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1,579 results for “Baltics”
Supplementary material for "Tracing emerging contaminants from the Baltic Sea and North Sea in fjord waters in southern Norway with rare earth elements as far-field tracers"
<p><span>Dataset presented and discussed in the manuscript of the research article “</span><span>Tracing emerging contaminants from the Baltic Sea and North Sea in fjord waters in southern Norway with rare earth elements as far-field tracers</span><span><span>” by Zocher et al. The manuscript will be submitted to <em>Environmental Pollution</em> and was prepared by the following authors: </span></span></p> <p> </p> <p><span><span>Anna-Lena Zocher (1), Tomasz Maciej Ciesielski (2,3), Stefania Piarulli (4), Julia Farkas (4) and Michael Bau (1). </span></span></p> <p><span> </span></p> <p><span><span>(1) School of Science, Constructor University, Bremen, Germany</span></span></p> <p><span><span>(2) Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway</span></span></p> <p><span><span>(3) </span></span><span><span>Department of Arctic Technology, The University Centre in Svalbard (UNIS), Longyearbyen, Norway</span></span></p> <p><span><span>(4) SINTEF Ocean, Trondheim, Norway</span></span></p> <p> </p> <p><span>This work was conducted within the ELEMENTARY project, and we appreciate funding from the Norwegian Research Council (grant No. 301236).</span></p>
Supplementary material for "Rare earth elements and yttrium in Polish rivers and the input of anthropogenic gadolinium into the Baltic Sea"
<p>This dataset is presented and discussed in the research article “Rare earth elements and yttrium in Polish rivers and the input of anthropogenic gadolinium into the Baltic Sea” by Alemu et al. This manuscript will be submitted to Environmental Pollution and was prepared by the following authors: Addis Kokeb Alemu (1,2), Keran Zhang (1), David Ernst (1), and Michael Bau (1). </p> <p>1Critical Metals for Enabling Technologies – CritMET, School of Science, Constructor University, Campus Ring 1, 28759 Bremen, Germany</p> <p>2Department of Chemistry, College of Natural and Computational Sciences, University of Gondar, P.O. Box 196, Gondar, Ethiopia</p> <p> </p> <p> </p> <p>Table A1 includes the general information and data for all sampling stations and reference materials used. </p> <p>Figs. A1 and A2 show the concentrations of total Gd and anthropogenic Gd in samples from the Oder River (OD) and its major tributary, the Warta River (Wa), as well as the Vistula River (VS) and its major tributaries: San (Sn), Bug (BG), Brda (BR), and Narew (NR).</p>
Compilation of 17 anthropogenic pressure gradients and 18 benthic indicators in the Baltic Sea, Atlantic Ocean and Mediterranean Sea
<p>Compilation of 17 benthic datasets that sampled benthic ecosystems over gradients of commercial bottom trawling intensity (n=14), eutrophication (n=1), oxygen depletion (n=1) and pollution (n=1) (Table 1).</p> <p>Compilation of 18 benthic indicators that were calculated for each gradient dataset. The indicators estimated were community biomass, abundance, richness, relative Margalef diversity, Shannon index, Simpson index, Inverse Simpson, AZTI’s Marine Biotic Index (AMBI), Multivariate AMBI (M-AMBI), BENTIX Biotic Index (BENTIX), Danish Quality Index (DKI), Trawling Disturbance Index (TDI), Modified TDI (mTDI), Modified vulnerability index (mT), Median longevity (Lm), Partial TDI (pTDI), Sentinels of Seabed (SoS), Long-lived fraction (Lf).</p> <p>The dataset has information on: 1) indicator outputs per sampling station; 2) combined data tables with gradient, station, and species information; 3) individual gradient information with replicate samples and the environmental variables reported in the original study.</p> <p>#----------------</p> <p>NOTE: The dataset was updated in February 2025 due to incorrect description of units used for two gradients (Silver Pit and Thames) in the "Individual Gradient Studies" folder.