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96 results for “DOC”
Photomineralization apparent quantum yield at 309 nm for DOC leached from permafrost soils collected from the North Slope of Alaska in the summer of 2015
Dissolved organic carbon (DOC) was leached from permafrost soils near the Toolik Field Station in the Alaskan Arctic and then characterized for its photochemical properties. The apparent quantum yield of photomineralization (photochemical carbon dioxide, CO2, production) of permafrost DOC was quantified at 309 nm.
Preparation of DOC leachates from permafrost soils collected from the North Slope of Alaska in the summer of 2018
Dissolved organic carbon (DOC) was leached from permafrost soils collected from the frozen permafrost layer at five sites underlying moist acidic tussock or wet sedge vegetation, and on three glacial surfaces on the North Slope of Alaska during summer 2018.
Dissolved organic carbon (DOC) in Imnavait Creek, Foothills, Brooks Range, Alaska, 2002-2009.
This file contains data on dissolved organic carbon concentrations from the main weir at Imnavait Creek on the North Slope of Alaska. The data coverage is from 2002 to 2009. Concentrations are expressed in micromoles of carbon per liter of water.
Dissolved organic carbon (doc) in stream water at watersheds 7, 14, and 27 at the Coweeta Hydrologic Laboratory, Otto, North Carolina, USA.
Dissolved organic carbon (DOC) plays a critical role in stream ecosystem processes. This study seeks to examine long-term patterns in DOC concentration in stream water resulting from climatic variation and associated with recovery form clear-cutting. Watershed 7 was clear-cut in 1977 as part of a multi-investigator study examining the response of both the terrestrial and aquatic communities to commercial clear-cutting.
Dissolved organic carbon (DOC) concentrations in glacial meltwater streams, McMurdo Dry Valleys, Antarctica (1990-2023, ongoing)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic aqueous geochemical sampling program has been undertaken. A series of terrestrial water samples have been collected and analyzed for dissolved organic carbon levels. This dataset shows concentrations of dissolved organic carbon found in various streams of the McMurdo Dry Valleys.
Dissolved organic carbon (DOC) concentrations in discrete water column samples collected from lakes in the McMurdo Dry Valleys, Antarctica (1993-2022, ongoing)
The McMurdo Long Term Ecological Research (LTER) project monitors patterns of organic material transport in perennial ice-capped lakes. This data set addresses this core area of research and quantifies dissolved organic carbon concentrations at specific depths in McMurdo Dry Valley lakes.
Stable and radiocarbon isotope compositions of DOC and DIC in Southeast Asian drainage canals
<p>This dataset contains the stable and radiocarbon isotope compositions of dissolved organic carbon (DOC) and radiocarbon isotope compositions of dissolved inorganic carbon (DIC) produced during DOC microbial respiration and photomineralization in canal waters sampled across disturbed peatlands in West Kalimantan, Indonesia in 2022. Microbial respiration and photomineralization experiments were carried out during laboratory incubations and natural sunlight exposures of canal water samples, respectively. Significant changes in the radiocarbon isotope composition of DIC between treatment and control waters were detected using a headspace extraction technique followed by a small-carbon extraction line for radiocarbon samples. </p>
DH2.1 working docs: DH 2.1 working version March 2022
The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
DH2.1 working docs: DH1.1 working version
The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
DH2.1 working docs: DH2.1 working version November 2021
The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
DH2.1 working docs: COL2020-08-01
The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
Interim data for scoping review on diagnosis, prognosis and treatment of pediatric DoC
<p>These are the data produced by the working group, while evaluating the existing literature on diagnosis, prognosis and treatment of pediatric DoC. Files include the results of the systematic search (3 repetitions), the data input of abstraction forms and QUADAS-2 and PROBAST checklists. A study workflow is also provided.</p>
