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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Soil Microbes Trade-Off Biogeochemical Cycling for Stress Tolerance Traits in Response to Year-Round Climate Change

Winter air temperatures are rising faster than summer air temperatures in high-latitude forests, increasing the frequency of soil freeze/thaw events in winter. To determine how climate warming and soil freeze/thaw cycles affect soil microbial communities and the ecosystem processes they drive, we leveraged the Climate Change across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest in the northeastern United States, where replicate field plots receive one of three climate treatments: warming (+5°C above ambient in the growing season), warming in the growing season + winter freeze/thaw cycles (+5°C above ambient +4 freeze/thaw cycles during winter), and no treatment. Soil samples were taken from plots at six time points throughout the growing season and subjected to amplicon (rDNA) and metagenome sequencing. We found that soil fungal and bacterial community composition were affected by changes in soil temperature, where the taxonomic composition of microbial communities shifted more with the combination of growing-season warming and increased frequency of soil freeze/thaw cycles in winter than with warming alone. Warming increased the relative abundance of brown rot fungi and plant pathogens but decreased that of arbuscular mycorrhizal fungi, all of which recovered under combined growing-season warming and soil freeze/thaw cycles in winter. The abundance of animal parasites increased significantly under combined warming and freeze/thaw cycles. We also found that warming and soil freeze/thaw cycles suppressed bacterial taxa with the genetic potential for carbon (i.e., cellulose) decomposition and soil nitrogen cycling, such as N fixation and the final steps of denitrification. These new soil communities had higher genetic capacity for stress tolerance and lower genetic capacity to grow or reproduce, relative to the communities exposed to warming in the growing season alone. Our observations suggest that initial suppression of biogeochemical cycling with year-round climate change may be linked to the emergence of taxa that trade-off growth for stress tolerance traits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Resistance, Resilience, and Recovery of Dryland Soil Bacterial Communities Across Multiple Disturbances

Dryland ecosystems are sensitive to perturbations and generally slow to recover post disturbance. The microorganisms residing in dryland soils are especially important as they contribute to soil structure and nutrient cycling. Disturbance can have particularly strong effects on dryland soil structure and function, yet the natural resistance and recovery of the microbial components of dryland soils has not been well documented. In this study, the recovery of surface soil bacterial communities from multiple physical and environmental disturbances is assessed. Samples were collected from three field sites in the vicinity of Moab, UT, United States, 6 to 7 years after physical and climate disturbance manipulations had been terminated, allowing for the assessment of community recovery. Additionally, samples were collected in a transect that included three habitat patches: the canopy zone soils under the dominant shrubs, the interspace soils that are colonized by biological soil crusts, and edge soils at the plot borders. Field site and habitat patch were significant factors structuring the bacterial communities, illustrating that sites and habitats harbored unique soil microbiomes. Across the different sites and disturbance treatments, there was evidence of significant bacterial community recovery, as bacterial biomass and diversity were not significantly different than control plots. There was, however, a small number of 16S rRNA gene amplicon sequence variants that distinguished particular treatments, suggesting that legacy effects of the disturbances still remained. Taken together, these data suggest that dryland bacterial communities may possess a previously unappreciated potential to recover within years of the original disturbance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fine-scale evaluation of two standard 16S rRNA gene amplicon primer pairs for analysis of total prokaryotes and archaeal nitrifiers in differently managed soils

