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6,170 results for “european”
Daily European biospheric methane emissions estimated with the ecosystem model JSBACH-HIMMELI.
<p>Daily estimates of European biospheric methane emissions from JSBACH-HIMMELI model from year 1990 to year 2023. JSBACH-HIMMELI is an ecosystem process model based on JSBACH land surface model, YASSO soil carbon model and HIMMELI methane emission model. The gridded fluxes are available with a resolution of 0.1x0.1 degrees and in units of mol m-2 s-1 (m-2 refers to grid cell area). The gridded flux file contains a variable for methane fluxes, including a sum of methane fluxes from peatlands, inundated lands and mineral soils. More information of the model set-up is documented in Petrescu, A. M. R., et al., The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019, Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, 2023, Tyystjärvi, V., 2024. Future methane fluxes of peatlands are controlled by management practices and fluctuations in hydrological conditions due to climatic variability. EGUsphere 1–37. https://doi.org/10.5194/egusphere-2023-3037 and Raivonen, M. et al., 2017. HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands. Geoscientific Model Development 10, 4665–4691. <a href="https://doi.org/10.5194/gmd-10-4665-2017">https://doi.org/10.5194/gmd-10-4665-2017</a></p>
Dataset of physical, biological and chemical soil properties from 10 European long-term experiments
<p>This dataset contains all measurements that were conducted within the Workpackage #2 of the SoilX Project (2022-2024). The data contains physical, chemical and biological soil parameters that were measured in ten European long-term field experiments, as well as soil management indicators calculated with the SoilManageR packager for R. Each data table contains different parameters, and they can be linked by the identifying columns (LTE, treatment, depth, block, replicate). Further information can be found in the ReadMe.txt.</p> <pre> </pre>
Top 10 most-played albums on Spotify for various European countries
<p>This dataset presents the Top 10 most listened-to albums on Spotify for five European countries: Spain, France, Italy, the United Kingdom, and Germany. The information has been compiled from data available on the website <a href="https://chartmasters.org/">https://chartmasters.org/</a>. The dataset, in CSV format, includes essential details such as the ranking position, album title, artist, and the total number of plays. Organized to provide an overview, the dataset offers insights into current musical preferences in various European regions, showcasing the most popular albums on the Spotify platform.</p>
SSH CENTRE - Mini-reports : Focus groups on "Adaptation to Climate Change: support at least 150 European regions and communities to become climate resilient by 2030"
<p>SSH CENTRE (Social Sciences and Humanities for Climate, Energy aNd Transport Research Excellence) is a Horizon Europe project, engaging directly with stakeholders across research, policy, and business (including citizens) to strengthen social innovation, SSH-STEM collaboration, transdisciplinary policy advice, inclusive engagement, and SSH communities across Europe, accelerating the EU's transition to carbon neutrality. </p><p>SSH CENTRE is based in a range of activities related to Open Science, inclusivity and diversity – especially with regards Southern and Eastern Europe and different career stages – including: development of novel SSH-STEM collaborations to facilitate the delivery of the EU Green Deal; SSH knowledge brokerage to support regions in transition; and the effective design of strategies for citizen engagement in EU R&I activities. Outputs include action-led agendas and building stakeholder synergies through regular Policy Insight events.</p><p>This is captured in a high-profile virtual SSH CENTRE generating and sharing best practice for SSH policy advice, overcoming fragmentation to accelerate the EU's journey to a sustainable future.</p><p>The aim of the focus groups was to gather citizen's perspectives, their hopes, concerns and ideas related to the Horizon Mission of Adaptation to Climate Change: support at least 150 European regions and communities to become climate resilient by 2030. The focus group discussion topics while remaining close to the Mission, avoid specific technical references to allow citizens to contribute based on their differing levels of understanding. As part of the SSH CENTRE project, in total, four focus group series will be conducted relating to Adaptation to Climate Change; Restore our Ocean and Waters by 2030; 100 Climate-Neutral and Smart Cities by 2030; A Soil Deal for Europe. </p><p>Notes were taken during each focus groups and turned into mini-reports. These mini-reports sum up the essence of the discussion: the participants' main ideas and some interesting quotes. </p>
Fig. 1 in Insects Associated with the European Mistletoe (Viscum album) in Western Ukraine: a Pilot Study
Fig. 1. Longitudinal section through the tissues of the host tree (Tilia cordata) and European mistletoe (Viscum album): A–A1 — section through intact tissues of mistletoe and host tree; B–B1, CC1 — section through infest- ed by xylophagous insects' tissues of mistletoe and host tree; D–D1 — section through infested by xylophagous insects' mistletoe tissue. A–D — sections in the original colors, A1–D1 — sections in the false colors. Labels: a (red) — xylophagous insects' galleries; b (pink) — wood of the host tree; c (orange) — bark and phloem of the host tree; d (yellow) — mistletoe wood; e (green) — bark and phloem of mistletoe; f (grey) — the external surface of plants.