Binned dissolved organic carbon (DOC), dissolved organic nitrogen (DON), and dissolved organic phosphorus (DOP) concentration observations in the ocean
<p>Here we provided binned dissolved organic carbon (DOC), dissolved organic nitrogen (DON), and dissolved organic phosphorus (DOP) concentration observations in the ocean used for manuscript "Global patterns of surface ocean dissolved organic matter stoichiometry " submitted to Global Biogeochemical Cycles.</p> <p>DOC and DON concentrations observations are from a compilation of DOM data obtained from global ocean observations from 1994 to 2021 (Hansell et al., 2021, https://doi.org/10.25921/s4f4-ye35)</p> <p>DOP concentration observations are from the DOPv2021 database (Liang et al., 2022, https://doi.org/10.1038/s41597-022-01873-7)</p> <p>We binned the data into the OCIM2 grid with a resolution of 2˚x2˚ with 24 vertical layers. More info about OCIM2 grid can be found on <a href="https://tdevries.eri.ucsb.edu/models-and-data-products/">https://tdevries.eri.ucsb.edu/models-and-data-products/</a></p>
Marcell Experimental Forest peat core extraction chemical analysis data (DOC, Fe, Ca, Mg, K, P, Al)
This data set reports iron (Fe), dissolved organic carbon (DOC), calcium (Ca), magnesium (Mg), potassium (K), phosphorus (P), and aluminum (Al) measured in extractions of soil cores sampled from two boreal peatlands, the S1 and S2 bogs, in the Marcell Experimental Forest (MEF) in Itasca County, Minnesota. The soil cores were sampled on September 2, 2017. Elements were quantified in extractions with hydrochloric acid, sodium dithionite, sodium sulfate, and sodium dithionite plus hydrochloric acid to examine how iron influences carbon and nutrient cycling in peatlands. The S1 and S2 sites are research catchments instrumented for hydrologic monitoring. The S1 bog is also the location of the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment. These data are used, analyzed, and reported in Curtinrich et al. (2021, Ecosystems).
Soil DOC and moisture measurements along climate and black spruce productivity gradients in interior Alaska
Water-soluble organic carbon data extracted from organic and mineral soils along gradients in stand productivity and soil temperature throughout 2004. 200g of organic soil or 400g of mineral (5 cm) soil were used. Values should be corrected for oven dry moisture percent of soil (also included in data set). Nine soil cores were obtained randomly on a 20 x 20 m sampling grid at each site in May, June-July, and again in September 2004. Cores were parsed in the field into organic (Oi+Oe+Oa) and mineral soil (5 cm, A+B). All cores were immediately sealed in polyethylene bags and were kept on ice in an insulated cooler while being transported to laboratory refrigerators kept at approximately 4 degC. All organic soil samples were extracted for WSOC content within 24 hours, and mineral soils were extracted within 48 hours. Water-soluble organic C concentrations from subsets of mineral soils extracted 24 and 48 hours after collection did not significantly differ (p = 0.30, 5.3 mg C l-1). The method for extracting WSOC from the soil followed Huang and Schoenau (1996), which was modified from McGill et al. (1986). Briefly, field moist soil samples were homogenized on a tray and roots greater then 2 mm were removed. Then 20 g of organic soil or 40 g of mineral soil were gently shaken on a rotary table with 100 ml (n = 9 per horizon per date) of deionized water for 1 hour, filtered through a Whatman GF/A filter, and then passed through a Whatman 0.45 um membrane filter. Soil extracts were preserved at pH 2 using H3PO4 and refrigerated at 4 degC prior to analysis. Each field moist soil sample was subsampled to determine moisture content (gravimetrically) and WSOC was adjusted to an oven-dry basis. Bulk density and depth measurements for each soil horizon were used to relate mg WSOC kg oven dry soil-1 on an area basis at each site (g WSOC m-2). Three zero-tension lysimeters (85 x 19 cm) were installed perpendicular to slope at the organic-mineral soil interface at the end of the g
Water residence time and Damköhler number for DOC cycling in global watersheds
