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483 results for “Iceland”
Survey data on attitudes towards salmon aquaculture industry in Norway, Iceland, and Tasmania (AU)
<p>The following data is from an online survey conducted in Norway, Tasmania (Australia), and Iceland. Respondents were recruited by survey companies that distributed e-mail invitations to their panels. A minimum respondent quotas was established for each region, with individuals under the age of 18 being exluded from participating in the survey. The dataset consists of a total of 2085 respondents, comprising 1183 participants from Norway, 406 from Tasmania, and 496 from Iceland. Questions were presented in their respective native language, namely Norwegian, English, and Icelandic.</p> <p>This survey data encompasses various aspects of perceptions of salmon aquaculture industry. Data was generated by the SoLic (Social License to operate for aquaculture) project (2019 - 2022), and funded by The Research Council of Norway (no. 295114). The survey was designed by the SoLic project group. </p> <p>The data and supplementary material is divided in 3 files:</p> <p>The raw survey data in .csv file format (Dataset Solic_2085 respondents.csv). The data file contains 71 variables and data from each of the 2085 respondents. Blank entries in the dataset indicate either a lack of response from the respondents or that specific questions were not applicable to certain respondents (questions exclusively posed to respondents in one country).</p> <p>Overview of survey questions and answer options (Survey.doc). The survey encompassed 28 questions related to the aquaculture industry, along with demographics, respondents’ knowledge of industry, trust in governance system, and environmental concerns. Some demographic variables were sourced from the existing panel data, while others were provided to respondents for their input.</p> <p>The codebook (Codebook.doc). The codebook provides explanations and details regarding all variables included in the survey data file. It includes coding information for each survey question, response options provided in the raw data, and further clarifies the purpose and origin of variables computed by the research group (e.g., variable on aquaculture municipality) or the survey company (e.g., weight variables for data from Norway and Iceland). When used in conjunction with the raw data, this codebook serves as a valuable guide for navigating the dataset. </p>
LTREB: Lake Myvatn Predation experiments at Myvatn, Iceland during 2009 and 2011
Changes in one prey species' density can indirectly affect the abundance of another prey species if a shared predator eats both species leading to positive or negative indirect effects. In some cases, indirect effects may occur when prey move into a habitat, such as when riparian predator populations grow in response to adult aquatic insects and increase predation on terrestrial prey. However, predators could instead switch to aquatic insects or become satiated, reducing predation on terrestrial prey. To determine the net indirect effect of aquatic insects on terrestrial arthropods via generalist spider predators, we conducted a field experiment using enclosures on the shoreline of an Icelandic lake with numerous aquatic midges. Midge abundance and wolf spider density were altered to mimic midge influx and a wolf spider numerical response. At all predator densities, the presence of midges decreased rates of predation on terrestrial prey. When midges were absent, predation was 30percent greater at high spider density. But when midges were present, predation of sentinel prey was equal across spider densities, negating the influence of increased predator density. In lab mesocosms, prey survivorship increased greater or equal 50percent where midges were present and rapidly saturated; the addition of 5, 20, 50 and 100 midges equivalently reduced spider predation, supporting predator distraction rather than satiation as the root cause. Our results demonstrate a strong positive indirect effect of midges, and broadly support the concept that predator responses to alternative prey are a major influence on the magnitude and direction of predator-mediated indirect effects.
