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6,170 results for “european”
FIG. 4 in The first molecular confirmation of the presence of the genus Ladislavella (Gastropoda: Lymnaeidae) in the European part of Russia
FIG. 4. Abnormally large individual of Ladislavella cf. terebra with trematode parthenitae in the hepatopancreas and mantle cavity. A. Shell. B. The copulatory apparatus. C. Soft body. Scale bars: 2 mm (B, C), 5 mm (A). РИС. 4. Аномально крупная особь Ladislavella cf. terebra с партенитами трематод в гепатопанкреасе и мантийной полости. A. Раковина. B. Копулятивный аппарат. C. Мягкое тело. Масштабная линейка: 2 мм (В, C), 5 мм (А).
Dataset in support of an AI-aided chronic mixture risk assessment along a small European river
<p>Here, we make available a dataset to perform an AI-aided multi-scenario chronic mixture risk assessment. In 2021, river-water samples were collected at six sampling sites along the Holtemme River in Central Germany using large-volume solid phase extraction. The extracts were analysed by target chemical analysis for contaminants of emerging concern. The dataset of the chemical analysis was already published and can be found at DOI: 10.5281/zenodo.10892038. Furthermore, a detailed description of the dataset can be found at DOI: 10.1016/j.dib.2024.110510.</p> <p> </p>
Pan-European temperature distribution at depth - GeoDH project
<p>The dataset includes two shapefiles showing the temperature distribution at depth in Europe, specifically areas with temperatures exceeding 50°C at 1000m depth and 90°C at 2000m depth.<br><br>This dataset was developed for assessing the potential of Geothermal District Heating in Europe as part of the <strong>GeoDH project</strong> (<a href="http://geodh.eu/" target="_new" rel="noopener">http://geodh.eu/</a>). Please note that this represents the<strong> state of the art as of 2014</strong> and that geological, technological, and regulatory developments may have occurred since its creation, and users should verify if more recent data is available for their purposes.</p>
Supplementary data to "The effects of small-scale heterogeneity on biomonitoring of desmid phytobenthos in Central European temperate mountain peatlands"
<p>The supplementary data consist of the files including the species-in-samples data and their associated NCV scores used for the analyses described in the manuscript submitted to hydrobiologia. In addition, two R scripts used for the analyses are included, too.</p> <p> </p>
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - Norway
<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_NO: Norwegian Veterinary Institute (NVI)</li> <li>TSE_2022_NO: Norwegian Veterinary Institute (NVI)</li> <li>TSE_2021_NO: Norwegian Veterinary Institute (NVI)</li> <li>TSE_2020_NO: Norwegian Veterinary Institute (NVI)</li> <li>TSE_2019_NO: Norwegian Veterinary Institute (NVI)</li> </ul>
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - Latvia
<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_LV: Food and Veterinary Service (PVD)</li> <li>TSE_2022_LV: Food and Veterinary Service (PVD)</li> <li>TSE_2021_LV: Food and Veterinary Service (PVD)</li> <li>TSE_2020_LV: Food and Veterinary Service (PVD)</li> <li>TSE_2019_LV: Food and Veterinary Service (PVD)</li> </ul>
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - Luxembourg
<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_LU: Veterinary Services Administration (ASV)</li> <li>TSE_2022_LU: Veterinary Services Administration (ASV)</li> <li>TSE_2021_LU: Veterinary Services Administration (ASV)</li> <li>TSE_2020_LU: Veterinary Services Administration (ASV)</li> <li>TSE_2019_LU: Veterinary Services Administration (ASV)</li> </ul>
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - Bosnia and Herzegovina
<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_BA: Food Safety Agency of Bosnia and Herzegovina (FSA)</li> <li>TSE_2022_BA: Food Safety Agency of Bosnia and Herzegovina (FSA)</li> <li>TSE_2021_BA: Food Safety Agency of Bosnia and Herzegovina (FSA)</li> <li>TSE_2020_BA: Food Safety Agency of Bosnia and Herzegovina (FSA)</li> </ul> <p>For Bosnia and Herzegovina, 2020 is the first year reporting TSE surveillance results.</p>
Digital repository for: Large-scale forest disturbance and associated management shape bird communities in Central European spruce forests
<p>Repository containing R-script and data to reproduce analysis and main figures on the effect of large-scale forest disturbance and associated pre- and post-disturbance management on bird communities in the Harz Mountains, Germany.