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19 results for “Tephra”
Community Established Best Practice Recommendations for Tephra Studies-from Collection through Analysis
<p>Tephra is a unique volcanic product with an unparalleled role in understanding past eruptions, long-term behavior of volcanoes, and the effects of volcanism on climate and the environment. Tephra deposits also provide spatially widespread, extremely high-resolution time-stratigraphic markers across a range of sedimentary settings and are used in a range of disciplines (e.g., volcanology, climate science, archaeology, ecology, and impact assessment). Nonetheless, the study of tephra deposits is challenged by a lack of standardization that often inhibits data integration across geographic regions and across disciplines.</p> <p>Here we present comprehensive recommendations for tephra data gathering and reporting that were developed by the tephra science community to serve as guidelines for future investigators and to ensure that sufficient data are gathered for transparency and interoperability. Recommendations include standardized field and laboratory data collection along with reporting and correlation guidance. These are organized as tabulated lists of key metadata with their definition and purpose. They are system independent and usable for template, tool, and database development. This new standardized framework promotes consistent tephra documentation and archiving, fosters interdisciplinary communication, and improves effectiveness of data sharing among diverse communities of researchers. Wider adoption will help to expand the applicability and usability of tephra data and facilitate scientific collaboration and data reuse.</p> <p>For additional details, see the accompanying manuscript:</p> <p>Wallace, K.*, Bursik, M. Kuehn, S., Kurbatov, A., Abbott, P., Bonadonna, C., Cashman, K., Davies, S., Jensen, B., Lane, C., Plunkett, G., Smith, V. Tomlinson, E., Thordarsson, T., and Walker, D. Community established best practice recommendations for tephra studies—from collection through analysis. <em>Sci Data</em> <strong>9, </strong>447 (2022). <a href="https://doi.org/10.1038/s41597-022-01515-y">https://doi.org/10.1038/s41597-022-01515-y</a></p> <p>*corresponding author: Kristi Wallace, <a href="mailto:kwallace@usgs.gov">kwallace@usgs.gov</a></p> <p>Open access article is available online here <a href="https://doi.org/10.1038/s41597-022-01515-y">https://doi.org/10.1038/s41597-022-01515-y</a> or as a PDF here <a href="https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nature.com%2Farticles%2Fs41597-022-01515-y.pdf&data=05%7C01%7Ckwallace%40usgs.gov%7C673f9f39fd3e4122dd9b08da6f3b9667%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C637944598967375940%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=%2BKVfwK2FbUKAoJf2gMerCmBMEQE1rvMDkS6xIk3DGKY%3D&reserved=0">https://www.nature.com/articles/s41597-022-01515-y.pdf</a>.</p>
Thermal demagnetization data of Risica et al. (Deposit-derived block-and-ash flows: the hazard posed by perched temporary tephra accumulations on volcanoes; 2018 Fuego disaster, Guatemala)
<p>Thermal demagnetization data (repository data) of Risica et al. "Deposit-derived block-and-ash flows: the hazard posed by perched temporary tephra accumulations on volcanoes; 2018 Fuego disaster, Guatemala".</p>
Lithogenesis of a phosphatized tephra marker horizon in the Eocene Messel maar lake
<p>Diffractograms of the Messel pit marker horizon M - messelite bands and a band consisting of messelite, montgomeryite, and mantienneite</p>
Vesicle size analysis dataset of Eldgjá tephra
<p>Raw vesicle area and metadata acquired by image analysis of thin-sections of Eldgjá tephra clasts. Acquired using the methods outlined by <a href="https://doi.org/10.1016/j.jvolgeores.2009.12.003">Shea et al. (2010)</a>, <a href="https://doi.org/10.1016/S0377-0273(98)00043-2">Sahagian & Proussevitch (1998)</a>, and <a href="https://hdl.handle.net/20.500.11815/324">Moreland (2019a)</a>.</p> <p>The format is compatible with the VSA Processor script (<a href="https://doi.org/10.5281/zenodo.2591179">Moreland 2019b</a>).</p>
Individual glass and secondary standard analyses for tephra described in sediment cores from Skilak Lake, Alaska
<p>This dataset comprises individual glass shard and secondary standard analyses for tephra collected in sediment cores from Skilak Lake, Alaska. These geochemical analyses were used in the research article in Sedimentology titled “Unravelling a 2300 year long sedimentary record of megathrust and intraslab earthquakes in proglacial Skilak Lake, south-central Alaska” by Praet et al. (2022). DOI: <a href="https://doi.org/10.1111/sed.12986">10.1111/sed.12986</a></p>