LTREB experimental chironomid mesocosms at Myvatn, Iceland
During the summer of 2014, we conducted experiments testing whether increasing numbers of chironomid larvae would increase primary production and standing chlorophyll a concentrations. We incubated experimental mesocosms with varying numbers of chironomid larvae for 12 days in July. We tested sediments for chlorophyll a concentrations, as sediments are primarily composed of benthic diatoms. We tested the oxygen production in these mesocosms. We did this by sealing the mesocosms and incubating them in Lake Myvatn for 3 hours, and taking measurements of dissolved oxygen before and after the incubations. We were also interested in whether this increase in food resources might translate to increased growth rates of chironomid larvae at high larval densities. After stocking experimental mesocosms with varying numbers of chironomid larvae, we set these mesocosms in Lake Myvatn for 12 days. We collected the larvae at the end of the 12 day experiment and obtained the average dry weights of the Chironomus islandicus larvae in each mesocosm. We hypothesized that the tubes that chironomid larvae build would be a superior substrate for algal growth, as compared to loose sediments. Because there are two taxa (Chironomus islandicus and Tanytarsus gracilentus) that are overwhelmingly dominant at our study site, we wondered whether there would be differences in this effect between the two species. We stocked mesocosms with larvae from one of the two species, and mesocosms were then incubated in Lake Myvatn. We collected sediments and larval tubes from each mesocosm and tested their chlorophyll a concentrations. We hypothesized that one mechanism that chironomid larvae might alleviate algal nutrient limitation by depositing concentrated nutrients near algae in the form of larval excretions. We collected chironomid larvae from Lake Myvatn and placed them in distilled water. We then sieved out the larvae and their fecal passings, and transported the water samples to Madison, WI, USA,
Iceland as stepping stone for intercontinental spread of highly pathogenic avian influenza H5N1 virus between Europe and North America: data set on phylogeographic analysis
<p>Highly pathogenic avian influenza viruses (HPAIV) subtype H5 clade 2.3.4.4b have widely spread within the northern hemisphere since 2020 and threaten wild bird populations as well as poultry production. For the very first time, HPAIV were detected in wild birds and, subsequently, in poultry holdings in Iceland.</p> <p>Here, we present phylogeographic evidence that Iceland has been used as a stepping stone for HPAIV translocation from Northern Europe to North America in 2021 and describe two independent incursions of HPAI H5N1 clade 2.3.4.4b viruses of two different genotypes to Iceland in 2021 and 2022.</p>
Methane concentrations and oxidation rates in land-terminating glacial runoff: measurements from three glacial rivers and a paraglacial lake in Iceland and a literature review
<div> <p>This dataset contains methane measurements from Icelandic lakes and rivers during the summer of 2018 and 2019. This includes data from net methane oxidation assays with sediment and overlying water from one paraglacial lake and one glacial river, and surface methane concentration data from grab samples in 3 glacial streams and 15 Icelandic lakes (1 of which is paraglacial). The dataset also contains methane concentration data from a synthesis of relevant aquatic ecosystems, used to compare against the original measurements collected. </p> </div> <div> <p>Data and Literature Review Synthesis is supplement to Strock et al. 2024 <em>Oxidation is a potentially significant methane sink in land-terminating glacial runoff</em> published in Nature Scientific Reports. </p> <div> <p>This study was funded by: National Geographic Society Changing Polar Systems grant (CP4-162R-18); In-kind support from the U.S. Geological Survey; Dickinson College Research and Development; Churchill Exploration Fund at Dickinson College </p> </div> </div>
LTREB Biological Limnology at Lake Myvatn, Iceland, 2012-2025
These data are part of a long-term monitoring program at Lake Myvatn, Iceland. The program was designed to characterize import benthic and pelagic variables across years as chironomid midge populations varied in abundance. Starting in 2012 samples were taken at roughly ten-day intervals during June, July, and August at a central location in the lake. Starting in 2015, additional five sites representing dominant habitat types were sampled generally three times each year. The dataset also includes occasional winter samples under ice.