</p> <p>R-script includes:</p> <ul> <li>indicator species analysis (R package indicspecies; Cáceres & Legendre, 2009)</li> <li>non-metric multidimensional scaling (R package vegan; Oksanen et al., 2016)</li> <li>rarefaction- and extrapolation of Hill numbers (R package iNEXT; Hsieh et al., 2019)</li> <li>multi-species community distance sampling (R package sp Abundance; Doser et al., 2023)</li> </ul> <p>Attached files:</p> <ul> <li><strong>bird_data_Graser_et_al.csv </strong>(row data of bird species point counts per distance category)</li> <li><strong>bird_data_abundance_100_Graser_et_al.csv </strong>(abundance of species per sampling site, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>siteCovs_Graser_et_al.csv</strong> (environmental variables for each sampling point)</li> <li><strong>A_species_matrix_100_new_Graser_et_al.csv</strong> (species-site matrix of <strong>bark-beetle disturbance, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>B_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>windthrow disturbance, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>C_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle/windthrow disturbance, underplanted, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>D_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle /windthrow disturbance, salvage-unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>E_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle /windthrow disturbance, underplanted, salvage-unlogged </strong>sites for rarefaction and extrapolation, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong> F_species_matrix_100_new_Graser_et_al.cs</strong>v (species-site matrix of <strong>mature spruce plantation </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>msHDS_bird_data_management_model_Graser_et_al.rds</strong> (R-data set for multi-species community distance sampling of the effect of different pre- and post-disturbance management groups)</li> <li><strong>msHDS_bird_data_stand_age_model_Graser_et_al.rds </strong>(R-data set for multi-species community distance sampling of the effect of post-disturbance forest succession)</li> </ul> <p>A more detailed description of the data can be found in the README.txt document.</p> <p><span>References:</span></p> <p><span>Cáceres, M. D., & Legendre, P. (2009). </span><span>Associations between species and groups of sites: Indices and statistical inference. <em>Ecology</em>, <em>90</em>(12), 3566–3574. https://doi.org/10.1890/08-1823.1</span></p> <p><span>Doser, J. W., Finley, A. O., Kéry, M., & Zipkin, E. F. (2023). spAbundance: An R package for single‐species and multi‐species spatially explicit abundance models. <em>Methods in Ecology and Evolution</em>, <em>15</em>(6), 1024–1033. https://doi.org/10.1111/2041-210X.14332</span></p> <p><span>Hsieh, T. C., Ma, K. H., & Chao, A. (2019). <em>iNEXT-package: Interpolation and extrapolation for species diversity</em>. https://cran.r-project.org/web/packages/iNEXT/vignettes/Introduction.html</span></p> <p><span>Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., O’hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., Wagner, H., Minchin, P. R., Gavin, L., & Henry, H. (2016). Vegan: Community ecology package. R package version 1.17-4. <em>Http://CRAN. R-Project. </em></span><em><span>Org/Package=vegan</span></em><span>.</span></p> <p></p> <p></p>
Land surface temperature (heatmaps) derived from earth observation data to assess thermal behaviour of 3 European cities: Milano, Logroño and Athens.
<p>Next tables present the detail description of the datasets developed in REACHOUT to characterize heat phenomena at city level by providing an assessment of the <strong>land surface temperature (heatmaps)</strong> of three European cities: Milan, Logroño and Athens. TECNALIA is the responsible partner for these datasets.</p> <p>There is a wide range of methods that can be used to characterise the thermal behaviour of a city, each of them with its advantages and disadvantages. One of these methods uses the land surface temperature that is obtained from remote sensing observations. Although thermal indices are considered more suitable when characterising thermal comfort, still the LST can provide a useful information about the behaviour of a citiy’s surfaces and materials. This has implications for several applications such as urban energy efficiency or urban environmental health. </p> <p>The input data used by the current version of the dataset came from Landsat 8. All the images acquired since 2013 by this satellite for Milan, Logroño and Athens were downloaded and processed to characterise not only the current (2019-2023) thermal behaviour of the city, but also its evolution considering the last seven 5-year windows.</p> <p>- 2013-2017<br>- 2014-2018<br>- 2015-2019<br>- 2016-2020<br>- 2017-2021<br>- 2018-2022<br>- 2019-2023</p> <p>The input data used in this dataset come from Landsat 8 downloaded from <a href="https://earthexplorer.usgs.gov/">Earth Explorer (usgs.gov)</a>.</p> <p>The format of this dataset is organized in two ZIP format files:</p> <p>- LANDSAT_8_L2SP_000000-milan_LST_peak.zip</p> <p>- LANDSAT_8_L2SP_000000-logrono_LST_peak.zip</p> <p>- LANDSAT_8_L2SP_000000-athens_LST_peak.zip</p> <p>Each of these zip files contain seven TIF images that represent the peak LST map according to the images of the above mentioned seven periods. The peak LST is obtained after getting the Annual Cycle Parameters of each of the periods and selecting a 30-day window centred on the day that the city reaches the maximum LST.</p> <p>The values of the images are in degree Celsius and nodata value is -9999.</p> <p> </p>
Biomass availability at NUTS3 level for modelling European energy system with 3 future scenario
