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At least 127 records · Page 7

Spatial scale drives patterns in soil bacterial diversity: Spatial scale drives soil diversity

Soil microbial communities are essential for ecosystem function, but linking community composition to biogeochemical processes is challenging because of high microbial diversity and large spatial variability of most soil characteristics. We investigated soil bacterial community structure in a switchgrass stand planted on soil with a history of grassland vegetation at high spatial resolution to determine whether biogeographic trends occurred at the centimeter scale. Moreover, we tested whether such heterogeneity, if present, influenced community structure within or among ecosystems. Pronounced heterogeneity was observed at centimeter scales, with abrupt changes in relative abundance of phyla from sample to sample. At the ecosystem scale (> 10 m), however, bacterial community composition and structure were subtly, but significantly, altered by fertilization, with higher alpha diversity in fertilized plots. Moreover, by comparing these data with data from 1772 soils from the Earth Microbiome Project, it was found that 20% diverse globally sourced soil samples, while grassland soils shared approximately 40% of their operational taxonomic units with the current study. By spanning several orders of magnitude, the analysis suggested that extreme patchiness characterized community structure at smaller scales but that coherent patterns emerged at larger length scales.

16S rRNA↗

Impact of dose size in single fraction spatially fractionated (grid) radiotherapy for melanoma

Purpose: To evaluate the impact of dose size in single fraction, spatially fractionated (grid) radiotherapy for selectively killing infiltrated melanoma cancer cells of different tumor sizes, using different radiobiological models. Methods: A Monte Carlo technique was employed to calculate the 3D dose distribution of a commercially available megavoltage grid collimator in a 6 MV beam. The linear-quadratic (LQ) and modified linear quadratic (MLQ) models were used separately to evaluate the therapeutic outcome of a series of single fraction regimens that employed grid therapy to treat both acute and late responding melanomas of varying sizes. The dose prescription point was at the center of the tumor volume. Dose sizes ranging from 1 to 30 Gy at 100% dose line were modeled. Tumors were either touching the skin surface or having their centers at a depth of 3 cm. The equivalent uniform dose (EUD) to the melanoma cells and the therapeutic ratio (TR) were defined by comparing grid therapy with the traditional open debulking field. The clinical outcomes from recent reports were used to verify the authors’ model. Results: Dose profiles at different depths and 3D dose distributions in a series of 3D melanomas treated with grid therapy were obtained. The EUDs and TRs for all sizes of 3D tumors involved at different doses were derived through the LQ and MLQ models, and a practical equation was derived. The EUD was only one fifth of the prescribed dose. The TR was dependent on the prescribed dose and on the LQ parameters of both the interspersed cancer and normal tissue cells. The results from the LQ model were consistent with those of the MLQ model. At 20 Gy, the EUD and TR by the LQ model were 2.8% higher and 1% lower than by the MLQ, while at 10 Gy, the EUD and TR as defined by the LQ model were only 1.4% higher and 0.8% lower, respectively. The dose volume histograms of grid therapy for a 10 cm tumor showed different dosimetric characteristics from those of conventional radiotherapy. A significant portion of the tumor volume received a very large dose in grid therapy, which ensures significant tumor cell killing in these regions. Conversely, some areas received a relatively small dose, thereby sparing interspersed normal cells and increasing radiation tolerance. The radiobiology modeling results indicated that grid therapy could be useful for treating acutely responding melanomas infiltrating radiosensitive normal tissues. The theoretical model predictions were supported by the clinical outcomes. Conclusions: Grid therapy functions by selectively killing infiltrating tumor cells and concomitantly sparing interspersed normal cells. The TR depends on the radiosensitivity of the cell population, dose, tumor size, and location. Because the volumes of very high dose regions are small, the LQ model can be used safely to predict the clinical outcomes of grid therapy. When treating melanomas with a dose of 15 Gy or higher, single fraction grid therapy is clearly advantageous for sparing interspersed normal cells. The existence of a threshold fraction dose, which was found in the authors’ theoretical simulations, was confirmed by clinical observations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Real-Time Highly Resolved Spatial-Temporal Vehicle Energy Consumption Estimation Using Machine Learning and Probe Data