Geothermal heat source estimations through ice flow modelling at Mýrdalsjökull, Iceland - Datasets
<p>This repository contains data used in the study "<em>Geothermal heat source estimations through ice flow modelling at</em><br><em>Mýrdalsjökull, Iceland", </em>to be published in <strong>The Cryosphere. </strong>A detailed reference will be added after publication.</p> <p>Details on processing of the data and the creation of the simulated data can be found in the aforementioned publication.</p> <p><strong>Data Specifications:</strong></p> <ul> <li>Cartographic projection: ISN93 / Lambert 1993 (EPSG:3057, <a href="http://https/epsg.io/3057">https://epsg.io/3057</a>)</li> <li>Origin of Elevation: meters above GRS80 ellipsoid (WGS84)</li> <li>Raster data format: GeoTIFF</li> <li>Pléiades dataset includes only DEMs because the Pléiades ortho imagery is for licensed use only. Please contact the authors for further information on this.</li> </ul> <p><strong>File descriptions:</strong></p> <ul> <li><em><strong>bedrock_Magnusson_etal_2021.tif: </strong></em>contains bedrock data published by Magnússon et al. 2021 for the simulation domain used in the paper. See reference below.</li> <li><em><strong>surface_27092016_pleiades.tif: </strong></em>contains glacier surface data from September 27th, 2016 which is used as a starting geometry for the simulations described in the paper. This data is based on Pléiades satellite images.</li> <li><em><strong>surface_01092017_pleiades.tif: </strong></em>contains glacier surface data from September 1st, 2017 which is used as a reference target geometry for the simulations described in the paper. This data is based on Pléiades satellite images.</li> <li><em><strong>HM_run04.tif:</strong></em> contains the best fitting simulation based surface which was compared to <em><strong>surface_01092017_pleiades.tif </strong></em>in the paper.</li> <li><em><strong>HM_run04_hillshade.png: </strong></em>a simple hillshade image for preview purposes.</li> </ul> <p> </p>
DATABASE OF THE DIGITAL ELEVATION MODELS OF THE SKEIÐARÁRSANDUR KETTLE-HOLES (S ICELAND), JUNE 2022 - PART I
<p>The database concerns kettle-holes of glacial flood origin. They are located at various outwash levels of Skeiðarársandur in S Iceland. The database contains 87 digital elevation models (DEM) with a minimum resolution of 0.05 m and additional files, e.g. field measurements data, frames selected from the video, errors calculation, point cloud, 3D view. These data document the process of obtaining the material using the photogrammetric ‘Structure from Motion’ method from fieldwork conducted in June 2022 through the processing stages in free, mainly open-source software. The data is prepared in the local Cartesian system and includes relative heights, where 0 m is the lowest point of the kettle-hole. The simple technique used, based on filming the landforms with a digital camera, enables mapping of depressions up to 1250 m<sup>2</sup> in the area and a maximum depth of up to 8 m with the assumed high accuracy.</p>
Ontolex-lemon and TIAD versions of Apertium Icelandic-Swedish dictionary
<p>OntoLex-lemon and TSV conversion of Apertium Bidix. For more details, see <a href="https://www.aclweb.org/anthology/2020.lrec-1.401/">https://www.aclweb.org/anthology/2020.lrec-1.401/</a></p> <p>Authors of the original data:</p> 2010-2013, Tihomir Rangelov 2011-2013, Francis M. Tyers 2013, Kevin Brubeck Unhammer 2013, Trond Trosterud 2014, Tino Didriksen
Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages
