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626 results for “Methanation”
Figure 4 in Free-living calamyzin chrysopetalids (Annelida) from methane seeps, anoxic basins, and whale falls
Figure 4. Vigtorniella zaikai. Line drawings, adult, NTM W.25871. A, anterior end, ventral view. B, jaw detail. C, mid-- body notochaetal fascicle. D, notochaetal detail. E, superior neurochaeta. F–H, mid and lower neurochaetae. I, spinigerous whip-like neurochaeta, segment II. Abbreviations: I, cirri of segment I; II, cirri and neuropodia of segment II; III, parapodia of segment III; j, jaws; la, lateral antennae; mp, mouth papillae; p, palp.
Figure 3 in Free-living calamyzin chrysopetalids (Annelida) from methane seeps, anoxic basins, and whale falls
Figure 3. Vigtorniella zaikai. Micrographs of larvae and adult. A, planktonic nectochaete larva SIO-BIC A5639, showing stylet jaws (arrow). B, detail of stylet jaws of specimen in (A). C, NTM W.25871, benthic adult, anterior end with jaws. D, E, SIO-BIC A5640: D, adult pharynx with jaws; E, detail of adult plate-like jaws. Abbreviation: dc1, dorsal cirrus segment I; ph, pharynx.
Figure 8 in Free-living calamyzin chrysopetalids (Annelida) from methane seeps, anoxic basins, and whale falls
Figure 8. Boudemos flokati gen. et comb. nov., California, juvenile specimen LACM 2783: A, anterior end showing pharynx with jaws (arrow); B, C, close-up views of jaws. Abbreviation: ph, pharynx.
Figure 1 in Free-living calamyzin chrysopetalids (Annelida) from methane seeps, anoxic basins, and whale falls
Figure 1. Eastern Pacific Ocean localities and habitats for the collection of Micospina auribohnorum gen. et sp. nov. These were a whale fall (fin whale) at a depth of 842 m off San Diego, California, and various methane seeps off Costa Rica, from depths of 745–1866 m.
Retrieval of dominant methane (CH4) emission sources, the first high resolution (1-2m) dataset of storage tanks of China in 2000-2021
<p>We presented a storage tank inventory of 92 typical cities with high volatile organic compounds, in response to the Three-Year Action Plan for Winning the Blue Sky Defense War, proposed by the State Council of China. It comprises of 14461 storage tanks, which are extracted based on high spatail resolution images of GaoFen-1, GaoFen-2, GaoFen-6, and Ziyuan satellites in year of 2021. It is the first inventory covering detailed distribution locations and boundaries of storage tanks. The inventory we aim to share provides a basic distribution of storage tanks in different sizes and will contribute to support environmentally friendly regulations proposal for more effective pollution control and energy resource management.</p>
Systematic review for optimizing sample size in dairy cow methane emission studies: a comprehensive methodological approach
<p>Collection of research data focusing on methane (CH4) emissions from dairy cows across various breeds and conditions. The dataset encompasses a range of studies published from 2012 to 2023, each documented with specific parameters including the study title, authors, country of research, cow breed, lactation status, methods used for CH4 measurement, experimental designs, CH4 yield and its variability, dry matter intake, and diet composition.</p>
GreenLITE™ single-blind controlled methane release data (EPA 2022)
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Eutrophication and deoxygenation drive high methane emissions from a brackish coastal system
<p>Data presented in the article "<span>Eutrophication and deoxygenation drive high methane emissions from a brackish coastal system </span>".</p>
Supplemental Data: Deciphering the biological contributors to methane cycling in Gulf Coast wetlands