<p>The database is built over three main sources</p> <ul> <li>S2Biom database from where most of the numbers come from <a title="S2Biom" href="https://s2biom.wenr.wur.nl/home" target="_blank" rel="noopener">(S2Biom original repo)</a></li> <li>ENSPRESO database that we use for few energy sources that are not part of s2biom (<a title="JRC" href="https://data.jrc.ec.europa.eu/collection/id-00138" target="_blank" rel="noopener">ENSPRESO</a>)</li> <li>National data for Switzerland (<a href="https://www.envidat.ch/dataset/swiss-biomass-potentials" target="_blank" rel="noopener">FoReMA Forest Resources Management Insititute</a></li> </ul> <p>Data processing is done with Julia code that has short documentation and additional databasePipeline.pdf to understand how the dataset was built. To rebuild the dataset, refer to the github repository linked to this dataset.</p> <p>Data are available as a csv file and as a sqlite database. Data query methods are available from the Github repository linked to this dataset.</p> <p>The dataset includes biomass energy availability, expressed in PJ, at nuts 0-3 (NUTS 2013), and ENTSOE bidding zones aggregation. For each biomass source, the roadsidecost of each source is associated. While the biomass data is varied, large, and detailed following standards (ISO 17225-1:2021, ISO 17225-2:2021, ISO 17225-3:2021, ISO 17225-4:2021, ISO 17225-5:2021, ISO 17225-6:2021, ISO 17225-7:2021, ISO 18125:2017, EN 13556), biomass sources have been aggregated into three categories: Forestry, Agriculture, Organic waste. There are 3 bioenergy potential, low, medium, and high. These were based on the available data listed above. </p> <p>Note: Technical availability of biomass is often much higher than the current use. Check comparison_biofuel_amounts.xlsx to compare the potentials to actual use in Eurostat and IEA data. Full potential should often not be used, because of possible issues with biodiversity and land use emissions.</p> <p> </p>
Diversity of radial variations of wood properties in European beech reveals the plastic nature of juvenile wood - Dataset
<p>The long-term (as opposed to short-term intra-ring) radial variation of wood properties in European beech (<em>Fagus sylvatica</em> L.) from pith to bark are largest in the young ages of the tree (internal core). This so-called juvenility reflects both cambium ageing (ontogenetic juvenility) and adaptation to the changing mechanical constraints during secondary growth (adaptive juvenility). Ring width (<em>RW</em>), specific gravity (<em>SG</em>) and specific modulus (<em>SM</em>) are important parameters for each new wood layer, needed for the study of mechanical stability of a standing tree. They should be sensitive to the mechanical adaptation of growth.<strong> </strong>They were measured on diametrical boards (North/South direction) issued from 86 trees from several high forest stands in European countries. Analysis of variance showed very significant influence of position within the tree (core/external), of trees within a plot and of plots, but not for North/South orientation. The share of variance was similar for <em>SG</em> and <em>SM</em> (importance of tree effect) but different for <em>RW </em>(importance of plot effect). The occurrence of red heartwood in the core on some trees had a significant influence, mostly on <em>SM</em>, but the differences between white and red wood was very small. Globally the variability was high for <em>RW</em>, rather small for <em>SM</em> and very small for <em>SG</em>. Accordingly, the variations of the modulus of elasticity (product of <em>SG</em> and <em>SM</em>) were much more influenced by <em>SM</em> than by <em>SG</em> for beech. The radial variations of each parameter were fitted by both a linear (2 coefficients: zero value and mean slope) and a parabolic curve (3 coefficients: zero value, initial slope and curvature). They were used to classify types or radial profile in terms of flat, up & down and straight, convex & concave. Median values of coefficients per plot (or total) were used to draw median profiles for each parameter per plot and at the global level. The median global profiles differed from the typical radial pattern (TRP) of juvenility for plantation softwoods for <em>SG</em> (down concave instead of up concave) and <em>SM</em> (convex like TRP but with a clear decrease in the mature wood). The main result was the very large variability of profiles between trees or even between plots. Even if there is a part of ontogenetic influence in the juvenile patterns for <em>RW</em>, <em>SG</em> and <em>SM</em>, the results suggest that the influence of mechanical constraints on tree growth (adaptive juvenility) dominates largely. </p> <p><em>The provided file contains the data and the sheets developped to analyse them. It serves as supplementary material for the related paper submitted for recommendation to the PCI Forest and Wood Science.</em></p>
FIG. 2 in Naja romani (Hoffstetter, 1939) (Serpentes: Elapidae) from the late Miocene of the Northern Caucasus: the last East European large cobra
FIG. 2. — The precloacal vertebra of Naja romani (Hoffstetter, 1939) from Solnechnodolsk locality in dorsal (A), ventral (B), left lateral (C), right lateral (D), anterior (E) and posterior (F) views. Scale bar: 5 mm.