<p>The relative capacity for watersheds to eliminate or export reactive constituents has important implications on aquatic ecosystem ecology and biogeochemistry. Removal efficiency depends on factors that affect either the reactivity or advection of a constituent within river networks. In this dataset, we characterized instream water residence time and Damköhler number (Da) for dissolved organic carbon (DOC) uptake in global watersheds.</p>
Polarization measurements of DOC-dependent IpaB-IpaD interactions
<p>The binding affinity between each of the engineered IpaD alanine mutants and the stable IpaB<sup>28-226</sup> construct was measured using fluorescence polarization. Here, the DOC effect on binding affinity between IpaB and the engineered IpaD π-helix mutants was quantified by holding IpaB<sup>28-226</sup>-Alexa568 concentration constant while the concentration of IpaD or engineered IpaD mutant was titrated from 0-10 μM with identical conditions then tested in the presence of 1 mM DOC.</p>
Engineering the docs at LSST
<p>Documentation plays a quiet, but critical, role in our field. Sooner or later, all of us have to write docs, whether we want to or not, and whether we have formal training or not. Docs always seem to take longer to make, and are harder to maintain, than we expect. In this talk, I will walk through several case studies of how we approach documentation production at the Large Synoptic Survey Telescope from my perspective as the documentation engineer for the Data Management subsystem. I'll show how we democratized information sharing with our Developer Guide and technical notes platform; how a Slack bot and templates make everyone on the team work like professional documentarians; how implementing continuous delivery for documentation stopped endless email chains of PDF and Word files; and even how we're helping the commissioning team communicate their investigations through Jupyter notebooks. I'll talk candidly about both the benefits and costs of our engineering-forward approach to LSST documentation and hopefully, will inspire you to take a fresh look at writing the docs for your own projects.</p>
North American Flora: North American Flora (1st 7 docs)
Species descriptions and attribute records extracted from: North American flora. New York Botanical Garden. "It was planned to complete the Flora in 34 volumes. Some 94 parts of 24 volumes were published at irregular intervals between 1905 and 1949." <p></p>https://www.biodiversitylibrary.org/bibliography/889<p></p>
Watershed DOC uptake occurs mostly in lakes in the summer and in rivers in the winter: The CUPS-OF-DOC model
<p>River networks transport dissolved organic carbon (DOC) from terrestrial uplands to the coastal ocean. The extent to which a reach or lake within a river network uptakes DOC depends on the stream order, the seasonal conditions, and the flow. At the watershed scale, it remains unclear whether DOC uptake is dominated by biological processes such as respiration, or abiotic processes like photomineralization. The partitioning of DOC uptake in lakes versus rivers is also unclear. In this study, we present a new model that unifies year-round controls on DOC cycling for an entire river network, including river-lake connectivity, to elucidate the importance of biotic vs. abiotic controls on DOC uptake. We present the <strong>C</strong>atchment <strong>Up</strong>take and <strong>S</strong>inks by <strong>S</strong>eason, <strong>O</strong>rder, and <strong>F</strong>low for <strong>DOC</strong> (CUPS-OF-DOC) model, which quantifies terrestrial DOC loading, gross primary productivity (GPP), and uptake via microbes and photomineralization. The model is applied to the Connecticut River Watershed and accounts for cascading reach- and lake-scale DOC cycling across ninety-eight scenarios spanning combinations of flows, seasons, and stream orders. We show that riverine DOC uptake is nearly constant with stream order, but the proportion of DOC uptake from photomineralization varies. Photomineralization dominates in rivers in most flow conditions and stream orders, especially in winter, accounting for at least half of whole-watershed DOC uptake in February across all flows. Whole-watershed summer DOC uptake occurs mostly via biomineralization in lakes, accounting for 80% of DOC uptake during the growing season, despite accounting for less than 6% of watershed open water surface area.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.