The advance of high-throughput molecular biology tools allows in-depth profiling of microbial communities in soils, which possess a high diversity of prokaryotic microorganisms. Amplicon-based sequencing of 16S rRNA genes is the most common approach to studying the richness and composition of soil prokaryotes. To reliably detect different taxonomic lineages of microorganisms in a single soil sample, an adequate pipeline including DNA isolation, primer selection, PCR amplification, library preparation, DNA sequencing, and bioinformatic post-processing is required. Besides DNA sequencing quality and depth, the selection of PCR primers and PCR amplification reactions arguably have the largest influence on the results. This study tested the performance and potential bias of two primer pairs, i.e., 515F (Parada)-806R (Apprill) and 515F (Parada)-926R (Quince) in the standard pipelines of 16S rRNA gene Illumina amplicon sequencing protocol developed by the Earth Microbiome Project (EMP), against shotgun metagenome-based 16S rRNA gene reads. The evaluation was conducted using five differently managed soils. We observed a higher richness of soil total prokaryotes by using reverse primer 806R compared to 926R, contradicting to in silico evaluation results. Both primer pairs revealed various degrees of taxon-specific bias compared to metagenome-derived 16S rRNA gene reads. Nonetheless, we found consistent patterns of microbial community variation associated with different land uses, irrespective of primers used. Total microbial communities, as well as ammonia oxidizing archaea (AOA), the predominant ammonia oxidizers in these soils, shifted along with increased soil pH due to agricultural management. In the unmanaged low pH plot abundance of AOA was dominated by the acid-tolerant NS-Gamma clade, whereas limed agricultural plots were dominated by neutral-alkaliphilic NS-Delta/NS-Alpha clades. This study stresses how primer selection influences community composition and highlights the importance of primer selection for comparative and integrative studies, and that conclusions must be drawn with caution if data from different sequencing pipelines are to be compared.

16S rRNA gene amplicon Illumina sequencing↗
DOE OSTI2018

Elucidating Sorghum Biomass, Nitrogen and Chlorophyll Contents With Spectral and Morphological Traits Derived From Unmanned Aircraft System

Unmanned aircraft systems (UAS) provide an efficient way to phenotype crop morphology with spectral traits such as plant height, canopy cover and various vegetation indices (VIs) providing information to elucidate genotypic responses to the environment. In this study, we investigated the potential use of UAS-derived traits to elucidate biomass, nitrogen and chlorophyll content in sorghum under nitrogen stress treatments. A nitrogen stress trial located in Nebraska, USA, contained 24 different sorghum lines, 2 nitrogen treatments and 8 replications, for a total of 384 plots. Morphological and spectral traits including plant height, canopy cover and various VIs were derived from UAS flights with a true-color RGB camera and a 5-band multispectral camera at early, mid and late growth stages across the sorghum growing season in 2017. Simple and multiple regression models were investigated for sorghum biomass, nitrogen and chlorophyll content estimations using the derived morphological and spectral traits along with manual ground truthed measurements. Results showed that, the UAS-derived plant height was strongly correlated with manually measured plant height (r = 0.85); and the UAS-derived biomass using plant height, canopy cover and VIs had strong exponential correlations with the sampled biomass of fresh stalks and leaves (maximum r = 0.85) and the biomass of dry stalks and leaves (maximum r = 0.88). The UAS-derived VIs were moderately correlated with the laboratory measured leaf nitrogen content (r = 0.52) and the measured leaf chlorophyll content (r = 0.69) in each plot. The methods developed in this study will facilitate genetic improvement and agronomic studies that require assessment of stress responses in large-scale field trials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Comparative transcriptomic and phenotypic analysis of monoclonal and polyclonal Populus deltoides genotypes

Populus species are highly valued for bioenergy and bioproducts due to their rapid growth and productivity. Polyclonal plantings, or mixtures of Populus clones, have shown the potential to enhance resource utilization and productivity, likely due to phenotypic differences arising from niche differentiation. In this study, we investigated gene expression and productivity in monoclonal and polyclonal stands of P. deltoides . Phenotypic results showed that polyclonal plots exhibited higher leaf area index (LAI; p < 0.01, 2.96 ± 0.057 m 2 ) and total biomass (p < 0.01, 2.74 ± 0.06) compared to monoclonal plots, indicating superior productivity. RNA sequencing revealed upregulation of key genes such as exocyst subunit exo70 family protein H7 (EXO70H7), NDH-dependent cyclic electron flow 5 (NDF5) , and expansin-like A3 (EXLA3) . We also observed enrichment in phenylalanine metabolism and other secondary metabolic pathways in clone S7C8. Phenotypic results, upregulated genes and enriched biological pathways identified in this study may explain the enhanced productivity, increased nitrate content, and expanded canopy in polyclonal plantings. Overall, this study provides a foundation for future research to enhance forest productivity by linking molecular mechanisms to practical applications in field plantings.