Data for NHESS manuscript by Biass et al. (2022): Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data
<p>This repository contains the data produced in the context of the following paper:</p> <blockquote> <p>Biass S, Jenkins SF, Aberhard WH, Delmelle P, Wilson T (2022): Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data, Accepted in NHESS</p> </blockquote> <p>Naming convention is: `run_date`_`landcover`_`impact_metrics`_`VI`_`anomaly`_test.pkl, where:</p> <ul> <li>Landcover is either crops, shrubs, herbaceous vegetation (grass), forests (trees) or all together</li> <li>Impact metrics is either minV (impact magnitude) or minT (impact duration)</li> <li>VI is the vegetation index (here, EVI)</li> <li>Anomaly is the impact indicator (here, cumulative difference index)</li> </ul> <p>Refer to the associated paper for more information on the methodology.</p> <p>Files are saved as .pkl and were generated by the <a href="https://explainerdashboard.readthedocs.io/en/latest/">explainerdashboard</a> library. They are the result of <a href="https://xgboost.readthedocs.io/en/stable/">XGBoost</a> runs that were optimised with <a href="https://optuna.org">Optuna</a> and analysed with the <a href="https://shap.readthedocs.io/en/latest/">SHAP</a> library. They contain:</p> <ol> <li>The explanatory variables and observed and computed target variables for all features</li> <li>The SHAP values</li> </ol> <p>To load the files, use <a href="https://explainerdashboard.readthedocs.io/en/latest/cli.html?highlight=load#explainerdashboard.explainers.BaseExplainer.from_file">this method</a>.</p> <p> </p>
Holocene marine tephra offshore Ecuador and Southern Colombia collected during the Amadeus and Atacames oceanographic campaigns (2005, 2012)
<p>Marine sediment cores collected during the Amadeus and Atacames oceanographic cruises reveal numerous turbidite and ash deposits, which are related to major earthquakes and volcanic eruptions that occurred along the Ecuadorian margin during the Holocene. We provide <sup>14</sup>C ages performed on planktonic foraminifera present in hemipelagic layers to constrain the age of turbidite sequences, as well as geochemical analyses of ash layers to identify their source.</p> <p>Files:</p> <p>1. Location of coring sites<br> 2. Raw 14C ages performed on planktonic foraminifera<br> 3. Depth of tephra layers<br> 4. Raw Electron Microprobe results (single glass shards)<br> 5. Raw LA-ICP-MS results (single glass shards)<br> 6. Raw ICP-AES results (bulk glass shards)</p> <p> </p>
LSTbase - a collation of Laacher See tephra occurrences
<p>LSTbase is a collation - from the literature - of locations at which Laacher See ejecta has been identified.</p> <p>The data are presented 'as is' with information taken from the published literature. The focus has been strictly on point-like occurrences in the medial and distal fields. For proximal mappings of tephra blankets and PDCs please consult the many publications by the late Hans-Ulrich Schmincke and collaborators. In addition, German soil maps also contain information on such blanket deposits (https://geoportal.bgr.de/mapapps/resources/apps/geoportal/index.html?lang=en#/geoviewer).</p> <p> </p> <p>Laacher See tephra occurrences are by default assumed to be the result of airfall; in some case - chiefly in relation to deposits along the River Rhine - they are classed as fluvially deposited, however. Please consult the original publications for further information.</p> <p>Whenever the information is provided in the original publications, section or core labels are given.</p> <p> </p> <p>Coordinates are provided in WGS84; not all locations are precise.</p> <p> </p> <p>For additional datapoints or corrections, please contact f.riede@cas.au.dk</p> <p> </p> <p>An earlier version of this dataset was published in Tephrabase (https://www.tephrabase.org/laacherSee.html) and reported in Riede, Felix, Oliver Bazely, Anthony J. Newton, and Christine S. Lane. “A Laacher See-Eruption Supplement to Tephrabase: Investigating Distal Tephra Fallout Dynamics.” Quaternary International 246, no. 1–2 (2011): 134–44. https://doi.org/doi: 10.1016/j.quaint.2011.06.029.</p>
Radiocarbon, Tephra, and Paleomagnetic Data from 5 Northern North Atlantic Sediment Cores to support Reilly et al. 2023, "The Amplitude and Timescales of 0-15 ka Paleomagnetic Secular Variation in the Northern North Atlantic."