</p> <p>#---------------</p> <p>Table 1. Overview of anthropogenic gradient datasets</p> <table> <tbody> <tr> <th>Location</th> <th>Sampling method</th> <th>Pressure gradient</th> </tr> </tbody> <tbody> <tr> <td>Adriatic Sea – Italian EEZ (sand)</td> <td>Rapido trawl</td> <td>Bottom trawling</td> </tr> <tr> <td>Adriatic Sea – Italian EEZ (mud)</td> <td>Rapido trawl</td> <td>Bottom trawling</td> </tr> <tr> <td>North Sea - Dutch EEZ</td> <td>Box core</td> <td>Bottom trawling</td> </tr> <tr> <td>North Sea - Dogger Bank</td> <td>Hamon grab</td> <td>Bottom trawling</td> </tr> <tr> <td>North Sea - Fladen Ground</td> <td>Day grab</td> <td>Bottom trawling</td> </tr> <tr> <td>North Sea - Long Forties</td> <td>Hamon grab</td> <td>Bottom trawling</td> </tr> <tr> <td>North Sea - Silver Pit</td> <td>Box core</td> <td>Bottom trawling</td> </tr> <tr> <td>North Sea – Thames</td> <td>Box core</td> <td>Bottom trawling</td> </tr> <tr> <td>Northern Iberian Coast (sand)</td> <td>Otter trawl</td> <td>Bottom trawling</td> </tr> <tr> <td>Northern Iberian Coast (mud)</td> <td>Otter trawl</td> <td>Bottom trawling</td> </tr> <tr> <td>Baltic Sea - Gotland</td> <td>van Veen grab</td> <td>Bottom trawling</td> </tr> <tr> <td>Baltic Sea – Polish EEZ</td> <td>Box core</td> <td>Bottom trawling</td> </tr> <tr> <td>NW Atlantic - Flemish Cap</td> <td>Otter trawl</td> <td>Bottom trawling</td> </tr> <tr> <td>Irish Sea - Sellafield</td> <td>Day grab</td> <td>Bottom trawling</td> </tr> <tr> <td>Gulf of Finland</td> <td>van Veen grab</td> <td>Oxygen depletion</td> </tr> <tr> <td>Saronikos Gulf</td> <td>Box core</td> <td>Eutrophication</td> </tr> <tr> <td>Vigo Estuary</td> <td>Box core</td> <td>Contaminants</td> </tr> </tbody> </table>
Combined data file for Jilbert et al. "Anthropogenic Inputs of Terrestrial Organic Matter Influence Carbon Loading and Methanogenesis in Coastal Baltic Sea Sediments", Frontiers in Earth Science 9, 2021
<p>The datafile contains all the new raw data presented in the figures in the publication.</p>
Bathymetry data from detonation scars in the Fehmarnbelt, German Baltic Sea.
<p>The bathymetric data were collected on the 27<sup>th</sup> of June 2020 as underway research data on a 1.5 km track during the cruise EMB239 with the German research vessel Elisabeth Mann Borgese. The objective of the data acquisition was to survey seafloor scars resulting from the controlled detonation of ground mines. For data acquisition, the ship’s hull-mounted Sonic 2024 (R2Sonic Inc.) multibeam echosounder was used. The raw sonar data were loaded in Qimera v2.4.3 (Quality Positioning Services B.V.) and automatically processed to compute sounding footprint location under consideration of sound velocity, position, motion, and heading information. To make the data usable without any specific software, the georeferenced soundings were exported without any bathymetric data cleaning as comma-separated ASCII file in the coordinate reference system EPSG: 32632 - WGS84 / UTM zone 32N.</p> <p>For more details please refer to Papenmeier, S., Darr, A., Feldens, P. (in prep): Geomorphological data from detonation craters in the Fehmarnbelt, German Baltic Sea.</p>
Appendix 1. Revelieria groehni Sergi, Perkovsky et Reike, 2013, female, Baltic amber, JDC-9116 [JDC], X-ray microtomography volume rendering of the habitus.
<p>X-ray microtomography volume rendering of the habitus of Revelieria groehni Sergi, Perkovsky et Reike, 2013, female, Baltic amber, JDC-9116 [JDC].</p>
Appendix 2. Revelieria groehni Sergi, Perkovsky et Reike, 2013, female, Baltic amber, JDC-9116 [JDC], X-ray microtomography volume rendering of the forebody.
<p>X-ray microtomography volume rendering of the forebody of Revelieria groehni Sergi, Perkovsky et Reike, 2013, female, Baltic amber, JDC-9116 [JDC].</p> <p> </p>
Fig. 5 in A New Species Of Globicornis (Hadrotoma) (Coleoptera, Dermestidae, Megatominae) From Baltic Amber
Fig. 5. Head and prothorax lateral aspect, prosternum indicated by arrow.