<p><strong>Introduction:</strong></p><p>On the 10th of July 2023, at 16:40, an eruption started in the Reykjanes Peninsula, Iceland, next to the mountain "Litla-Hrútur". As part of the response, the CIEST2 french initiative was activated (Gouhier et al., 2022). Once activated, Pléiades stereoimages were tasked and scheduled for fast delivery within the area of Interest. On the 20th of August 2023 an additional stereopair of images from Pléiades was acquired and processed after the eruption had stopped.</p><p>Once acquired and delivered, the Pléiades images were processed following the methods described in the section below. This repository contains the near-real time results of DEMs, difference maps compared to a pre-eruption DEM, and lava outlines digitized from the difference map and the orthoimage.</p><p> </p><p><strong>Methods</strong>:</p><p>The Pléiades stereoimages were processed using the Ames StereoPipeline (ASP, Shean et al., 2016, see ASP branch in repository), yielding a DEM in 2x2m GSD and an orthoimage in 0.5x0.5m GSD. The processing was done using as only input the stereoimages and their orientation information, as Rational Polynomial Coefficients (RPCs). The <i>parallel_stereo </i>routine performs all the steps needed in the correlation of the stereoimages, yielding a pointcloud which is then interpolated using the routine <i>point2dem</i>. Besides default parameters, the <i>parallel_stereo</i> parameters used for creation of the DEMs were the standard parameters, plus the following ones: </p><p><i>--stereo-algorithm asp_mgm --corr-tile-size 300 --corr-timeout 900 --cost-mode 3 --subpixel-mode 9 --corr-kernel 7 7 --subpixel-kernel 15 15</i></p><p>Once the DEM was created, DEM co-registration was applying in order to align and minimize positional biases between the pre-eruption DEM and the Pléiades DEMs. We followed the co-registration method of Nuth & Kääb (2011), implemented by David Shean's co-registration routines (<a href="https://github.com/dshean/demcoreg">https://github.com/dshean/demcoreg</a>, Shean et al., 2016). The co-registration involved a horizontal and vertical shift of the Pléiades DEMs, as well as a planar tilt correction. The horizontal offset obtained from the DEM co-registration was also applied to the Pléiades orthoimages.</p><p>The pre-eruption DEM used for this study is a survey done on the 27th of September 2022, data collected Birgir Óskarsson and Robert A. Askew (Icelandic Institute of Natural History) and processed by Sydney R. Gunnarsson and Joaquín M.C. Belart (National Land Survey of Iceland). Metadata of this dataset is available here: https://gatt.lmi.is/geonetwork/srv/eng/catalog.search#/metadata/c59da6cf-18ee-44af-a085-afbad0de029a</p><p>Lava outlines were manually digitized from the co-registered Pléiades orthoimages, The lava outlines are available as GeoPackages in the "GPKG" branch of the repository.</p><p>At the moment, the results from Pléiades are used by the Institute of Earth Sciences of the Univesity of Iceland (Jarðvisindustofnun Háskoli Íslands) to estimate lava volumes and effusion rate, following the methods described in Pedersen et al. (2022). Please contact the authors if these data are intended to be used for a similar purpose, in order to avoid conflict of interests or duplicate work. We encourage collaboration and data sharing for the purpose of the monitoring of the eruption and for research applications.</p><p><strong>Data naming convention:</strong></p><p>faf_YYYYMMDD_hhmmss_hhmmss_*align.tif: DEM obtained from the processing, co-registered to the reference pre-eruption DEM.</p><p>faf_YYYYMMDD_hhmmss_hhmmss_*align_diff.tif: Difference of elevation between the Pléiades DEM and the pre-eruption DEM.</p><p>faf_YYYYMMDD_hhmm.gpkg: Polygon containing the lava outlines, extracted from the Pléiades orthoimage and the map of elevation difference.</p><p>0_faf_YYYYMMDD_hhmmss_hhmmss_*fig.png: A figure showing the latest map of elevation difference, overlaid with a hillshade of the latest Pléiades DEM and the latest lava outlines, result of the processing of the Pléiades stereoimages. The figure was created using the tool imviewer.py from the GitHub repository https://github.com/dshean/imview (Shean et al., 2016).</p><p><strong>Data Specifications:</strong></p><ul><li>Cartographic projection: ISN93 / Lambert 1993 (EPSG:3057, <a href="http://https:/epsg.io/3057">https://epsg.io/3057</a>)</li><li>Origin of Elevation: meters above GRS80 ellipsoid (WGS84)</li><li>Raster data format: GeoTIFF</li><li>Raster compression system: LZW</li><li>Vector data format: GeoPackage (<a href="https://www.geopackage.org/">https://www.geopackage.org/</a>)</li><li>Pléiades dataset includes only DEMs because the Pléiades ortho imagery is for licensed use only. Please contact the authors for further information on this.