<p>Data in support of Reilly et al., 2023, "The Amplitude and Timescales of 0-15 ka Paleomagnetic Secular Variation in the Northern North Atlantic." Published in the Journal of Geophysical Research: Solid Earth.</p> <p> </p> <p>Excel file includes worksheets for the following data:</p> <p>Tabular versions of the Supplementary Data Tables from the associated publication:</p> <ul> <li>Supplementary Table S1 from Publication: 14C data from sediment cores used in study</li> <li>Supplementary Table S2 from Publication: 14C data used in the GREENICE15 Stack</li> <li>Supplementary Table S3 from Publication: Tephra data used in study</li> </ul> <p>Paleomagnetic Datasets for the Characteristic Remanent Magnetizations used in this study:</p> <ul> <li>Paleomagnetic Data for Core MD99-2264</li> <li>Paleomagnetic Data for Core MD99-2265</li> <li>Paleomagnetic Data for Core MD99-2266</li> <li>Paleomagnetic Data for Core MD99-2269</li> <li>Paleomagnetic Data for Core MD99-2322</li> </ul> <p>Independent radiocarbon based Age Models for 5 cores used in this study:</p> <ul> <li>Independent Age Model for Core MD99-2264</li> <li>Independent Age Model for Core MD99-2265</li> <li>Independent Age Model for Core MD99-2266</li> <li>Independent Age Model for Core MD99-2269</li> <li>Independent Age Model for Core MD99-2322</li> </ul> <p>PSV Dynamic Time Warping (DTW) solutions of 3 cores to target curve, as described in publication</p> <ul> <li>DTW solution for MD99-2265 to target curve</li> <li>DTW solution for MD99-2266 to target curve</li> <li>DTW solution for MD99-2322 to target curve</li> </ul> <p>GREENICE15 PSV Stack</p> <ul> <li>Age model for GREENICE15 Stack using combined radiocarbon dates and correlated equivalent depth scale</li> <li>Inclination, Declination, and alpha 95 for the GREENICE15 PSV Stack</li> </ul>
IDW interpolation dataset of ash and tephra deposition following the 2021 Tajogaite volcanic eruption on La Palma, Canary Islands, Spain
<p>The compiled dataset is the result of a field collection campaign to measure the depth of the ash and tephra layer in the aftermath of the 2021 volcanic eruption (Tajogaite) on the island of La Palma, Canary Islands, Spain.</p> <p>The dataset consists of two files: a shapefile and a GeoTIFF raster. The shapefile is a point layer file that displays the location of all ash depth measurements (415 points) taken in the field. To improve our sampling near the crater, where safety and time constraints prevented field collection, we manually sampled additional drone-based measurements (66 points). We combined these data into a single dataset ("ash_depth"; 481 total points) that was then used as input for a spatial interpolation using Inverse Distance Weighting (IDW).</p> <p>The IDW interpolation was performed using the Spatial Analyst toolbox in ArcMap 10.8.1 (Esri, 2021). As an exact deterministic interpolation, IDW estimates pixels values of unknown points by using average distance and a weight between sample points (Watson & Philip, 1985). This is ideal for a dataset that includes many field measurements since IDW interpolates between the minimum and maximum of the collected data. The model parameters were adjusted manually but the best results were yielded using the default settings, with the exception of the output cell size. The output cell size was calibrated to 2 m. The IDW parameters can be viewed in Table 1.</p> <p>The sample point locations were resampled from the raster file to estimate the Root Square Mean Error (RMSE) and were saved to the shapefile as "ash_idw". The RMSE of the dataset is 0.34 m. For further inquiries please contact Christopher Shatto (email: christopher.shatto@uni-bayreuth.de).