysis of opaque horizontal Lambertian facets, as the asymptotic value for a dense canopy at any viewing angle. For soybeans, this ratio applies very closely at 15 deg viewing zenith angle. The results suggest that inversion based on simple architecture, applying explicit expressions, might be of value, either in itself or as a preliminary step before inversion applying complex models.

Otterman, J.↗

Modeling bidirectional reflectance of forests and woodlands using Boolean models and geometric optics

Geometric-optical discrete-element mathematical models for forest canopies have been developed using the Boolean logic and models of Serra. The geometric-optical approach is considered to be particularly well suited to describing the bidirectional reflectance of forest woodland canopies, where the concentration of leaf material within crowns and the resulting between-tree gaps make plane-parallel, radiative-transfer models inappropriate. The approach leads to invertible formulations, in which the spatial and directional variance provides the means for remote estimation of tree crown size, shape, and total cover from remotedly sensed imagery.

Strahler, Alan H.↗

NGEE Arctic Integrated Modeling (IM3): Improved snow-vegetation interaction

This data product represents the integration of new code capability for arctic tundra snow-vegetation-terrain interactions into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The NGEE Arctic project developed a total of six Integrated Modeling (IM) modules informed by observations and experiments. New ELM capability represented by this data product (IM3) falls into three categories: 1) Downscaling from gridcell to topographic unit level when working through the existing coupler bypass code. 2) Four new parameters (taper, stocking, bendresist, and vegshape) have been added to ELM to allow for flexible definition of snow-vegetation interactions. 3) Vegshape and bendresist parameters are used to calculate the fraction of leaf area and/or stem area buried by snow for a given snow depth. This data record consists of a single document (pdf format) that describes the theoretical basis for the snow-vegetation-terrain interactions added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. 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).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗

Contribution of Chlorophyll Fluorescence to the Reflectance of Corn Foliage

To assess the contribution of chlorophyll fluorescence (ChlF) to apparent reflectance (Ra) in the red/far-red, spectra were collected on a C4 agricultural species (corn, Zea Mays L.) under conditions ranging from nitrogen deficiency to excess. A significant contribution of ChlF to Ra was observed, with on average 10-25% at 685nm and 2-6% at 740nm of Ra being due to ChlF. Higher ChlF was consistently measured from the abaxial leaf surface as compared to the adaxial. Using 350-665nm excitation, the study confirms the trends in three ChlF ratios established previously by active F technology, suggesting that the ChlF utility this technology has developed for monitoring vegetation physiological status is likely applicable also under natural solar illumination.

Campbell, Petya K. Entcheva↗

Vegetation reflectance features in AVIRIS data

Equations for converting Airborne Visible-IR Imaging Spectrometer (AVIRIS) digital numbers to percent reflectance were developed using a set of three calibration targets. When converted to reflectance the following spectral features of vegetation can be observed in AVIRIS data: details in the pigment absorption region, the red edge, the NIR plateau, leaf water absorptions on the NIR plateau, leaf water absorptions, and lignocellulose absorptions. These results indicate that AVIRIS data will be quite useful in geobotanical remote sensing.

Elvidge, Christopher D.↗

Ultrastructure of potato tubers formed in microgravity under controlled environmental conditions

Previous spaceflight reports attribute changes in plant ultrastructure to microgravity, but it was thought that the changes might result from growth in uncontrolled environments during spaceflight. To test this possibility, potato explants were examined (a leaf, axillary bud, and small stem segment) grown in the ASTROCULTURETM plant growth unit, which provided a controlled environment. During the 16 d flight of space shuttle Columbia (STS-73), the axillary bud of each explant developed into a mature tuber. Upon return to Earth, tuber slices were examined by transmission electron microscopy. Results showed that the cell ultrastructure of flight-grown tubers could not be distinguished from that of tuber cells grown in the same growth unit on the ground. No differences were observed in cellular features such as protein crystals, plastids with starch grains, mitochondria, rough ER, or plasmodesmata. Cell wall structure, including underlying microtubules, was typical of ground-grown plants. Because cell walls of tubers formed in space were not required to provide support against the force due to gravity, it was hypothesized that these walls might exhibit differences in wall components as compared with walls formed in Earth-grown tubers. Wall components were immunolocalized at the TEM level using monoclonal antibodies JIM 5 and JIM 7, which recognize epitopes of pectins, molecules thought to contribute to wall rigidity and cell adhesion. No difference in presence, abundance or distribution of these pectin epitopes was seen between space- and Earth-grown tubers. This evidence indicates that for the parameters studied, microgravity does not affect the cellular structure of plants grown under controlled environmental conditions.

Non-NASA Center↗

Development of the Ames Global Hyperspectral Synthetic Data Set: Surface Bidirectional Reflectance Distribution Function

This study introduces the Ames Global Hyperspectral Synthetic Data set (AGHSD), in particular the surface bidirectional reflectance distribution function (BRDF) product, to support the NASA Surface Biology and Geology (SBG) mission development. The data set is generated based on the corresponding multispectral BRDF products from NASA's MODIS satellite sensor. Based on theories of radiative transfer in vegetation canopies, we derive a simple but robust relationship that indicates that the hyperspectral surface BRDF can be accurately approximated as a weighted sum of the soil surface reflectance, the leaf single albedo, and the canopy scattering coefficient, where the weights or coefficients are spectrally invariant and thus readily estimated from the multispectral MODIS products. We validate the algorithm with simulations by a Monte Carlo Ray Tracing model and find the results highly consistent with the theoretic derivation. Using reflectance spectra of soil and vegetation derived from existing spectral libraries, we apply the algorithm to generate the AGHSD BRDF product at 1 km and 8-day resolutions for the year of 2019. The data set is biogeochemically and biogeophysically coherent and consistent, and serves the goal to support the SBG community in developing sciences and applications for the future global imaging spectroscopy mission.

Hyperspectral Remote Sensing↗