Figure 4 in A new dwarf boa (Serpentes, Booidea, 'Tropidophiidae') from the Early Oligocene of Belgium: a case of the isolation of Western European snake faunas
Figure 4. Trunk/caudal transition in Falseryx petersbuchi, in left lateral view: A, posterior trunk vertebra (BSP, 1976 XXII 6127); B, fusion of last trunk, 1st cloacal and 2nd cloacal vertebrae (BSP, uncatalogued); C, anterior caudal vertebra (SMNS, 57898-3). Abbreviations: h, hypapophysis; hk, haemal keel; ls, lymphapophyses; pd, paradiapophysis; pl, pleurapophysis. A and C from Szyndlar & Rage (2003: fig. 27C, P).
Figure 1 in A new dwarf boa (Serpentes, Booidea, 'Tropidophiidae') from the Early Oligocene of Belgium: a case of the isolation of Western European snake faunas
Figure 1. Holotype middle trunk vertebra of Falseryx neervelpensis sp. nov. (IRSNB R 240), in right lateral (A), left lateral (B), dorsal (C), ventral (D), anterior (E) and posterior (F) views. Abbreviations: cd, condyle; ct, cotyle; d, diapophysis; hk, haemal keel; lf, lateral foramen; na, neural arch; nc, neural canal; ns, neural spine; p, parapophysis; pd, paradiapophysis (diapophysis + parapophysis); po, postzygapophysis; poa, postzygapophyseal articular surface; pr, prezygapophysis; pra, prezygapophyseal articular surface; prp, prezygapophyseal process; sf, subcentral foramen; sg, subcentral groove; sr, subcentral ridge; z, zygosphene; zy, zygantrum.
Figure 2 in A new dwarf boa (Serpentes, Booidea, 'Tropidophiidae') from the Early Oligocene of Belgium: a case of the isolation of Western European snake faunas
Figure 2. Trunk vertebrae of Falseryx neervelpensis sp. nov. A–C, anterior trunk vertebra (IRSNB R 239), in right lateral (A), anterior (B) and dorsal (C) views; D–F, middle trunk vertebra (IRSNB R 241), in left lateral (D), dorsal (E) and ventral (F) views; G–K, posterior trunk vertebra (IRSNB R 237), in right lateral (G), dorsal (H), ventral (I), anterior (J) and posterior (K) views; L–P, one of the final trunk vertebrae (IRSNB R 238), in left lateral (L), dorsal (M), ventral (N), anterior (O) and posterior (P) views. Abbreviation: h, hypapophysis.
Figs 10−16. Apical abdominal segments. 10−15 in Omalium gildenkovi (Coleoptera: Staphylinidae: Omaliinae), a new species from the central part of European Russia
Figs 10−16. Apical abdominal segments. 10−15 – Omalium gildenkovi; 16 – O. exiguum. 10 – male sternite VIII; 11 – male tergite VIII; 12 – female sternite VIII; 13 – female tergite VIII; 14 – male genital segment; 15−16 – female genital segment. Scale bars 0.1 mm. Рис. 10−16. Вершинные брюшные сегменты. 10−15 – Omalium gildenkovi; 16 – O. exiguum. 10 – стернит VIII самца; 11 –тергит VIII самца; 12 – стернит VIII самки; 13 – тергит VIII самки; 14 – генитаΛьный сегмент самца; 15−16 – генитаΛьный сегмент самки. Масштабные Λинейки 0.1 мм.