October 2019 700 kHz multibeam echo sounder data used for Seasonal Change of Multifrequency Backscatter in three Baltic Sea Habitats
<p>The raw data used for the study</p> <p>Seasonal Change of Multifrequency Backscatter in three Baltic Sea Habitats</p> <p>by Schulze et al.; currently under review at Frontiers in Remote Sensing. </p> <p> </p> <p>Files are stored in the s7k-Format, and sorted by date of acquisition and frequency. 200 and 400 kHz data were manufacturer-calibrated. Correct absorption values have been applied duirng the export. Refer to the paper for further dataset information.</p> <p> </p> <p>This upload stores the 700 kHz data recorded in October 2019.</p>
Retracing Cyanobacteria Blooms in the Baltic Sea
<p>This repository is the data supplement to</p> <p>"Retracing Cyanobacteria Blooms in the Baltic Sea" by U. Löptien and H. Dietze 2022 in Nature Scientific Report doi:.</p> <p>The files named<strong> </strong><strong><a href="https://zenodo.org/api/files/6ae9260c-42d5-4496-aa26-348f4f898d60/backtrace_2010.mov">backtrace_20**.mov </a></strong><strong> </strong>feature visualizations of of lagrangian particles that were randomly seeded within blooms (indicated by cyan crosses) and outside blooms (indicated by grey circles). The trajectories of these particels are backtraced using output of the general ocean circulation model <a href="https://doi.org/10.5194/gmd-7-1713-2014">MOMBA</a>. The background color shading indicates surface mixed layer depth.</p> <p>The <a href="https://en.wikipedia.org/wiki/MATLAB">Matlab</a> data files named<strong> <a href="https://zenodo.org/api/files/6ae9260c-42d5-4496-aa26-348f4f898d60/trajectV03_8_2010.mat">trajectV03_8_20**.mat </a></strong> contain 2-D matrices DD (distance from coast), MD (surface mixed layer depth), SOLD (solar radiation), TD (temperature), XD (longitude), YD (latitude) with lines and columns corresponding to timesteps and lagrangian particles, respectively. Icy and Inocy are index vectors indicating which of the columns refer to blooming and "not blooming" particles, respectively. timY, timM, timH and timD refer to Year, Month, Day and Hour of respective lines of the 2-matrices, respectively.</p> <p>Don't hesitate to contact ulrike.loeptien@ifg.uni-kiel.de or heiner.dietze@ifg.uni-kiel.de in case of confusion.</p> <p> </p> <p> </p>
Baltic Sea stable isotope ecology meta-data collection
<p>Stable isotope analysis (SIA) has become a pivotal method in food web and ecological research, leading to the establishment of the research field "stable isotope ecology". We conducted the first systematic review of stable isotope studies in this field in the Baltic Sea macro-region (Eglite et al. 2022). The meta-data collection provided here includes the information extracted from all 164 studies identified in the systematic review across various dimensions (topic, space, time, taxonomic, and technical focus), but not primary stable isotope data. The first published version of this meta-data collection represents the status as of July 10, 2021, and was used to filter and extract meta-data to produce the figures and tables in the review by Eglite et al. (2022). The meta-data collection is a resource for both experienced isotope ecologists and newcomers to grasp and access all published Baltic Sea SIA work on any fundamental or applied research topic, sub-region, taxon, or trophic group of interest. It also represents an ideal foundation for an envisioned "Baltic Isobank" database of primary stable isotope data, following the vision outlined in Eglite et al. (2022). We will provide regular updates of the meta-data collection in the Dryad repository, based on new runs of the systematic review query and including any additions of research papers and corrections received from the stable isotope ecology community. For this purpose, we encourage researchers to inform us about newly published research papers employing stable isotopes in the Baltic Sea ecology field by sending an e-mail with the publication reference to baltic-isobank@geomar.de.</p>
Figs 1–8 in A new genus of the subfamily Languriinae (Coleoptera: Erotylidae) from the Late Eocene Baltic amber
Figs 1–8. Photomicrographs of Thallisellites olgae sp. n., holotype, No UCP UwB 1701.
Baltic Brass Swastika
Baltic Brass Swastika - PBR Game Ready low-poly 3d model ready for Virtual Reality (VR), Augmented Reality (AR), games and other real-time apps. Single mesh. Includes texture sets ready for Unreal Engine 4 and Unity 5. Purchase includes: .dae model High and Low poly .fbx models PBR Texture Set: Albedo Ambient Occlusion Metallic Normal Roughness Textures are available in 2k. Source: Objaverse 1.0 / Sketchfab
Baltic Sea Region Land Cover Plus - Training and Validation data
<p>Training and validation data used in creating Baltic Sea Region Land Cover Plus (BSRLC+) maps: <a href="https://doi.org/10.5281/zenodo.10653871" target="_blank" rel="noopener">Dataset link</a></p> <ul> <li><strong>landcover_training_data_2006_2018.gpkg</strong>: Points data of consistent land cover from 2006 to 2018</li> <li><strong>crop_training_data_{year}.gpkg</strong>: Points data of crop types derived from <a href="https://doi.org/10.1038/s41597-023-02517-0">EuroCrop dataset </a>in particular year (2019, 2021, 2023)</li> <li><strong>landcover_validation_{year}.gpkg</strong>: Points data of validation data derived from <a href="https://doi.org/10.1038/s41597-020-00675-z">LUCAS points </a>in particular year (2009, 2012, 2015, 2018)</li> <li><strong>Metadata.pdf</strong>: Information of land cover code in each dataset</li> </ul> <p>Version notes:</p> <p>Version 2: Correcting the validation data 2018 and Metadata file</p> <p>Version 1: Original upload</p>
Impact of persistently high sea surface temperatures on the rhizobiomes of Zostera marina in a Baltic Sea benthocosms
Open the record for dataset details and reuse information.