<p>File descriptions:</p> <p>Data</p> <ul> <li>Table 1: experimental design. Number of samples from each wetland, ecosite and depth. Number of reads per sample. Other measurements available for each sample.</li> <li>Tale 2: geochemistry measurements. Anions, cations, pH, salinity and depth</li> <li>Table 3: 16S feature table with SILVA taxonomy</li> <li>Table 4: feature table of methanogens and methanotrophs</li> </ul> <p>Supplemental_Figures</p> <ul> <li>Figure S1: Dissolved oxygen measured at the saltwater marsh</li> <li>Figure S2: Redox potential of soils at each ecosite</li> <li>Figure S3: Concentrations of anions and cations at each ecosite</li> <li>Figure S4: Soil pH at each ecosite</li> <li>Figure S5: Community composition at the Phylum level</li> <li>Figure S6: Correlation matrix of methane cycling taxa and environmental variables</li> <li>Figure S7: Linear discriminant analysis of methane cycling genera</li> <li>Figure S8: Relative abundance of soil methanogen and methanotroph tax across sites, ecosites, and depths</li> <li>Figure S9: Relative abundance of water column methanotroph taxa across sites, ecosites, and depths</li> </ul>
China's gridded fugitive energy methane emissions over 2011-2020
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Methane plumes for NASA/JPL/UArizona/ASU Sep-Nov 2019 Permian campaign
<p>Plume imagery to accompany the journal article "Intermittency of Large Methane Emitters in the Permian Basin"</p> <p>Journal Article Citation:</p> <p>Daniel H. Cusworth, Riley M. Duren, Andrew K. Thorpe, Winston Olson-Duvall, Joseph Heckler, John W. Chapman, Michael L. Eastwood, Mark C. Helmlinger, Robert O. Green, Gregory P. Asner, Philip E. Dennison, and Charles E. Miller</p> <p>Environmental Science & Technology Letters <strong>2021</strong> <em>8</em> (7), 567-573</p> <p>DOI: 10.1021/acs.estlett.1c00173</p>
Riparian cottonwood trees and adjacent river sediments have different microbial communities and produce methane with contrasting carbon isotope compositions
<p class="Abstract">Rivers and their adjacent riparian forests are intimately linked by the exchange of water, nutrients, and organic matter. Both riparian cottonwood trees and adjacent river sediments host microbial communities including archaeal methanogens, supporting methane production and emission to the atmosphere. Here we combine microbial community and stable isotope analyses to characterize the drivers of methane cycling in distinct anoxic habitats (river sediments versus riparian cottonwood stems) in the Oldman River, southern Alberta (Canada). We demonstrate that, differences in the chemical characteristics of organic matter support divergent microbial communities that generate methane from distinct metabolic pathways. Organic matter in river sediments had C/N ratios approximately 50-fold lower than in tree stems and had more diverse dissolved organic components. Contrasting substrate availability between river sediment and tree stems was likely the primary mechanism for the observed differences in bacterial and methanogen community compositions, and greater microbial diversity in river sediments than in tree stems. The methane carbon isotope composition (δ<sup>13</sup>C values) differed for the tree stem (-103.6 to -70.6‰) and river sediment (-55.1 to -48.4‰) environments, suggesting that methane was primarily produced via CO<sub>2</sub>-reduction in tree stems by Methanobacteriales, while river sediments produced more methane through acetate fermentation primarily by Methanosarcinales. This study demonstrates the importance of organic matter quality and microbial community composition in driving metabolic processes contributing to methane production and emission in rivers and adjacent riparian forests.</p>
Full Dataset S4 - Metagenomes associated with the methane ice worm (Sirsoe methanicola)
<p><strong>FULL DATASET S4</strong>. IDs and alignment statistics of each read from A) worm fragments sequenced by HiSeq (Library W), B) gut contents sequenced by HiSeq (Library G), and C) gut contents sequenced by MiSeq (Library G-Mi) matching 16S rRNA gene sequences sequenced from methanogenic habitats (<strong>Dataset S3</strong>) using NCBI Magic-BLAST. The results were deduplicated to only show paired-reads. For multi-mapping reads, the alignment with the highest score is shown. The alignment statistics were further summarized in D) Library W, E) Library G, and F) Library G-Mi to show the total number of reads, mean % identity, min % identity, and max % identity mapped to each reference sequence. G) Predicted taxonomy for reference 16S rRNA gene sequences in <strong>Dataset 3 </strong>produced by QIIME2's VSEARCH-based consensus taxonomy classifier and sci-kit learn classifier.</p>