differential gene expression↗
DOE OSTI2022

Comparing Deep Learning Approaches for Understanding Genotype × Phenotype Interactions in Biomass Sorghum

We explore the use of deep convolutional neural networks (CNNs) trained on overhead imagery of biomass sorghum to ascertain the relationship between single nucleotide polymorphisms (SNPs), or groups of related SNPs, and the phenotypes they control. We consider both CNNs trained explicitly on the classification task of predicting whether an image shows a plant with a reference or alternate version of various SNPs as well as CNNs trained to create data-driven features based on learning features so that images from the same plot are more similar than images from different plots, and then using the features this network learns for genetic marker classification. We characterize how efficient both approaches are at predicting the presence or absence of a genetic markers, and visualize what parts of the images are most important for those predictions. We find that the data-driven approaches give somewhat higher prediction performance, but have visualizations that are harder to interpret; and we give suggestions of potential future machine learning research and discuss the possibilities of using this approach to uncover unknown genotype × phenotype relationships.

Zhang, Zeyu↗
DOE OSTI2025

High-shade dryland agrivoltaic conditions enhanced carbon uptake and water-use efficiency in zucchini ( Cucurbita pepo )

Introduction: The increasing global demand for food and energy is intensifying land-use competition. Agrivoltaic systems are a multifunctional land-use approach that vertically integrates the production of agricultural crops and solar power on the same land area. Most food crops are adapted to full-sun conditions, and the physiological responses of these crops to the novel microclimate under solar panels remain poorly understood. We hypothesized that the microclimate beneath the high-density photovoltaic system would influence carbon uptake, water use, and yield outcomes of zucchini summer squash.Methods: We conducted a field experiment in a hot, semi-arid climate on zucchini (Cucurbita pepo). Plants were grown under an agrivoltaic system with a 75% ground cover ratio (GCR) and in a full-sun control plot, each with two irrigation regimes (100 and 50%). We measured leaf-level photosynthesis, microclimate variables, and fruit yield at plant maturity and throughout the growing season.Results: The agrivoltaic array reduced photosynthetically active radiation (PAR) by ~79%, resulting in a cooler (−1.1 °C), more humid environment with higher soil moisture. These microclimatic conditions enhanced midday photosynthesis and daily cumulative carbon uptake. However, fruit yield was consistently lower under the panels, indicating a shift in carbon allocation toward vegetative growth. Photosynthesis was primarily driven by PAR across treatments, while soil moisture significantly influenced photosynthesis only in the control plots, suggesting water limitation was alleviated under the panels.Discussion: These findings highlight a trade-off between improved physiological performance and reduced yield under high-density agrivoltaics. While the system buffered heat and drought stress and improved overall plant function, excessive shade reduced reproductive output. Optimizing panel density or selecting crops cultivated for non-fruit yields will be essential for balancing food production and energy generation in dryland agrivoltaic settings.

14 SOLAR ENERGY↗
DOE OSTI2019

Biomass Grinding Process Optimization Using Response Surface Methodology and a Hybrid Genetic Algorithm

Biomass could be a key source of renewable energy. Agricultural waste products, such as corn stover, provide a convenient means to replace fossil fuels, such as coal, and a large amount of feedstock is currently available for energy consumption in the U.S. This study has two main objectives: (1) to understand the impact of corn stover moisture content and grinder speed on grind physical properties; and (2) develop response surface models and optimize these models using a hybrid genetic algorithm. The response surface models developed were used to draw surface plots to understand the interaction effects of the corn stover grind moisture content and grinder speed on the grind physical properties and specific energy consumption. The surface plots indicated that a higher corn stover grind moisture content and grinder speed had a positive effect on the bulk and tapped density. The final grind moisture content was highly influenced by the initial moisture content of the corn stover grind. Optimization of the response surface models using the hybrid genetic algorithm indicated that moisture content in the range of 17 to 19% (w.b.) and a grinder speed of 47 to 49 Hz maximized the bulk and tapped density and minimized the geomantic mean particle length. The specific energy consumption was minimized when the grinder speed was about 20 Hz and the corn stover grind moisture content was about 10% (w.b.).

