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227 results for “Estonia”
Map of soil organic carbon loss of mineral soils in Estonia
<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.</p> <p>The map was generated to evaluate soil organic carbon (SOC) loss in Estonian agricultural soils. It is directly related to SERENA project WP3, T3.2, D3.3 with the aim of applying cookbooks to assess soil threats or ecosystem services. This map is the outcome of applying a cookbook developed by ISRIC (Genova, G., Poggio, L., Kempen, B., & Colman, B. DSM Workflow Seedling. ISRIC - World Soil Information. https://doi.org/10.17027/ISRIC-FSX2-2691).</p> <p>The generated map of SOC loss expressed as absolute sequestration rate (t C ha-1 a-1) between 2015 and 2021 is in GEOTIFF format at the resolution of 100m. The input data for the cookbook was from the PANDA database, which contains regular soil monitoring and voluntary soil sampling data by farmers in Estonia. To achieve the aim for accounting SOC loss in agricultural soils temporal pairs were selected resulting in 1037 paired points where the interval between second sampling was more than 5 years. SOC stocks were calculated for the depth of 20 cm using the equation by Adams (1973) to calculate soil bulk density. The calculated SOC stock for time0 and time2 (> 5 years resampled locations) were used as input points for digital soil mapping, that is the ISRIC cookbook. </p>
EJPSOIL_SERENA: Maps of Soil Organic Carbon Loss Scenarios in Elva Parish, Estonia
<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales. </p> <p>The study examined the effects of winter cropping systems on long-term soil fertility and their potential to mitigate SOC (Soil Organic Carbon) loss compared to bare soil during the winter months. It analyzed changes in SOC stocks (0–30 cm) at the field level in Elva Parish over the period 2020–2040, under different land-use scenarios. The modeling was based on a SOC stock map layer for Estonian mineral arable soils, developed by the Centre of Estonian Rural Research and Knowledge, which represented the baseline conditions in 2020. SOC stock projections were made using the RothC model, which simulates soil carbon turnover. </p> <p>In the first scenario (Scenario 1), the average SOC stock in Elva Parish by 2040 was estimated assuming the land would remain bare, without vegetation, during the winter months from October to April. In the second scenario (Scenario 2), the SOC stock projection accounted for the presence of winter vegetation, which means the soil is covered with vegetation year-round. The dataset includes four files: a projected SOC stock map for Elva Parish in 2040 and the stock changes from 2020–2040 under Scenario 1, along with a projected SOC stock map for 2040 and the stock changes from 2020–2040 under Scenario 2. </p>
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - Estonia
<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_EE: Veterinary and Food Board (VFB)</li> <li>TSE_2022_EE: Veterinary and Food Board (VFB)</li> <li>TSE_2021_EE: Veterinary and Food Board (VFB)</li> <li>TSE_2020_EE: Veterinary and Food Board (VFB)</li> <li>TSE_2019_EE: Veterinary and Food Board (VFB)</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Estonia
<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>
A grid-based spatial database of current and potential mires in Estonia (EstMire)
<p>The EstMire dataset <span>includes </span><span>11,394,461 points (</span>center points of a <span>25</span><span>×</span><span>25 m regular grid</span><span>)</span> <span>covering</span> the<span> <span>known (as of 2022) and potential mires in Estonia. It was compiled and modified from multiple data sources for running a spatial simulation model, SooSim. The database includes the areas mapped by the Estonian Fund for Nature (1997–2021), wetland polygons from Estonian Topographic Database (2023), and the completed mire restoration projects carried out by the State Forest Management Centre </span></span>(2013<span>–2022</span>). Added to these sources are the<span> remaining Histosols areas from Estonian soil map, which were screened for being either so far unmapped mires or potential areas (mostly drained forests) that could develop into mires once restored. </span>Natural open- or semi-open (wooded) mires, peatland forests and areas with the recovery potential was separated by assessing tree canopy height and density based on the Lidar data provided by Estonian Land Board, and by combining this with land use data to remove regenerating clear-cuts or otherwise human modified areas. Each current or potential mire point includes its coordinates and 10 variables describing its woody cover and restoration potential, mire site type, the surrounding ditch length, and (if recently subjected to ditch renovation or restoration) the year of those interventions. The dataset consists of two tables, the current mire points (“Estmire_current.csv”) and other peatland points (“Estmire_potential.csv”).</p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Longitudinal Survey Data: Wave 1 & Wave 2: Estonia