Data from: Increased annual methane uptake driven by warmer winters in an alpine meadow
<p>Pronounced non-growing season warming and changes in soil freeze-thaw (F-T) cycles can dramatically alter net methane (CH<sub>4</sub>) exchange rates between soils and the atmosphere. However, the magnitudes and drivers of warming impacts on CH<sub>4</sub> uptake in different stages of the F-T cycle are poorly understood in cold alpine ecosystems, which have been found to be a net sink of atmospheric CH<sub>4</sub>. Here, we reported a year-round ecosystem daily CH<sub>4</sub> uptake in an alpine meadow on the Qinghai-Tibetan Plateau after a five-year warming experiment that included a control, a low-level warming treatment (+2.4℃ at 5 cm soil depth), and a high-level warming treatment (+4.5℃ at 5 cm soil depth). We found that warming shortened the F-T cycle under the low-level warming and soils did not freeze under the high-level warming. Although both warming treatments increased the mean CH<sub>4</sub> uptake rate, only the high-level warming significantly increased annual CH<sub>4</sub> uptake compared to the control. The warming-induced stimulation of CH<sub>4</sub> uptake mainly occurred in the cold season, which was mostly during spring thaw under low-level warming and during the frozen winter under high-level warming due to a longer period with thawed soil. We also found that warming significantly stimulated daily CH<sub>4</sub> uptake mainly by reducing near-surface soil water content in the warm season, whereas both soil water content and temperature controlled daily CH<sub>4</sub> uptake in different ways during the autumn freeze, frozen winter, and spring thaw periods of the control. Our study revealed a strong warming effect on CH<sub>4</sub> uptake during the entire F-T cycle in the alpine meadow, especially the unfrozen winter. Our results also suggested the important roles of soil pH, available phosphorus, and methanotroph abundance in regulating annual CH<sub>4</sub> uptake in response to warming, which should be incorporated into biogeochemical models for accurately forecasting CH<sub>4</sub> fluxes under future climate scenarios.</p>
Peat macropore networks – new insights into episodic and hotspot methane emission
<p>The data and scripts are related to the manuscript "Peat macropore networks – new insights into episodic and hotspot methane emission" by Petri Kiuru, Marjo Palviainen, Tiia Grönholm, Maarit Raivonen, Lukas Kohl, Vincent Gauci, Iñaki Urzainki, and Annamari (Ari) Laurén submitted to Biogeosciences.</p>
Predicting methane emission in Canadian Holstein dairy cattle using milk mid-infrared reflectance spectroscopy and other commonly available predictors via artificial neural networks
<p>Supplementary Tables - Version 2</p>
Data from: High spatiotemporal variability of methane concentrations challenges estimates of emissions across vegetated coastal ecosystems
<div> <p><span>Coastal </span><span>methane (CH<sub>4</sub>) emissions dominate the global ocean CH<sub>4</sub> budget and can offset the "blue carbon" storage capacity of vegetated coastal ecosystems. However, current estimates lack systematic, high-resolution, and long-term data from these intrinsically heterogeneous environments, making coastal budgets </span><span>sensitive to statistical assumptions and uncertainties</span><span>. Using continuous CH<sub>4</sub> concentrations, δ<sup>13</sup>C-CH<sub>4</sub> values, and CH<sub>4</sub> sea-air fluxes across four seasons in three globally pervasive coastal habitats, we show that the CH<sub>4 </sub>distribution is spatially patchy over meter-scales and highly variable in time. Areas with mixed vegetation, macroalgae, and their surrounding sediments exhibited a spatiotemporal variability of surface water CH<sub>4 </sub>concentrations ranging two orders of magnitude (i.e., 6 – 460 nM CH<sub>4</sub>) with habitat-specific seasonal and diurnal patterns. We observed (1) δ<sup>13</sup>C-CH<sub>4</sub> signatures that revealed habitat-specific CH<sub>4</sub> production and consumption pathways, (2) daily peak concentration events that could change >100% within