Real-time highly resolved spatial-temporal vehicle energy consumption is a key missing dimension in transportation data. Most roadway link-level vehicle energy consumption data are estimated using average annual daily traffic measures derived from the Highway Performance Monitoring System; however, this method does not reflect day-to-day energy consumption fluctuations. As transportation planners and operators are becoming more environmentally attentive, they need accurate real-time link-level vehicle energy consumption data to assess energy and emissions; to incentivize energy-efficient routing; and to estimate energy impact caused by congestion, major events, and severe weather. This paper presents a computational workflow to automate the estimation of time-resolved vehicle energy consumption for each link in a road network of interest using vehicle probe speed and count data in conjunction with machine learning methods in real time. The real-time pipeline can deliver energy estimates within a couple seconds on query to its interface. The proposed method was evaluated on the transportation network of the metropolitan area of Chattanooga, Tennessee. The volume estimation results were validated with ground truth traffic volume data collected in the field. To demonstrate the effectiveness of the proposed method, the energy consumption pipeline was applied to real-world data to quantify road transportation-related energy reduction because of mitigation policies to slow the spread of COVID-19 and to measure energy loss resulting from congestion.

Severino, Joseph↗

Data for Greenhouse Gas Accounting Procedures in Low Carbon Fuel Policies Overlook the Spatial Variability of Miscanthus-Derived Sustainable Aviation Fuel

Low carbon fuel policies such as the U.S. Renewable Fuel Standard (RFS), Canada Clean Fuel Regulations (CFR), and California Low Carbon Fuel Standard (LCFS) as well as the 45Z tax credit are intended to reduce greenhouse gas (GHG) emissions from transportation. Cellulosic feedstocks, optimized biorefineries, and favorable farming locations can significantly reduce biofuel carbon intensity (CI). Despite advances in field-to-fuel GHG monitoring and flexibility in resource allocation within biorefineries (e.g., governing net electricity production), rigid CI accounting procedures in current policies may limit CI responsiveness across candidate sites and processing facilities. This work examines a hypothetical biomass-to-sustainable aviation fuel (SAF) pathway using miscanthus and alcohol-to-jet (i) to demonstrate how GHG accounting requirements drive estimates of biofuel CIs and (ii) to explore potential CI and financial implications of scenario-specific life cycle assessment (LCA). Results demonstrate that GHG accounting using the CFR/LCFS can reasonably account for distinct levels of net electricity production by a biorefinery, but only the CFR yields similar CI sensitivity to spatially explicit factors (feedstock CI, grid electricity CI) as scenario-specific LCA: most GHG accounting frameworks do not capture CI variation across candidate sites in the United States. Ultimately, this work demonstrates the importance of LCA methodological specifications in low carbon fuel policies and tax credits.

Miscanthus↗

Assessing Cloud and Precipitation Properties on Temporal and Spatial Scales Using LASSO Simulations over ENA

Low clouds and precipitation representation remain a major source of uncertainty in Earth System Models (ESMs), particularly due to challenges in representing their sub-grid variability and scale-dependent sampling. This study evaluates the performance of preliminary simulations from the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project over the Eastern North Atlantic (ENA), with a focus on liquid water path (LWP), ice water path (IWP), cloud fraction (CF), and surface precipitation simulated across closed-cell, open-cell, and transitional cloud regimes. Using LES (100 m horizontal grid spacing) driven by ERA5 and MERRA-2 reanalyses, we assess the representativeness of ground-based point observations by analyzing their correspondence to model-resolved spatial and temporal means. Results suggest that observational sampling of at least 6 hours is required to achieve consistency with domain-scale averages, in particular for observations that exhibit pronounced sub-grid heterogeneity, such as precipitation. ERA5-forced simulations exhibit improved spatial coherence and agreement with domain-averaged quantities when compared to MERRA-2 runs, with performance discrepancies largest for convective cloud conditions due to differences in forcing fidelity and temporal resolution. These findings highlight the importance of regime-aware model evaluation strategies and potentially demonstrate how LES can inform observation-model comparison practices and the development of cloud and precipitation parameterizations in ESMs.