Рис. 1–3. Самка Chrysopa viridinervis Jakowleff, 1869. 1 – экземпΛяр сбоку; 2 – гоΛова и груΑь сверху; 3 – гоΛова спереΑи. Figs 1–3. Female of Chrysopa viridinervis Jakowleff, 1869. 1 – specimen in lateral view; 2 – head and thorax, dorsal view; 3 – head, frontal view. in New data on Neuropterida from the southern part of the European Russia
Рис. 1–3. Самка Chrysopa viridinervis Jakowleff, 1869. 1 – экземпΛяр сбоку; 2 – гоΛова и груΑь сверху; 3 – гоΛова спереΑи. Figs 1–3. Female of Chrysopa viridinervis Jakowleff, 1869. 1 – specimen in lateral view; 2 – head and thorax, dorsal view; 3 – head, frontal view.
Рис. 4. МестонахожΑение Chrysopa viridinervis Jakowleff, 1869 на опушке ХваΛынского Λеса, Саратовская обΛасть. Fig. 4. The locality of Chrysopa viridinervis Jakowleff, 1869 at the edge of the Khvalynsk Forest, Saratov Region. in New data on Neuropterida from the southern part of the European Russia
Рис. 4. МестонахожΑение Chrysopa viridinervis Jakowleff, 1869 на опушке ХваΛынского Λеса, Саратовская обΛасть. Fig. 4. The locality of Chrysopa viridinervis Jakowleff, 1869 at the edge of the Khvalynsk Forest, Saratov Region.
Figs 4−9 in Omalium gildenkovi (Coleoptera: Staphylinidae: Omaliinae), a new species from the central part of European Russia
Figs 4−9. Aedeagi of Omalium spp. 4−5 – O. gildenkovi, holotype; 6−7 – O. exiguum (Smolensk Region, Russia); 8−9 – O. funebre (Alpi Carniche, Italy). 4, 6, 8 – ventral view; 5, 7, 9 – lateral view. Scale bars 0.1 mm. Рис. 4−9. ЭÃеагусы Omalium spp. 4−5 – O. gildenkovi, гоΛотип; 6−7 – O. exiguum (СмоΛенская обΛасть, Россия); 8−9 – O. funebre (Карнийские АΛьпы, ИтаΛия). 4, 6, 8 – виà снизу; 5, 7, 9 – виà сбоку. Масштабные Λинейки 0.1 мм.
Figs 1−3 in Omalium gildenkovi (Coleoptera: Staphylinidae: Omaliinae), a new species from the central part of European Russia
Figs 1−3. Species of the genus Omalium, habitus. 1–2 – O. gildenkovi sp. n.: 1 – male, holotype, 2 – female, paratype; 3 – O. exiguum, male (Smolensk Region, Russia). Scale bars 1 mm. Рис. 1−3. ВиÃы роÃа Omalium, габитус. 1–2 – O. gildenkovi sp. n.: 1 – самец, гоΛотип, 2 – самка, паратип; 3 – O. exiguum, самец (СмоΛенская обΛасть, Россия).Масштабные Λинейки 1 мм.
Network of Marital and Parental Relations of Western and Central European Dynasties, 1350-1550 (Burgundian Dukes Highlighted)
<p>This map visualises the marital and parental connections of princely Western- and Central European dynasties between 1350 and 1550. It features the rulers and consorts born between 1350 and 1550 and their parents. Individuals are undirectedly connected to each other based on either a marital or parental relationship. Red nodes refer to individuals (ruler and/or consort) of the Burgundian State. Nodes are scaled based on the Eigenvector Centrality Count of the individual.</p><p>See: Miara Fraikin and Meike Wiedemann, 'The "Burgundian Model" revisited: Using Digital Approaches to Explore the Reach of Burgundy', in Sanne Maekelberg and Krista De Jonge (eds.), <i>Mapping the Space of the Early Modern Court in Europe. Functionality and Representation, </i>2023, pp.13-34.</p>
Network of Marital and Parental Relations of Western and Central European Dynasties, 1350-1550
<p>This map visualizes the marital and parental connections of princely Western- and Central European dynasties between 1350 and 1550. It features the rulers and consorts born between 1350 and 1550 and their parents. Individuals are undirectedly connected to eachother based on either a marital relationship or a parental relationship. Pink nodes refer to women, green nodes refer to men. Nodes are scaled based on their Eigenvector Centrality count.</p><p>See: Miara Fraikin and Meike Wiedemann, 'The "Burgundian Model" revisited: Using Digital Approaches to Explore the Reach of Burgundy', in Sanne Maekelberg and Krista De Jonge (eds.), <i>Mapping the Space of the Early Modern Court in Europe. Functionality and Representation, </i>2023, pp.13-34.</p>
Data from: Adaptation of perennial flowering phenology across the European range of Arabis alpina