</p> <p> </p> <p>Please cite the data paper link to this repository as: </p> <p><strong>C. Shatto, F. Weiser and A. Walentowitz et al., Volcanic tephra deposition dataset based on interpolated field measurements following the 2021 Tajogaite Eruption on La Palma, Canary Islands, Spain, Data in Brief, https://doi.org/10.1016/j.dib.2023.109949</strong></p> <p> </p> <table> <tbody> <tr> <td>Power</td> <td>2</td> </tr> <tr> <td>Output cell size</td> <td>2</td> </tr> <tr> <td>Search neighborhood type</td> <td>Standard (circular)</td> </tr> <tr> <td>Major/minor semiaxis</td> <td>12161.79/12161.79</td> </tr> <tr> <td>Max/minimum neighbors</td> <td>15/10</td> </tr> <tr> <td>Sector type</td> <td>1</td> </tr> <tr> <td>Angle</td> <td>0</td> </tr> <tr> <td>Weight field</td> <td>None</td> </tr> </tbody> </table> <p> </p>
Summer Lake Pliocene Tephra Dataset
<p>This dataset describes a fault-uplifted sequence of 11 tephra layers preserved in ~3 Ma, fossiliferous lacustrine sediments and 3 tephra in adjacent late Pleistocene lacustrine sediments and Holocene dune sand at Summer Lake, Oregon, USA. It includes tephra and host sediment stratigraphy, sample information, tephra layer thicknesses, tephra grain size data, volcanic glass geochemistry, SEM imagery, method information, and suggested tephra correlations.</p> <p>Most of this information is contained in a series of spreadsheets that follow <a href="https://zenodo.org/record/4075613#.X5mcdi9h1aU">tephra community recommended best practices</a>. </p> <p>The listed files below follow the naming convention and format of Abbott et al. (2020) version 2.0, and they serve as worked examples of that format. See DOI: <a href="https://doi.org/10.5281/zenodo.3866266">10.5281/zenodo.3866266</a> for more information.</p> <ul> <li>Summer Lake Collection3b.xlsx (location information, sample information, stratigraphy)</li> <li>Summer Lake Sample_Processing2.xlsx (sample preparation)</li> <li>Summer Lake Physical_analysis2.xlsx (maximum grain size data, pumice class density)</li> <li>Summer Lake Physical_Microanalysis3.xlsx (polarizing microscope images, SEM-EDS images, sample mount images)</li> <li>Summer Lake Geochemical_Analysis 3.xlsx (EPMA method details)</li> </ul> <p>Glass geochemistry by EPMA may be found in the following file:</p> <ul> <li>Summer Lake Glass DATA.xlsx</li> </ul> <p>SEM and other images may be found in the following file:</p> <ul> <li>Summer Lake EPMA Images.zip</li> </ul> <p>Additional geological field data and field photographs may be found in the <a href="https://strabospot.org">StraboSpot repository</a>.</p>
June Lake Tephra Dataset
<p>This dataset describes a sequence of tephra layers recovered from a Holocene sediment core taken at June Lake, California, USA. It includes tephra sediment stratigraphy, sample information, tephra layer thicknesses, tephra grain size data, volcanic glass geochemistry, Fe-Ti oxide geochemistry, SEM imagery, and method information. The tephra layers originate from the Mono-Inyo volcanic system.</p> <p>Most of this information is contained in a series of spreadsheets that follow <a href="https://zenodo.org/record/4075613#.X5mcdi9h1aU">tephra community recommended best practices</a>. </p> <p>The listed files below follow the naming convention and format of Abbott et al. (2020) version 2.0, and they serve as worked examples of that format. See DOI: <a href="https://doi.org/10.5281/zenodo.3866266">10.5281/zenodo.3866266</a> for more information.</p> <ul> <li>June Lake Collection2b.xlsx (location information, sample information, stratigraphy)</li> <li>June Lake Sample_Processing.xlsx (sample preparation)</li> <li>June Lake Physical_analysis2b.xlsx (maximum grain size data, pumice class density)</li> <li>June Lake Physical_Microanalysis2.xlsx (SEM-EDS images, sample mount images)</li> <li>June Lake Geochemical_Analysis2.xlsx (EPMA method details)</li> </ul> <p>Glass and Fe-Ti oxide geochemistry by EPMA may be found in the following files:</p> <ul> <li>June Lake Glass DATA.xlsx</li> <li>June Lake Fe-Ti Oxides DATA.xlsx</li> </ul> <p>SEM and other images may be found in the following file:</p> <ul> <li>June Lake EPMA Images.zip</li> </ul>
