339 research outputs found

    Nonequilibrium clumped isotope signals in microbial methane

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    Methane is a key component in the global carbon cycle with a wide range of anthropogenic and natural sources. Although isotopic compositions of methane have traditionally aided source identification, the abundance of its multiply-substituted “clumped” isotopologues, e.g., 13CH3D, has recently emerged as a proxy for determining methane-formation temperatures; however, the impact of biological processes on methane’s clumped isotopologue signature is poorly constrained. We show that methanogenesis proceeding at relatively high rates in cattle, surface environments, and laboratory cultures exerts kinetic control on 13CH3D abundances and results in anomalously elevated formation temperature estimates. We demonstrate quantitatively that H2 availability accounts for this effect. Clumped methane thermometry can therefore provide constraints on the generation of methane in diverse settings, including continental serpentinization sites and ancient, deep groundwaters.National Science Foundation (U.S.) (EAR-1250394)National Science Foundation (U.S.) (EAR-1322805)Deep Carbon Observatory (Program)Natural Sciences and Engineering Research Council of CanadaDeutsche Forschungsgemeinschaft (Gottfried Wilhelm Leibniz Program)United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship)Neil & Anna Rasmussen FoundationGrayce B. Kerr Fund, Inc. (Fellowship)MIT Energy Initiative (Shell-MITEI Graduate Fellowship)Shell International Exploration and Production B.V. (N. Braunsdorf and D. Smit of Shell PTI/EG grant

    Photometric IGM tomography with Subaru/HSC: the large-scale structure of Lyα emitters and IGM transmission in the COSMOS field at z ∼ 5

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    We present a novel technique called “photometric IGM tomography” to map the intergalactic medium (IGM) at z ≃ 4.9 in the COSMOS field. It utilizes deep narrow-band (NB) imaging to photometrically detect faint Lyα forest transmission in background galaxies across the Subaru/Hyper-Suprime Cam (HSC)’s 1.8sq.deg field of view and locate Lyα emitters (LAEs) in the same cosmic volume. Using ultra-deep HSC images and Bayesian spectral energy distribution fitting, we measure the Lyα forest transmission at z ≃ 4.9 along a large number (140) of background galaxies selected from the DEIMOS10k spectroscopic catalogue at 4.98 < z < 5.89 and the SILVERRUSH LAEs at z ≃ 5.7. We photometrically measure the mean Lyα forest transmission and achieve a result consistent with previous measurements based on quasar spectra. We also measure the angular LAE-Lyα forest cross-correlation and Lyα forest auto-correlation functions and place an observational constraint on the large-scale fluctuations of the IGM around LAEs at z ≃ 4.9. Finally, we present the reconstructed 2D tomographic map of the IGM, co-spatial with the large-scale structure of LAEs, at a transverse resolution of 11h−1cMpc across 140h−1cMpc in the COSMOS field at z ≃ 4.9. We discuss the observational requirements and the potential applications of this new technique for understanding the sources of reionization, quasar radiative history, and galaxy-IGM correlations across z ∼ 3 − 6. Our results represent the first proof-of-concept of photometric IGM tomography, offering a new route to examining early galaxy evolution in the context of the large-scale cosmic web from the epoch of reionization to cosmic noon

    The Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) Survey Design, Reductions, and Detections

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    We describe the survey design, calibration, commissioning, and emission-line detection algorithms for the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX is to measure the redshifts of over a million Lyα emitting galaxies between 1.88 < z < 3.52, in a 540 deg2 area encompassing a comoving volume of 10.9 Gpc3. No preselection of targets is involved; instead the HETDEX measurements are accomplished via a spectroscopic survey using a suite of wide-field integral field units distributed over the focal plane of the telescope. This survey measures the Hubble expansion parameter and angular diameter distance, with a final expected accuracy of better than 1%. We detail the project’s observational strategy, reduction pipeline, source detection, and catalog generation, and present initial results for science verification in the Cosmological Evolution Survey, Extended Groth Strip, and Great Observatories Origins Deep Survey North fields. We demonstrate that our data reach the required specifications in throughput, astrometric accuracy, flux limit, and object detection, with the end products being a catalog of emission-line sources, their object classifications, and flux-calibrated spectra

    The Role of Galaxies and AGN in Reionising the IGM - I: Keck Spectroscopy of 5 < z < 7 Galaxies in the QSO Field J1148+5251