<p>The data set was generated within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme - Grant Agreement No 649538. The data set is a truncated version of the adolescents’ and young adults’ longitudinal survey that was carried out in Estonia from October 2016 to February 2018. It merges results of two polls (15-19 and 20-30 year olds). Survey was conducted by Univversity of Tartu (UT) within the WP7 research activity which aims at testing processes influencing societal and political engagement of young people.</p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Survey Data: Estonia: Wave 2
<p>The data set was generated within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme - Grant Agreement No 649538. The data set is a truncated version of the adolescents’ and young adults’ survey that was carried out in Estonia from November 2017 to February 2018. It merges results of two polls (15-19 and 20-30 year olds). Survey was conducted by University of Taartu (UT) within the WP7 research activity which aims at testing processes influencing societal and political engagement of young people.</p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Pilot Questionnaires: Estonia
<p>The data set was generated within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme - Grant Agreement No 649538. The data set is a truncated version of the adolescents’ and young adults’ survey that was carried out in Estonia from May to June 2016. It merges results of two polls (16-18 and 20-26 year olds). Survey was conducted by University of Tartu (UT) within the WP7 research activity which aims at testing processes influencing societal and political engagement of young people.</p>
National Checklists 2017: Estonia Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from Estonia collected using effechecka and geonames polygons
National Checklists 2019: Estonia Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from Estonia collected using effechecka and geonames polygons
High-frequency water quality and air parameters from large lake Võrtsjärv, Estonia: 2010-2019
This high frequency water-air dataset was collected from large shallow Lake Võrtsjärv (Estonia) with an automated lake monitoring buoy system and was used in the analyses described in the manuscript by Thayne, M.W., B. Kraemer, J.P. Mesman, A. Laas, E. de Eyto, B. W. Ibelings, R. Adrian. “Trophic state effects on antecedent lake characteristics shape the resistance and resilience of lakes following extreme storms”. Dataset contains every 10-minute measurements from the open water periods in years 2010-2019. Underwater measurements were conducted with Yellow Springs Instrument multiparameter sonde model YSI 6600 V2-4. Underwater measurements contain the collected values of pH, dissolved oxygen, dissolved oxygen saturation, water temperature, specific conductance, water turbidity, chlorophyll concentration (calculated by the sensor from fluorescence values), and the abundance of the bluegreen algae (calculated by the sensor from phycocyanin fluorescence values). Air parameters were collected with the Vaisala multiparameter weather station model WXT520 and contain measurements of wind direction, wind speed, air temperature, atmospheric pressure, and cumulative amount of rain between measurement periods. All air measurements were collected 2 m above from the water surface. Additionally, solar irradiance measurements were collected from the automated buoy system with the Licor pyranometer model LI-200, those measurements contain values in two different columns: average solar irradiance in W/m2 and average photon flux density values in micromoles per square meter per second.
Fig. 4 in New species and new records of black fungus gnats (Diptera: Sciaridae) from the Viidumäe Nature Reserve, Estonia
Fig. 4. Sciara bryophila sp. nov., paratype from Estonia, Viidumäe (MZH), hypopygium, ventral view. Scale bar = 300 µm.
Fig. 2 in New species and new records of black fungus gnats (Diptera: Sciaridae) from the Viidumäe Nature Reserve, Estonia
Fig. 2. Cratyna (Diversicratyna) palustricola sp. nov. A. Hypopygium (holotype, MZH), ventral view. B. Gonostyli (paratype, MZH), ventral view. Scale bars: A = 130 µm; B = 40 µm.
EstSoil-EH: A high-resolution eco-hydrological modelling parameters dataset for Estonia (dataset)
<p>For the EstSoil-EH dataset, we synthesized more than 20 extended eco-hydrological variables for Estonia as numerical and categorical values from the original Soil Map of Estonia, the Estonian 5m Lidar DEM, Estonian Topographic Database and EU-HydroSoilGrids layers. The Soil Map of Estonia maps more than 750 000 soil units throughout Estonia at a scale of 1:10 000 and forms the basis for EstSoil-EH. It is the most detailed and information-rich dataset for soils in Estonia, with 75% of mapped units smaller than 4.0 ha, based on Soviet era field mapping. For each soil unit, it describes the soil type (i.e. soil reference group), soil texture, and layer information with a composite text code, which comprises not only of the actual texture class, but also of classifiers for rock content, peat soils, distinct compositional layers and their depths. To use these as eco-hydrological process properties in modelling applications we translated the text codes into numbers. The derived parameters include soil profiles (e.g., layers, depths), texture (clay, silt, sand components), coarse fragments and rock content. In addition, we aggregated and predicted physical variables related to water and carbon (bulk density, hydraulic conductivity, organic carbon content, available water capacity).