09 BIOMASS FUELS↗
DOE OSTI2021

Tafel Slope Analyses for Homogeneous Catalytic Reactions

Tafel analysis of electrocatalysts is essential in their characterization. This paper analyzes the application of Tafel-like analysis to the four-electron nonelectrochemical oxidation of water by the stoichiometric homogeneous 1-electron oxidant [Ru(bpy)3]3+ to dioxygen catalyzed by homogeneous catalysts, [Ru4O4(OH)2(H2O)4(γ-SiW10O36)2]10− (Ru4POM) and [Co4(H2O)2(PW9O34)2]10– (Co4POM). These complexes have slow electron exchange rates with electrodes due to the Frumkin effect, which precludes the use of known electrochemical methods to obtain Tafel plots at ionic strengths lower than 0.5 M. The application of an electron transfer catalyst, [Ru(bpy)3]3+/2+, increases the rates between the Ru4POM and electrode, but a traditional Tafel analysis of such a complex system is precluded due to a lack of appropriate theoretical models for 4-electron processes. Here, we develop a theoretical framework and experimental procedures for a Tafel-like analysis of Ru4POM and Co4POM, using a stoichiometric molecular oxidant [Ru(bpy)3]3+. The dependence of turnover frequency (TOF) as a function of electrochemical solution potential created by the [Ru(bpy)3]3+/[Ru(bpy)3]2+ redox couple (an analog of the Tafel plot) was obtained from kinetics data and interpreted based on the suggested reaction mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Probabilistic Assessment and Uncertainty Analysis of CO2 Storage Capacity of the Morrow B Sandstone—Farnsworth Field Unit

This paper presents probabilistic methods to estimate the quantity of carbon dioxide (CO2) that can be stored in a mature oil reservoir and analyzes the uncertainties associated with the estimation. This work uses data from the Farnsworth Field Unit (FWU), Ochiltree County, Texas, which is currently undergoing a tertiary recovery process. The input parameters are determined from seismic, core, and fluid analyses. The results of the estimation of the CO2 storage capacity of the reservoir are presented with both expectation curve and log probability plot. The expectation curve provides a range of possible outcomes such as the P90, P50, and P10. The deterministic value is calculated as the statistical mean of the storage capacity. The coefficient of variation and the uncertainty index, P10/P90, is used to analyze the overall uncertainty of the estimations. A relative impact plot is developed to analyze the sensitivity of the input parameters towards the total uncertainty and compared with Monte Carlo. In comparison to the Monte Carlo method, the results are practically the same. The probabilistic technique presented in this paper can be applied in different geological settings as well as other engineering applications.

03 NATURAL GAS↗
DOE OSTI2021

Thresholding Analysis and Feature Extraction from 3D Ground Penetrating Radar Data for Noninvasive Assessment of Peanut Yield

This study explores the efficacy of utilizing a novel ground penetrating radar (GPR) acquisition platform and data analysis methods to quantify peanut yield for breeding selection, agronomic research, and producer management and harvest applications. Sixty plots comprising different peanut market types were scanned with a multichannel, air-launched GPR antenna. Image thresholding analysis was performed on 3D GPR data from four of the channels to extract features that were correlated to peanut yield with the objective of developing a noninvasive high-throughput peanut phenotyping and yield-monitoring methodology. Plot-level GPR data were summarized using mean, standard deviation, sum, and the number of nonzero values (counts) below or above different percentile threshold values. Best results were obtained for data below the percentile threshold for mean, standard deviation and sum. Data both below and above the percentile threshold generated good correlations for count. Correlating individual GPR features to yield generated correlations of up to 39% explained variability, while combining GPR features in multiple linear regression models generated up to 51% explained variability. The correlations increased when regression models were developed separately for each peanut type. This research demonstrates that a systematic search of thresholding range, analysis window size, and data summary statistics is necessary for successful application of this type of analysis. The results also establish that thresholding analysis of GPR data is an appropriate methodology for noninvasive assessment of peanut yield, which could be further developed for high-throughput phenotyping and yield-monitoring, adding a new sensor and new capabilities to the growing set of digital agriculture technologies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Sensitivity of Optical Satellites to Estimate Windthrow Tree-Mortality in a Central Amazon Forest