Liang, Jiakun [University of Hawai'i at Manoa] (OR↗

A Hubble Space Telescope survey for novae in M87.I. light and color curves, spatial distributions, and the nova rate

The Hubble Space Telescope has imaged the central part of M87 over a 10 week span, leading to the discovery of 32 classical novae (CNe) and nine fainter, likely very slow, and/or symbiotic novae. In this first paper of a series, we present the M87 nova finder charts, and the light and color curves of the novae. We demonstrate that the rise and decline times, and the colors of M87 novae are uncorrelated with each other and with position in the galaxy. The spatial distribution of the M87 novae follows the light of the galaxy, suggesting that novae accreted by M87 during cannibalistic episodes are well-mixed. Conservatively using only the 32 brightest CNe we derive a nova rate for M87: ${363}_{-45}^{+33}$ novae yr –1 . We also derive the luminosity-specific classical nova rate for this galaxy, which is ${7.88}_{-2.6}^{+2.3}\,{\mathrm{yr}}^{-1}/{10}^{10}\,{L}_{\odot }{,}_{K}$. Both rates are 3–4 times higher than those reported for M87 in the past, and similarly higher than those reported for all other galaxies. As a result, we suggest that most previous ground-based surveys for novae in external galaxies, including M87, miss most faint, fast novae, and almost all slow novae near the centers of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Hubble Parameter and Baryon Acoustic Oscillation Measurement Constraints on the Hubble Constant, the Deviation from the Spatially Flat ΛCDM Model, the Deceleration–Acceleration Transition Redshift, and Spatial Curvature

We construct a complete collection of reliable Hubble parameter H(z) data to redshift z ≤ 2.36 and use them with the Gaussian Process approach to determine continuous H(z) functions for various data subsets. From these continuous H(z)'s, summarizing across the data subsets considered, we find H 0 ~ 67 ± 4 km s–1 Mpc–1, more consistent with the recent lower values observed using a variety of techniques. In most data subsets, we see a cosmological deceleration–acceleration transition at 2σ significance, with the data subsets transition redshifts varying over $0.33\lt {z}_{\mathrm{da}}\lt 1.0$ at 1σ significance. We discover that the flat-ΛCDM model is consistent with the H(z) data to a z of 1.5 to 2.0, depending on data subset considered, with 2σ deviations from flat-ΛCDM above this redshift range. Using the continuous H(z) with baryon acoustic oscillation distance-redshift observations, we constrain the current spatial curvature density parameter to be ${{\rm{\Omega }}}_{K0}=-0.03\pm 0.21$, consistent with a flat universe, but the large error bar does not rule out small values of spatial curvature that are now under debate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Analysis of spatial inhomogeneities in cumulus clouds using high spatial resolution Landsat data

Aircraft observations and high resolution Landsat MSS digital data are used to determine the sizes of spatial inhomogeneities ('holes') in cumulus clouds. The majority of holes are found near cloud edges, but the larger holes tend to be found in cloud interiors. Aircraft measurements show these cloud spatial inhomogeneities in the range of 100 to 500 m, while Landsat data show them in the range of 100 m to 3 km. The number of holes per cloud decreases exponentially with increasing hole diameter. Small clouds not only have smaller holes, but also fewer holes than large clouds. Large clouds have large holes in them, as well as large numbers of the smaller holes. The total cloud area occupied by holes increases with increasing cloud size.

Parker, Lindsay↗

Radiometric and Spatial Characterization of High-Spatial Resolution Sensors

The development and improvement of commercial hyperspatial sensors in recent years has increased the breadth of information that can be retrieved from spaceborne and airborne imagery. NASA, through it's Scientific Data Purchases, has successfully provided such data sets to its user community. A key element to the usefulness of these data are an understanding of the radiometric and spatial response quality of the imagery. This proposal seeks funding to examine the absolute radiometric calibration of the Ikonos sensor operated by Space Imaging and the recently-launched Quickbird sensor from DigitalGlobe. In addition, we propose to evaluate the spatial response of the two sensors. The proposed methods rely on well-understood, ground-based targets that have been used by the University of Arizona for more than a decade.