</li></ul><p><strong>Acknowledgements</strong>: </p><p>Pléiades images from July 2023 were provided under the CIEST² initiative (CIEST2 is part of ForM@Ter (<a href="https://en.poleterresolide.fr/">https://en.poleterresolide.fr/</a>). Pléiades images from August 2023 were provided under the CEOS Volcano Supersite (https://ceos.org/ourwork/workinggroups/disasters/gsnl/). Image Pléiades©CNES2023, distribution AIRBUS DS.</p><p><strong>Dataset Attribution</strong>:</p><p>This dataset is licensed under a <a href="https://creativecommons.org/licenses/by-nc/4.0/">Creative Commons CC BY-NC 4.0 International License</a> (Attribution-NonCommercial).</p><p><strong>Citation:</strong></p><p>Please cite this repository as described below:</p><p>Joaquin M.C. Belart, Virginie Pinel, Hannah. I. Reynolds, Etienne Berthier, & Sydney R. Gunnarson. (2023). Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages (1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10133203</p>
Wikipedia: wikipedia-is (Icelandic)
Wikipedia is a multilingual, web-based, free-content encyclopedia project supported by the Wikimedia Foundation and based on a model of openly editable content. EOL harvests articles from wikipedia that are indexed as species or higher taxa.<p></p><p></p>https://is.wikipedia.org
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - Iceland
<p>This dataset contains TSE surveillance results in cattle, sheep, goats, cervids and other species, and genotyping in sheep, pursuant to Regulation (EC) 999/2001.</p> <p><strong>Reporting authorities contributing to each data collection</strong>:</p> <ul> <li>TSE_2023_IS: Icelandic Food and Veterinary Authority (MAST)</li> <li>TSE_2022_IS: Icelandic Food and Veterinary Authority (MAST)</li> <li>TSE_2021_IS: Icelandic Food and Veterinary Authority (MAST)</li> <li>TSE_2020_IS: Icelandic Food and Veterinary Authority (MAST)</li> <li>TSE_2019_IS: Icelandic Food and Veterinary Authority (MAST)</li> </ul>
Relative abundance of the CHC extracts of each population replicate's of I. uriae ticks from Iceland after log centered ratio transformation
<p>Relative abundance of the CHC extracts of each population replicate’s of I. uriae ticks from Iceland after log centered ratio transformation.</p>
Combining Horizontal Strain DAS and Local Seismic Stations in a Full Waveform Attribute Stacking Detector/Locator Algorithm: Verification Test for the Thorbjörn, Iceland, 2020 Unrest Episode
<p>We present a waveform stacking-based earthquake catalog of the seismicity unrest episode in the Svartsengi fissure swarm close to Mt. Thorbjörn, SW Iceland, which started in January 2020 and was still ongoing in January 2021. The magmatic unrest produced more than 5 earthquake swarms comprising thousands of individual events each. We were able to combine local and regional seismic networks with 6 months recording of a 17 km long distributed acoustic sensing (DAS) fibre optical cable with a channel resolution of 4 m. The kHz DAS data were downsampled to 200 Hz and stacked every 64 m. The catalog is based on a migration-based detector / locator technique as for instance implemented in Lassie (Pyrocko). In the accompanying we demonstrate the robustness in a wide variety of applications in seismology. For this dataset, we have extended Lassie to efficiently combine linear ultra-dense sensor arrays with sparse seismological networks.</p>
Mechanism of landslide induced by glacier-retreat on the Tungnakvíslarjökull area, Iceland