Windthrow (i.e., trees broken and uprooted by wind) is a major natural disturbance in Amazon forests. Images from medium-resolution optical satellites combined with extensive field data have allowed researchers to assess patterns of windthrow tree-mortality and to monitor forest recovery over decades of succession in different regions. Although satellites with high spatial-resolution have become available in the last decade, they have not yet been employed for the quantification of windthrow tree-mortality. Here, we address how increasing the spatial resolution of satellites affects plot-to-landscape estimates of windthrow tree-mortality. We combined forest inventory data with Landsat 8 (30 m pixel), Sentinel 2 (10 m), and WorldView 2 (2 m) imagery over an old-growth forest in the Central Amazon that was disturbed by a single windthrow event in November 2015. Remote sensing estimates of windthrow tree-mortality were produced from Spectral Mixture Analysis and evaluated with forest inventory data (i.e., ground true) by using Generalized Linear Models. Field measured windthrow tree-mortality (3 transects and 30 subplots) crossing the entire disturbance gradient was 26.9 ± 11.1% (mean ± 95% CI). Although the three satellites produced reliable and statistically similar estimates (from 26.5% to 30.3%, p < 0.001), Landsat 8 had the most accurate results and efficiently captured field-observed variations in windthrow tree-mortality across the entire gradient of disturbance (Sentinel 2 and WorldView 2 produced the second and third best results, respectively). As expected, mean-associated uncertainties decreased systematically with increasing spatial resolution (i.e., from Landsat 8 to Sentinel 2 and WorldView 2). However, the overall quality of model fits showed the opposite pattern. We suggest that this reflects the influence of a relatively minor disturbance, such as defoliation and crown damage, and the fast growth of natural regeneration, which were not measured in the field nor can be captured by coarser resolution imagery. Our results validate the reliability of Landsat imagery for assessing plot-to-landscape patterns of windthrow tree-mortality in dense and heterogeneous tropical forests. Satellites with high spatial resolution can improve estimates of windthrow severity by allowing the quantification of crown damage and mortality of lower canopy and understory trees. However, this requires the validation of remote sensing metrics using field data at compatible scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Data and Code for Atomic Scale Etching of Diamond: Insights from Molecular Dynamics Simulations

This work investigates the effects of argon ions, hydrogen atoms, and hydrogen ions on the diamond (100) surface using classical molecular dynamics simulations. The purpose of this investigation was to asses plasma processing techniques for applications in quantum device manufacturing. The simulations suggest that combining argon ion smoothing with selective, near threshold energy H removal of amorphous C could be an effective strategy for diamond surface engineering, leading to more reliable and sensitive diamond color center devices. Results were found to differ significantly with interatomic potential, and an analysis of these differences was also carried out. Included in this repository are LAMMPS source files, input scripts, and plotting scripts required to reproduce the data. Also included are the output data required to make all the plots included in the associated publication.