hours across all habitats, and (3) a high thermal sensitivity of the CH<sub>4 </sub>distribution signified by apparent activation energies of </span><span>∼</span><span>1 eV that drove seasonal changes. </span><span>Bootstrapping simulations show that scaling the CH<sub>4</sub> distribution from few samples involves large errors,</span><span> and that </span><span>∼</span><span>50 concentration samples per day are needed to resolve the scale and drivers of the natural variability and improve the certainty of flux calculations by up to 70%. Finally, we identify northern temperate coastal habitats with mixed vegetation and macroalgae as understudied but seasonally relevant atmospheric CH<sub>4</sub> sources (i.e., releasing ≥100 μmol CH<sub>4</sub> m<sup>−2</sup> day<sup>−1</sup> in summer). Due to the large spatial and temporal heterogeneity of coastal environments, high-resolution measurements will improve the reliability of CH<sub>4</sub> estimates and confine the habitat-specific contribution to regional and global CH<sub>4</sub> budgets.</span></p> </div>
Data from: High methane emissions from an anoxic fjord driven by mixing and oxygenation
<p>Tracking sources, sinks and long-term trends of methane emissions is imperative under climate change. Marine methane fluxes remain elusive and uncertain even though the ocean plays a major role in global budgets. High-latitude fjord ecosystems are widespread, store large amounts of sediment carbon, and undergo cycles of water column mixing, making them potential but still overlooked sources of methane to the atmosphere. Here, state-of-the-art benthic lander robots and multi annual observations revealed that anoxic fjords emit substantially more methane during mixing events than under water stratification. Fjords only cover 0.1% of global sea surface area, but may contribute as much methane as that released by the open ocean, which covers 84% of the global sea surface.</p>
Methane emission and 13C data - Mycklemossen
<p>Picarro data from automatic chamber system</p> <p>Temperature and PAR data from automatic chamber system</p>
A 130-year global inventory of methane emissions from livestock: trends, patterns, and drivers
<p>Livestock contributes approximately one-third of global anthropogenic methane (CH4) emissions. Quantifying the spatial and temporal variations of these emissions is crucial for climate change mitigation. Although country-level information is reported regularly through national inventories and global databases, spatially-explicit quantification of century-long dynamics of CH4 emissions from livestock has been poorly investigated. Using the Tier 2 method adopted from the 2019 Refinement to 2006 IPCC guidelines, we estimated CH4 emissions from global livestock at a spatial resolution of 0.083° (~ 9 km at the equator) during the period 1890−2019. We find that global CH4 emissions from livestock increased from 31.8 [26.5−37.1] (mean [minimum−maximum of 95% confidence interval) Tg CH4 yr-1 in 1890 to 131.7 [109.6−153.7] Tg CH4 yr-1 in 2019, a fourfold increase in the past 130 years. The growth in global CH4 emissions mostly occurred after 1950 and was mainly attributed to the cattle sector. Our estimate shows faster growth in livestock CH4 emissions as compared to the previous Tier 1 estimates and is ~20% higher than the estimate from FAOSTAT for the year 2019. Regionally, South Asia, Brazil, North Africa, China, the United States, Western Europe, and Equatorial Africa shared the majority of the global emissions in the 2010s. South Asia, tropical Africa, and Brazil have dominated the growth in global CH4 emissions from livestock in the recent three decades. Changes in livestock CH4 emissions were primarily associated with changes in population and national income and were also affected by the policy, diet shifts, livestock productivity improvement, and international trade. The new geospatial information on the magnitude and trends of livestock CH4 emissions identifies emission hotspots and spatial-temporal patterns, which will help to guide meaningful CH4 mitigation practices in the livestock sector at both local and global scales.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.