<br> The developed methodology and dataset will be an important resource for the Baltic region, but possibly also all other regions where detailed field-based soil mapping data is available. Countries like Lithuania and Latvia have similar historical soil records from the Soviet era that could be turned into value-added datasets such as the one we developed for Estonia.</p> <p> </p> <p>We created an extended eco-hydrological dataset for Estonia, the EstSoil-EH, containing derived numerical values for the following data in all of the mapped soil units in the 1:10 000 soil map: soil profiles (e.g., layers, depths), texture (clay, silt, and sand components), rockiness, and physical variables related to water and carbon (bulk density, hydraulic conductivity, organic carbon content). Ultimately, our objective was to develop a reproducible method for deriving numerical values to support modelling and prediction of eco-hydrological processes in Estonia using the popular Soil and Water Assessment Tool.</p> <p>For more information on the development of this dataset look for "EstSoil-EH: a high-resolution eco-hydrological modelling parameters dataset for Estonia", Alexander Kmoch, Arno Kanal†, Alar Astover, Ain Kull, Holger Virro, Aveliina Helm, Meelis Pärtel, Ivika Ostonen and Evelyn Uuemaa, 2021, Earth Syst. Sci. Data, 13, 83–97, <a href="https://doi.org/10.5194/essd-13-83-2021">https://doi.org/10.5194/essd-13-83-2021</a> </p>
AI results complementing the Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Estonia
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2019, 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>
Data from: Early Silurian recovery of Baltica crinoids following the end-Ordovician extinctions (Llandovery, Estonia)
Three new Llandovery (early Silurian) crinoids from Estonia provide an improved understanding of the paleogeographic aspects of the crinoid diversification following the end-Ordovician extinctions. The new taxa include Euspirocrinus hintsae n. sp. (Rhuddanian eucladid), Oepikicrinus perensae n. sp. n. gen. (Aeronian camerate), and Rozhnovicrinus isakarae n. sp. n. gen. (Aeronian eucladid). This brings the total of described Llandovery crinoids in Estonia to eight nominal species and a further three taxa in open nomenclature. The Rhuddanian radiation in Baltica mirrored that on Laurentia and Avalonia and was dominated by Ordovician clades that continued to diversify during the Silurian. Known Aeronian crinoids from Estonia continue these clades, whereas new clades diversified on Laurentia and Avalonia. However, by the Wenlock a largely cosmopolitan fauna existed on Laurentia, Avalonia, and Baltica.
FTIR-ATR and VSC measurements on cremated archaeological bone from Aakre Kivivare tarand grave, Estonia
<p>This dataset is described in paper bt Lillak <em>et al. </em>in prep "FTIR spectroscopy and VSC-based colour assessment dataset for comparative analysis of cremated bones".</p> <p>This dataset comprises four excel files: </p> <p>Bone list of bones from Aakre Kivivare <em>tarand </em>cemetery. This list is in Estonian.</p> <p>Bone list of bones from Viimsi I <em>tarand </em>cemetery. This list is in English.</p> <p>Bone list template with a table heading proposal, both in Estonian and English.</p> <p>A table of excavated <em>tarand </em>cemeteries, when and by whom they were excavated and whether and where these bones are stored. </p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Estonia
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in the ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Veterinary and Food Board</p> <p>OCC-CHEMMON2021 – Veterinary and Food Board</p> <p>OCC-CHEMMON2022 – Veterinary and Food Board</p> <p>OCC-CHEMMON2023 – Veterinary and Food Board</p> <p>OCC-CHEMMON2024 – Veterinary and Food Board</p>
Fig. 14 in Palaeoecology of corals and stromatoporoids in a late Silurian biostrome in Estonia
Fig. 14. Interpreted reconstruction of faunas and sea-floor appearances of Facies 2 at Katri, represented by Layers 2 and 4.
Fig. 9 in Palaeoecology of corals and stromatoporoids in a late Silurian biostrome in Estonia
Fig. 9. Slab and thin section photographs of tabulate corals from Katri biostrome, upper Ludlow, Silurian, showing the identifications of taxa. A–D. Favosites forbesi Milne-Edwards and Haime, 1851. A. GIT656-27, vertical polished slab of bulbous corallum showing different growth centres. B. GIT656-17, transverse thin-section. C. GIT656-54, vertical thin-section. D. GIT656-56, vertical slab of columnar corallum in sediment. E, F. Thecia swinderniana Goldfuss, 1829. E. GIT656-20, vertical slab of tabular corallum. F. GIT656-62, transverse (F1) and vertical (F2) thin-sections. G, H. Thin- → sections of Kitakamiia callosa Klaamann, 1964. G. GIT656-98, vertical section through rugosan with K. callosa. H. GIT656-90, transverse section. I, J. Thin-sections of Laceripora cribrosa Eichwald, 1854. I. GIT656-29, vertical section through the base of corallum. J. GIT656-10, vertical section through the branching corallum. K. Symbitoic Syringopora affabilis Klaamann, 1962 within stromatoporoid Petridiostroma convictum Yavorsky, 1929, GIT656-38, transverse section (K1), which also has rugose corals within the stromatoporoid; vertical section (K2). Scale bars 10 mm.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.