Brenner↗
DOE OSTI2016

ROTATION AND GRANULATION OF THE K2 GIANT α SER

The red giant α Ser was observed over 10 seasons, 2001–2010, at the Elginfield Observatory with the high-resolution coudé spectrograph. Season-mean radial velocities appear to show a small secular rise ∼11 ± 3 m s{sup 1} yr{sup 1}. The absolute spectroscopic radial velocity with convective blueshifts taken into account is 2730 m s{sup 1}. Ten line-depth ratios were investigated and show that the star's temperature is constant with any secular variation below 1.3 ± 1.0 K over the 11 years of observation. Fourier analysis of the line broadening yields v sin i = 2.0 ± 0.3 km s{sup 1} and a radial-tangential macroturbulence dispersion ζ {sub RT} = 4.50 ± 0.10 km s{sup 1}. The third-granulation-signature plot shows that the granulation velocities of α Ser are only 0.55 ± 0.10 as large as the Sun's. The line bisector of Fe i λ 6253 has the usual “C” shape and when mapped onto the third-signature plot results in a flux deficit that is slightly broader than seen in other measured K giants. The deficit fractional area of 12.3 ± 1.5% suggests a temperature difference between granules and lanes of 105 K as seen averaged over the stellar disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

A Spectroscopic Analysis of the Hyades Cool Giants

High-resolution spectroscopic observations of the four cool giants in the Hyades cluster, taken at the Elginfield Observatory, are analyzed. The velocity of γ Tau between 2002 and 2009 is constant to a few m s{sup −1}; small variations, compatible with the planetary orbit, are seen for ε Tau. The primary-to-secondary mass ratio of θ {sup 1} Tau is found to be 2.33 ± 0.07. Absolute radial velocities are determined for three of the giants from third-signature plots that correct for granulation blueshifts: 38,615 ± 50, 38,760 ± 100, and 38,570 ± 50 m s{sup −1} for γ Tau, δ Tau, and ε Tau respectively. Line–depth ratios show that γ Tau is 33 ± 5 K, δ Tau is 53 ± 10 K, and θ {sup 1} Tau is 30 ± 6 K hotter than ε Tau. Although the λ6253 line bisectors are similar for all four giants, there are significant differences in the line profiles. Fourier analysis of the profile shapes yields projected rotation rates of 2.1, 2.4, 2.8, and 2.8 km s{sup −1} for γ Tau, δ Tau, ε Tau, and θ {sup 1} Tau respectively, with an uncertainty of ±0.3 km s{sup −1}. The corresponding radial–tangential macroturbulence dispersions are 5.07, 5.66, 5.55, and 4.65 km s{sup −1}, with a uncertainty of ±0.10 km s{sup −1}. Scale factors for third-signature plots are close to unity, ±10%, implying that the granulation velocity gradient through their photospheres is similar to the Sun's. Bisector mapping returns flux differences between granules and lanes, with average granule-to-lane temperature differences ∼125 K.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

An alternative to the Λcdm model: the case of scale invariance

The hypothesis is made that, at large scales where general relativity may be applied, empty space is scale invariant. This establishes a relation between the cosmological constant and the scale factor λ of the scale-invariant framework. This relation brings major simplifications in the scale-invariant equations for cosmology, which contain a new term, depending on the derivative of the scale factor, that opposes gravity and produces an accelerated expansion. The displacements due to the acceleration term make a high contribution Ω{sub λ} to the energy density of the universe, satisfying an equation of the form Ω{sub m}+Ω{sub k}+Ω{sub λ}=1. The models do not demand the existence of unknown particles. There is a family of flat models with different density parameters Ω{sub m}<1. Numerical integrations of the cosmological equations for different values of the curvature and density parameter k and Ω{sub m} are performed. The presence of even tiny amounts of matter in the universe tends to kill scale invariance. The point is that for Ω{sub m}=0.3 the effect is not yet completely killed. Models with non-zero density start explosively with a braking phase followed by a continuously accelerating expansion. Several observational properties are examined, in particular the distances, the m–z diagram, and the Ω{sub m} versus Ω{sub λ} plot. Comparisons with observations are also performed for the Hubble constant H{sub 0} versus Ω{sub m}, for the expansion history in the plot H(z)/(z+1) versus redshift z, and for the transition redshift from braking to acceleration. These first dynamical tests are satisfied by scale-invariant models, which thus deserve further study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Formation and fractionation of CO (carbon monoxide) in diffuse clouds observed at optical and radio wavelengths