<p><strong>Introduction</strong></p> <p>This repository contains the data used for the study of the slope instability of Tungnakvíslarjökull, Iceland, described in Lacroix et al. (submitted). Specifically, the repository contains three time series in Tungnakvíslarjökull:</p> <ol> <li> <p>Time series of Digital Elevation Models (DEMs) from ASTER, 2000-2020.</p> </li> <li> <p>Time series of horizontal ground displacements, 1999-2019.</p> </li> <li> <p>Time series of earthquakes, 1995-2019.</p> </li> </ol> <p>Finally, we provide the map of the rate of elevation difference and the map of horizontal ground displacements for the whole period 2000-2019, as shown in Figure 1 of Lacroix et al. (submitted).</p> <p>The data and methods used for the elaboration of this data repository are described in detail in Lacroix et al. (submitted). In this repository we also provide a short summary and overview of the data and methods used.</p> <p><strong>Data</strong></p> <p>A total of 160 ASTER scenes were used to produce the time series of DEMs. A series of images from SPOT1, Landsat-7, ASTER and Landsat-8 was used in order to produce the horizontal ground displacements maps. The South-Iceland Lowlands (SIL) network (Jóndsdóttir et al., 2007) was obtained from Veðurstofan Íslands (www.vedur.is). Table 1 provides an overview of these data.</p> <table> <caption>Table1: Data used for the creation of this repository</caption> <tbody> <tr> <td>Application</td> <td>Platforms</td> <td>Acquisition dates</td> </tr> <tr> <td>DEM</td> <td>ASTER</td> <td>160 scenes from 2000-10-16 to 2020-08-27. <p>Format for the date is YYYYMMDD</p> </td> </tr> <tr> <td>Horizontal ground displacement</td> <td>SPOT1</td> <td>1987-08-05</td> </tr> <tr> <td> </td> <td>Landsat-7</td> <td>1999-07-26, 2000-08-20, 2001-09-24, 2002-07-09</td> </tr> <tr> <td> </td> <td>ASTER</td> <td>2003-08-04, 2004-09-18, 2007-08-15, 2011-08-10, 2013-07-24, 2014-08-18, 2016-08-07</td> </tr> <tr> <td> </td> <td>Landsat-8</td> <td>2014-08-12, 2015-09-16, 2016-08-24, 2017-08-20, 2018-09-14, 2019-08-10</td> </tr> <tr> <td>Seismicity</td> <td>SIL network</td> <td>370491 events recorded between 1995-2019 in the Mýrdalsjökull (S-Iceland) area and surroundings</td> </tr> </tbody> </table> <p><strong>Methods</strong></p> <p>The DEMs were created using the Ames StereoPipeline (ASP, Shean et al., 2016) with the same setup as used in Brun et al., (2017). Each DEM was then co-registered to a lidar DEM acquired in 2010 (Jóhannesson et al., 2013), using the co-registration methods from Berthier et al. (2007), and adding an across-track fifth-degree polynomial correction (Gardelle et al., 2013). The stack of elevations obtained from the DEM time series was linearly fitted in order to produce the map of elevation difference (file name 20000101_20210101_30x30m_UTM27N_DHDT_Lacroixetal2022.tif) of the period 2000-2020.</p> <p>The horizontal ground displacement maps were created using the offset tracking methodology described in Bontemps et al. (2018), consisting of: (1) pairwise image correlation using Mic-Mac (Rupnik et al., 2017), (2) masking of areas with low correlation coefficients (3) correction of co-registration bias by subtracting the mean values of the NS and EW displacement fields and (4) pixelwise fit of the horizontal ground displacements by least squares, using the time interval between measurements as weights and obtaining the full horizontal ground displacement for the analyzed period (file name 19990726_20200101_15x15m_UTM27N_HGD_Lacroixetal2022.tif)</p> <p>The time series of earthquakes obtained from the SIL network was filtered, and 2089 earthquakes with depth <5 km and magnitude <1.7 were used in this study and data repository (file name 19950814_20181118_SILvedur_time_lon_lat_dep_mag.txt).</p> <p><strong>Acknowledgements</strong></p> <p>We thank Bryndís Brandsdóttir for providing the seismic data used in this repository. E.B. and P.L. acknowledge the support from the French Space Agency (CNES) through the TOSCA, PNTS, SWH and ISIS programs.</p> <p><strong>Dataset attribution</strong></p> <p>This dataset is licensed under a Creative Commons CC BY 4.0 International License.</p> <p><strong>Dataset Citation</strong></p> <p>Lacroix, P., Belart, J.M.C., Berthier, E., Sæmundsson, Þ., Jónsdóttir, K.: Data Repository: Mechanism of landslide induced by glacier-retreat on the Tungnakvíslarjökull area, Iceland. Dataset distributed on Zenodo: 10.5281/zenodo.6388069</p>
40Ar/39Ar dating of the Barmur Group (Tjörnes beds), northern Iceland.