Data from: Detection of tephra layers in Antarctic sediment cores with hyperspectral imaging
Tephrochronology uses recognizable volcanic ash layers (from airborne pyroclastic deposits, or tephras) in geological strata to set unique time references for paleoenvironmental events across wide geographic areas. This involves the detection of tephra layers which sometimes are not evident to the naked eye, including the so-called cryptotephras. Tests that are expensive, time-consuming, and/or destructive are often required. Destructive testing for tephra layers of cores from difficult regions, such as Antarctica, which are useful sources of other kinds of information beyond tephras, is always undesirable. Here we propose hyperspectral imaging of cores, Self-Organizing Map (SOM) clustering of the preprocessed spectral signatures, and spatial analysis of the classified images as a convenient, fast, non-destructive method for tephra detection. We test the method in five sediment cores from three Antarctic lakes, and show its potential for detection of tephras and cryptotephras.
Data for: Andic soil properties and tephra layers hamper C turnover in Icelandic peatlands - selective dissolution of Al, Fe, Si and decomposition proxies
<p>Due to frequent volcanic activity and erosion of dryland soils, peatlands in Iceland receive regular additions of mineral aeolian deposits (tephra and eroded material). Therefore, their soils may develop not only histic, but also andic characteristics. Here we present data sets of a study that elucidates interactions between carbon characteristics and andic soil properties in Histosols of three Icelandic peatlands. The data sets contain information about the soil carbon structure derived by <sup>13</sup>C NMR spectroscopy, andic soil properties based on selective dissolution of Al, Fe and Si, decomposition proxies C/N, δ<sup>13</sup>C and δ<sup>15</sup>N, information on total carbon and nitrogen content, dry bulk density, soil organic matter content and pH measured in deionised water and NaF solution.</p>
[Simulation] Dynamics, Monitoring and Forecasting of Tephra in the Atmosphere.
<p><span><span>This repository </span><span>contains</span><span> the simulations</span><span> to produce Figures 1</span><span>5</span><span> and 1</span><span>7</span><span> in " </span><span>Dynamics, Monitoring and Forecasting of Tephra in the Atmosphere</span><span> " - Reviews of Geophysics, by </span></span><span><span>Pardini</span> </span><span><span>et al. (2024).</span></span><span> </span></p>
Data from: Understory succession after burial by tephra from Mount St. Helens
Open the record for dataset details and reuse information.
Data for: Andic soil properties and tephra layers hamper C turnover in Icelandic peatlands - selective dissolution of Al, Fe, Si and decomposition proxies
Open the record for dataset details and reuse information.
Data from: Detection of tephra layers in Antarctic sediment cores with hyperspectral imaging
Open the record for dataset details and reuse information.
Tephra fall hazard curves in Japan
<p>This is the dataset of tephra fall hazard curves at 47 prefecural offices. These were created usng the database of TephraDB_Prototype_ver1 at 10.5281/zenodo.3608346 and the scripts at https://github.com/s-uesawa/Prototype-TephraDB-Japan. Related paper is now availavle online at https://dx.doi.org/10.21203/rs.2.23106/v1.</p>
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