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    We introduce a new method for determining the influence of galaxies and active galactic nuclei (AGN) on the physical state of the intergalactic medium (IGM) at high redshift and illustrate its potential via a first application to the field of the z=6.42z=6.42 QSO J1148+5251. By correlating the spatial positions of spectroscopically-confirmed Lyman break galaxies (LBGs) with fluctuations in the Lyman alpha forest seen in the high signal-to-noise spectrum of a background QSO, we provide a statistical measure of the typical escape fraction of Lyman continuum photons close to the end of cosmic reionisation. Here we use Keck DEIMOS spectroscopy to locate 7 colour-selected LBGs in the redshift range 5.3z6.45.3\lesssim z\lesssim 6.4 and confirm a faint z=5.701z=5.701 AGN. We then examine the spatial correlation between this sample and Lyα\alpha/Lyβ\beta transmission fluctuations in a Keck ESI spectrum of the QSO. Interpreting the statistical HI proximity effect as arising from faint galaxies clustered around the detected LBGs, we translate the observed mean Lyα\alpha transmitted flux around an average detected LBG into a constraint on the mean escape fraction fesc0.08\langle f_{\rm esc}\rangle\geq0.08 at z6z\simeq6. We also report evidence of the individual transverse HI proximity effect of a z=6.177z=6.177 luminous LBG via a Lyβ\beta transmission spike and two broad Lyα\alpha transmission spikes around the z=5.701z=5.701 AGN. We discuss the possible origin of such associations which suggest that while faint galaxies are primarily driving reionisation, luminous galaxies and AGN may provide important contributions to the UV background or thermal fluctuations of the IGM at z6z\simeq6. Although a limited sample, our results demonstrate the potential of making progress using this method in resolving one of the most challenging aspects of the contribution of galaxies and AGN to cosmic reionisation.Comment: 21 pages, 16 figures, the version accepted in MNRA

    Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

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    Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting halfhourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).Peer reviewe

    Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

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    Background Underweight and obesity are associated with adverse health outcomes throughout the life course. We estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from 1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories. Methods We used data from 3663 population-based studies with 222 million participants that measured height and weight in representative samples of the general population. We used a Bayesian hierarchical model to estimate trends in the prevalence of different BMI categories, separately for adults (age ≥20 years) and school-aged children and adolescents (age 5–19 years), from 1990 to 2022 for 200 countries and territories. For adults, we report the individual and combined prevalence of underweight (BMI &lt;18·5 kg/m2) and obesity (BMI ≥30 kg/m2). For school&#x2;aged children and adolescents, we report thinness (BMI &lt;2 SD below the median of the WHO growth reference) and obesity (BMI &gt;2 SD above the median). Findings From 1990 to 2022, the combined prevalence of underweight and obesity in adults decreased in 11 countries (6%) for women and 17 (9%) for men with a posterior probability of at least 0·80 that the observed changes were true decreases. The combined prevalence increased in 162 countries (81%) for women and 140 countries (70%) for men with a posterior probability of at least 0·80. In 2022, the combined prevalence of underweight and obesity was highest in island nations in the Caribbean and Polynesia and Micronesia, and countries in the Middle East and north Africa. Obesity prevalence was higher than underweight with posterior probability of at least 0·80 in 177 countries (89%) for women and 145 (73%) for men in 2022, whereas the converse was true in 16 countries (8%) for women, and 39 (20%) for men. From 1990 to 2022, the combined prevalence of thinness and obesity decreased among girls in five countries (3%) and among boys in 15 countries (8%) with a posterior probability of at least 0·80, and increased among girls in 140 countries (70%) and boys in 137 countries (69%) with a posterior probability of at least 0·80. The countries with highest combined prevalence of thinness and obesity in school-aged children and adolescents in 2022 were in Polynesia and Micronesia and the Caribbean for both sexes, and Chile and Qatar for boys. Combined prevalence was also high in some countries in south Asia, such as India and Pakistan, where thinness remained prevalent despite having declined. In 2022, obesity in school-aged children and adolescents was more prevalent than thinness with a posterior probability of at least 0·80 among girls in 133 countries (67%) and boys in 125 countries (63%), whereas the converse was true in 35 countries (18%) and 42 countries (21%), respectively. In almost all countries for both adults and school-aged children and adolescents, the increases in double burden were driven by increases in obesity, and decreases in double burden by declining underweight or thinness. Interpretation The combined burden of underweight and obesity has increased in most countries, driven by an increase in obesity, while underweight and thinness remain prevalent in south Asia and parts of Africa. A healthy nutrition transition that enhances access to nutritious foods is needed to address the remaining burden of underweight while curbing and reversing the increase in obesit
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