<p><sup>40</sup>Ar/<sup>39</sup>Ar radiometric ages and whole-rock major element data from four basaltic lavas that underlie, are intercalated with, and overlie the Barmur Group (Tjörnes beds), northern Iceland.</p>
UAV Laser Scanning surveys of the lake terminating glacier Fjallsjokull in SE Iceland, captured in July, 2021.
<p>This dataset consists of 5 separate laser scanning surveys performed between the 8th and 15th July, 2021. Two surveys were conducted in the morning and afternoon of the 8th and the 9th, and then only the morning of the 15th. The point clouds have been cleaned to remove erroneous points. The point clouds were processed using the methods and code available at <a href="https://github.com/christomsett/Direct_Georeferencing">Direct_Georeferencing</a>. All point clouds are georeferenced in the projected WGS 1984 UTM 28N system, and provided in the widely used compressed 'laz' format. An accuracy assessment of the data showed that all surveys were consistent to within 0.1 m of each other, apart from the second flight (afternoon) on the 8th July. Any users of this data should be aware of its limitations in a challenging cryospheric environment. </p>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Iceland
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
Processed UAV orthomosaics and DEMs of Fjallsjökull, southeast Iceland (2 of 2)
<p>Orthomosaics of the lower ice surface of Fjallsjökull, southeast Iceland, produced from high resolution UAV surveys undertaken in July 2021. This data was produced as part of my PhD research, and therefore, forms a significant component of my final PhD thesis.</p> <p>All files are in UTM Zone 28N. The resolution of the all the uploaded orthomosaics in this dataset is <strong>0.02 m</strong>. </p> <p>Please note this is dataset 2 out of 2 (due to the 50 GB limit of file uploads). The DEMs and orthomosaics from 2019, DEMs from 2021, as well as three of the orthomosaics from 2021, have been uploaded to dataset 1 of 2 (DOI: 10.5281/zenodo.7105133). </p> <p>For reference, this dataset includes the orthomosaics produced from the following days in July 2021 (in separate files): </p> <p><strong>1)</strong> 8th</p> <p><strong>2) </strong>9th</p> <p><strong>3) </strong>10th</p> <p><strong>4) </strong>11th</p> <p><strong>5)</strong> 12th</p> <p><strong>6)</strong> 15th</p>
H2020 PrimeFish National Level Competitiveness Iceland Norway Spain Vietnam Newfoundland
<p>The data set contains data on individual indicators of national seafood competitiveness. Data are collected as part of the EU H2020 project PrimeFish (grant no 635761). The analysis follows the general framework of the annual World Economic Forum Competitiveness Report. Indicators are taken from three sources; directly from the World Economic Forum report, survey among national experts and hard data such as stock sizes and wages. All data are numeric, and on a 1-7 scale. Data were collected from the World Economic Forum 2017 competitiveness report and surveys and hard data collected in 2017.</p> <p> </p> <p>Indicators are grouped in several catergories, that again are grouped in higher level categories, ultimately yielding a single competitiveness indicator for the seafood sector.</p>
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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.