1847 in Atlas of European millipedes 3: Order Chordeumatida (Class Diplopoda)
1847, according to Enghoff et al. (2015) with recent modifications: 1. Family Anthogonidae Ribaut, 1913 has been reinstated and added to superfamily Anthroleucosomatoidea; it includes Acherosomatidae Verhoeff, 1929 and Biokoviellidae Mršić, 1992 as junior synonyms (Antić et al. 2015a, 2016). 2. Family Dalmatosomatidae Antić & Makarov, 2018, was described as new and placed in Branneroidea by Antić et al. (2018c). 3. Family Hungarosomatidae Ceuca,1974, was reinstated by Mock et al. (2016) but not assigned to a superfamily. Based on the discussion by Mock et al. (2016), it is here placed as Craspedosomatidea incertae sedis. Families covered by the present volume are shown in bold and are followed by the number of known European species
Data from: The 2018 European heatwave led to stem dehydration but not to consistent growth reductions in forests
<p>Heatwaves exert disproportionately strong and sometimes irreversible impacts on forest ecosystems. These impacts remain poorly understood at the tree and species level and across large spatial scales. Here, we investigate the effects of the record-breaking 2018 European heatwave on tree growth and tree water status using a collection of high-temporal resolution dendrometer data from 21 species across 53 sites. Relative to the two preceding years, annual stem growth was not consistently reduced by the 2018 heatwave but stems experienced twice the temporary shrinkage due to depletion of water reserves. Conifer species were less capable of rehydrating overnight than broadleaves across gradients of soil and atmospheric drought, suggesting less resilience toward transient stress. In particular, Norway spruce and Scots pine experienced extensive stem dehydration. Our high-resolution dendrometer network was suitable to disentangle the effects of a severe heatwave on tree growth and desiccation at large-spatial scales in situ, and provided insights on which species may be more vulnerable to climate extremes.</p>
TSE results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - the United Kingdom
<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>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: TSE_2020_UK: Animal and Plant Health Agency (APHA)</p>
Fig. 1 in Study of some European wild hybrids of Erica L. (Ericaceae), with descriptions of a new nothospecies: Erica nelsonii Fagúndez and a new nothosubspecies: Erica veitchii nothosubsp. asturica Fagúndez
Fig. 1. – Erica ×nelsonii Fagúndez. A. Synflorescence of upper left fragment (typus); B. General view of upper right fragment. [P. F. Hunt 1636, K] [Drawn by the author]
Fig. 2 in Study of some European wild hybrids of Erica L. (Ericaceae), with descriptions of a new nothospecies: Erica nelsonii Fagúndez and a new nothosubspecies: Erica veitchii nothosubsp. asturica Fagúndez
Fig. 2. – Seeds of different species of Erica L. A: Erica tetralix L.; B: E. tetralix (detail of surface cells); C: E. tetralix × E. ciliaris; D: E. tetralix × E. ciliaris (detail of surface cells); E: E. ciliaris L.; F: E. ciliaris (detail of surface cells). [A: Fagúndez s.n., SANT-BG [119]; B: Fagúndez s.n., SANT-BG [211]; C-D: Fagúndez 3266, SANT; E: Fagúndez & Reyes s.n., SANT-BG [266]; F: Fagúndez & Reyes s.n., SANT-BG [273]]
Tables and figures complementing the European Union OneHealth 2020 Zoonoses Report
<p>All summary tables and figures produced for the European Union One Health 2020 Zoonoses Report are provided as archives containing Excel files for tables, and as PDF or PNG files for figures.</p> <p><strong>All country data connected to this Report are published SEPARATELY on Knowledge Junction - see related identifiers. This is because DATA OWNERSHIP for country data stays with the organisation(s) of the country submitting the data - for further reference see doi:10.2903/sp.efsa.2019.EN-1544.</strong></p>
Sample based prevalence data complementing the European Union One Health 2020 Zoonoses Report - Norway
<p>This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agents in foodstuffs. Relevant EU legislation: Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014.</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.