Thome, Kurtis↗

Land Cover Change Analysis and Spatial Variations in Southeast Asian Nations: Insights on Spatial Scale Dynamics

Land cover type is a fundamental aspect of studies using remote sensing for environmental analysis such as monitoring deforestation, quantifying wildland fire emissions, and more. There are many land cover products available for varying time periods and spatial resolutions, each with different land cover class definitions and number of land cover classes. These differences yield inherent variation in land cover estimates. In this study, we explore the spatial and areal variation between two major datasets for their commonly available time of 2018 to 2022 (MODIS 500m Land Cover and Esri Sentinel-2 10m land cover) in the continental Southeast Asia countries of Cambodia, Laos, Myanmar, Thailand, and Vietnam. To enable comparison, we resampled the datasets and reclassified the land cover classes to a common scheme. Major disagreement was detected between Esri and MODIS, especially for the wetlands/flooded vegetation class in which only 3.6% of pixels were in agreement. In addition to quantifying variation between the datasets, we quantify land cover change at the decadal scale of 2001, 2011, and 2021 for each country and identified province-level hotspots of land cover change. Cambodia experienced the highest rate of land cover change with 67.8% of total land area changed, followed by Vietnam (58.6%), Laos (50.2%), Myanmar (46.9%), and Thailand (46.3%). The highest rate of land cover change was detected in Odtar Mean Chey, Cambodia, which had large swaths of forest area cleared for agricultural production, river damming, and more. Ultimately, many areas in the region experienced forest clearing for crop production (i.e. rice) which appeared to be classified as wetland in the MODIS product, and crop in the Esri product. Myanmar was the only country which did not experience net decline in forest area over the 2001 to 2021 time period.

Land Cover Change↗

Spatial distribution of crystalline corrosion products formed during corrosion of stainless steel in concrete

The mineralogy and spatial distribution of nano-crystalline corrosion products that form in the steel/concrete interface were characterized using synchrotron X-ray micro-diffraction (μ-XRD). Two types of low-nickel high-chromium reinforcing steels embedded into mortar and exposed to NaCl solution were investigated. Corrosion in the samples was confirmed by electrochemical impedance spectroscopy (EIS). μ-XRD revealed that goethite (α-FeOOH) and akaganeite (β-FeOOH) are the main iron oxide–hydroxides formed during the chloride-induced corrosion of stainless steel in concrete. Goethite is formed closer to the surface of the steel due to the presence of chromium in the steel, while akaganeite is formed further away from the surface due to the presence of chloride ions. Detailed microstructural analysis is shown and discussed on one sample of each type of steel. - Highlights: • Synchrotron micro-diffraction used to map the distribution of crystalline phases. • Goethite and akaganeite are the main corrosion products during chloride induced corrosion in mortar. • Layers of goethite and akaganeite are negatively correlated. • EDS showed Cr present in corrosion products identified by SEM.

36 MATERIALS SCIENCE↗

Spatial variation in soil microbial processes as a result of woody encroachment depends on shrub size in tallgrass prairie

Aims: As woody plants encroach into grassland ecosystems, we expect that altered plant-soil interactions will lead to changes in the microbial processes that affect carbon storage and nutrient cycling. Specifically, this research aimed to address how (1) soil chemistry, (2) microbial nutrient demand, and (3) the rate and source of potential soil C mineralization vary spatially under individual woody shrubs of varying size within a mesic grassland. Methods: Here, we collected soil samples from the center, the midpoint between the center and edge, the edge, and the shrub-grass ecotone of multiple Cornus drummondii shrubs across a shrub-size gradient in infrequently burned tallgrass prairie. Results: We found total soil carbon and total soil nitrogen increased with shrub size in every location but the edge. Microbial demand for nitrogen also increased as shrubs increased in size. Across all shrub sizes and sampling locations, potential soil carbon mineralization rates were higher when microbes broke down proportionally more shrub-derived (C 3 ) organic matter than grass-derived (C 4 ) organic matter. Conclusions: Our results suggest that the spatio-temporal context of woody encroachment is critical for understanding its impact on belowground microbial processes. In this ecosystem, a longer period of occupancy by woody plants increases potentially mineralizable carbon.

59 BASIC BIOLOGICAL SCIENCES↗