Marine seismic multichannel data collected in the Pomeranian Bay and around Rügen (southern Baltic Sea) by University of Hamburg
<p>The dataset includes multi-channel seismic data collected during various marine student training cruises. The cruises were organized and led by the Institute of Geophysics at the University of Hamburg.</p> <p>The seismic sources were GI-Guns or Mini-GI-Guns from the company SODERA. The data was recorded with various analog streamer systems. All data are poststack time-migrated with suppressed seafloor multiples.</p> <p>All data are in SEG-Y format with CDP-coordinates at standard byte positions (UTM33)</p> <table> <tbody> <tr> <td> <p>Vessel</p> </td> <td> <p>Cruise-ID</p> </td> <td> <p>Year</p> </td> </tr> <tr> <td> <p>RV ALKOR</p> </td> <td> <p>AL225</p> </td> <td> <p>2003</p> </td> </tr> <tr> <td> <p>RV HEINCKE</p> </td> <td> <p>HE217</p> </td> <td> <p>2004</p> </td> </tr> <tr> <td> <p>RV ALKOR</p> </td> <td> <p>AL263</p> </td> <td> <p>2005</p> </td> </tr> <tr> <td> <p>RV ALKOR</p> </td> <td> <p>AL562</p> </td> <td> <p>2021</p> </td> </tr> <tr> <td> <p>RV ALKOR</p> </td> <td> <p>AL582</p> </td> <td> <p>2022</p> </td> </tr> <tr> <td> <p>RV ALKOR</p> </td> <td> <p>AL605</p> </td> <td> <p>2023</p> </td> </tr> </tbody> </table>
3D model of a small piece of Baltic amber (KM 8) containing four different ant species.
<p>Video S1 of 3D model of a small piece of Baltic amber (KM 8) containing four different ant species. S<span><span><span>pecimen is kept in the collection </span></span><span><span>of the Kaliningrad Amber Museum, Kaliningrad, Russia</span></span></span></p>
Fig. 1. Saphanites mirabilis Vitali, 2011 in Paratimia succinicola sp. n. (Coleoptera: Cerambycidae) from Baltic amber, with palaeogeographical remarks on the tribe Atimiini LeConte, 1873
Fig. 1. Saphanites mirabilis Vitali, 2011, reconstruction.
Dataset for Interannual and seasonal variability of the air-sea CO2 exchange at Utö in the coastal region of the Baltic Sea
<p>Uto Atmospheric and Marine Research Station<br>Finnish Meteorological Institute and Finnish Environment Institute</p> <p>Data Jan 2017 - Dec 2021</p> <p> </p> <p>Data used in:<br>Honkanen, M., Aurela, M., Hatakka, J., Haraguchi, L., <br>Kielosto, S., Mäkelä, T., Seppälä, J., Siiriä, S.-M., <br>Stenbäck, K., Tuovinen, J.-P., Ylöstalo, P., and Laakso, L.: <br>Interannual and seasonal variability of the air-sea CO2 exchange at Utö in the coastal region of the Baltic Sea, <br>EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-628, 2024.</p> <p> </p> <p>This research has been supported by the Research Council of Finland project SEASINK (Evolving carbon sinks and sources in coastal<br>seas – will ecosystem response temper or aggravate climate change? project nos. 317297 and 317298), and the JERICO-NEXT and JERICO-S3 projects which have received funding from the European Union Horizon 2020 Research and Innovation Program under grant agreement nos. 654410 and 871153, respectively.</p>
Fig. 1 in Allium Paradoxum (M.Bieb.) G. Don (Amaryllidaceae) - A New Invasive Plant Species For The Flora Of Baltic States
Fig. 1. Map showing the distribution of Allium paradoxum (M. Bieb.) G. Don. in Latvia.
ScienceDex guides
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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.