We modeled H{sub 2} and CO formation incorporating the fractionation and selective photodissociation affecting CO when A{sub V} ≲ 2 mag. UV absorption measurements typically have N({sup 12}CO)/N({sup 13}CO) ≈ 65 that are reproduced with the standard UV radiation and little density dependence at n(H) ≈ 32–1024 cm{sup −3}: densities n(H) ≲ 256 cm{sup −3} avoid overproducing CO. Sightlines observed in millimeter wave absorption and a few in UV show enhanced {sup 13}CO by factors of two to four and are explained by higher n(H) ≳ 256 cm{sup −3} and/or weaker radiation. The most difficult observations to understand are UV absorptions having N({sup 12}CO)/N({sup 13}CO) > 100 and N(CO) ≳ 10{sup 15} cm{sup −2}. Plots of W{sub CO} versus N(CO) show that W{sub CO} remains linearly proportional to N(CO) even at high opacity owing to sub-thermal excitation. {sup 12}CO and {sup 13}CO have nearly the same curve of growth so their ratios of column density/integrated intensity are comparable even when different from the isotopic abundance ratio. For n(H) ≳ 128 cm{sup −3}, plots of W{sub CO} versus N(CO) are insensitive to n(H), and W{sub CO}/N(CO) ≈ 1 K km s{sup −1}/(10{sup 15} CO cm{sup −2}); this compensates for small CO/H{sub 2} to make W{sub CO} more readily detectable. Rapid increases of N(CO) with n(H), N(H), and N(H{sub 2}) often render the CO bright, i.e., a small CO-H{sub 2} conversion factor. For n(H) ≲ 64 cm{sup −3}, CO enters the regime of truly weak excitation, where W{sub CO} ∝ n(H)N(CO). W{sub CO} is a strong function of the average H{sub 2} fraction and models with W{sub CO} = 1 K km s{sup −1} fall in the narrow range of 〈f{sub H{sub 2}}〉 0.65–0.8 or 〈f{sub H{sub 2}}〉 0.4–0.5 at W{sub CO} 0.1 K km s{sup −1}. The insensitivity of easily detected CO emission to gas with small 〈f{sub H{sub 2}}〉 implies that even deep CO surveys using broad beams may not discover substantially more emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Long-slit Spectroscopy of Edge-on Low Surface Brightness Galaxies

We present long-slit optical spectra of 12 edge-on low surface brightness galaxies (LSBGs) positioned along their major axes. After performing reddening corrections for the emission-line fluxes measured from the extracted integrated spectra, we measured the gas-phase metallicities of our LSBG sample using both the [N ii]/H α and the R {sub 23} diagnostics. Both sets of oxygen abundances show good agreement with each other, giving a median value of 12 + log(O/H) = 8.26 dex. In the luminosity–metallicity plot, our LSBG sample is consistent with the behavior of normal galaxies. In the mass–metallicity diagram, our LSBG sample has lower metallicities for lower stellar mass, similar to normal galaxies. The stellar masses estimated from z -band luminosities are comparable to those of prominent spirals. In a plot of the gas mass fraction versus metallicity, our LSBG sample generally agrees with other samples in the high gas mass fraction space. Additionally, we have studied stellar populations of three LSBGs, which have relatively reliable spectral continua and high signal-to-noise ratios, and qualitatively conclude that they have a potential dearth of stars with ages <1 Gyr instead of being dominated by stellar populations with ages >1 Gyr. Regarding the chemical evolution of our sample, the LSBG data appear to allow for up to 30% metal loss, but we cannot completely rule out the closed-box model. Additionally, we find evidence that our galaxies retain up to about three times as much of their metals compared with dwarfs, consistent with metal retention being related to galaxy mass. In conclusion, our data support the view that LSBGs are probably just normal disk galaxies continuously extending to the low end of surface brightness.

79 ASTRONOMY AND ASTROPHYSICS↗