<p>Perennial <em>Arabis alpina</em> has a wide geographic distribution and is adapted to local environments. However, the traits that underlie adaptation are unknown. Flowering phenology is an adaptive trait in other species, but its geographic variation has not been systematically studied in herbaceous perennials.</p> <p>Accessions of <em>A. alpina</em> were collected across the European range. Their flowering behavior was tested in controlled conditions, in experimental common-garden plantations at native sites and <em>in-situ</em> in natural populations. Also, genetic diversity within and among populations was examined.</p> <p>French Alpine and Scandinavian accessions varied in timing and duration of flowering. By contrast, in controlled conditions and <em>in-situ</em>, all Spanish accessions were obligate vernalization-requiring with a short duration of flowering. Nevertheless, Spanish populations were as genetically diverse as French Alpine populations and more so than Scandinavian populations. Furthermore, <em>perpetual flowering 1</em>, a mutant that shows no vernalization requirement and a long duration of flowering, showed higher mortality and poorer performance than local accessions at Spanish experimental sites.</p> <p>We propose that in this perennial species, the vernalization requirement and short duration of flowering are under selection in Spain as a strategy to survive exposure to longer, warmer growing seasons.</p>
I-MAESTRO data: 42 million trees from three large European landscapes in France, Poland and Slovenia
<p>Here we present three datasets describing three large European landscapes in France (Bauges Geopark - 89,000 ha), Poland (Milicz forest district - 21,000 ha) and Slovenia (Snežnik forest - 4,700 ha) down to the tree level. Individual trees were generated combining inventory plot data, vegetation maps and Airborne Laser Scanning (ALS) data. Together, these landscapes (hereafter virtual landscapes) cover more than 100,000 ha including about 64,000 ha of forest and consist of more than 42 million trees of 51 different species.</p><p>For each virtual landscape we provide a table (in .csv format) with the following columns:<br>- cellID25: the unique ID of each 25x25 m² cell<br>- sp: species latin names<br>- n: number of trees. n is an integer >= 1, meaning that a specific set of species "sp", diameter "dbh" and height "h" can be present multiple times in a cell.<br>- dbh: tree diameter at breast height (cm)<br>- h: tree height (m)</p><p>We also provide, for each virtual landscape, a raster (in .asc format) with the cell IDs (cellID25) which makes data spatialisation possible. The coordinate reference systems are EPSG: 2154 for the Bauges, EPSG: 2180 for Milicz, and EPSG: 3912 for Sneznik.</p><p>The v2.0.0 presents the algorithm in its final state.</p><p>Finally, we provide a proof of how our algorithm makes it possible to reach the total BA and the BA proportion of broadleaf trees provided by the ALS mapping using the alpha correction coefficient and how it maintains the Dg ratios observed on the field plots between the different species (see algorithm presented in the associated Open Research Europe article).</p><p>Below is an example of R code that opens the datasets and creates a tree density map.</p><p>------------------------------------------------------------<br># load package</p><p>library(terra)</p><p>library(dplyr)</p><p> </p><p># set work directory</p><p>setwd() # define path to the I-MAESTRO_data folder</p><p> </p><p># load tree data</p><p>tree <- read.csv2('./sneznik/sneznik_trees.csv', sep = ',')</p><p> </p><p># load spatial data</p><p>cellID <- rast('./sneznik/sneznik_cellID25.asc')</p><p> </p><p># set coordinate reference system</p><p># Bauges:</p><p># crs(cellID) <- "epsg:2154"</p><p># Milicz:</p><p># crs(cellID) <- "epsg:2180"</p><p># Sneznik:</p><p># crs(cellID) <- "epsg:3912"</p><p> </p><p># convert raster into dataframe</p><p>cellIDdf <- as.data.frame(cellID)</p><p>colnames(cellIDdf) <- 'cellID25'</p><p> </p><p># calculate tree density from tree dataframe</p><p>dens <- tree %>% group_by(cellID25) %>% summarise(n = sum(n))</p><p> </p><p># merge the two dataframes</p><p>dens <- left_join(cellIDdf, dens, join_by(cellID25))</p><p> </p><p># add density to raster</p><p>cellID$dens <- dens$n</p><p> </p><p># plot density map</p><p>plot(cellID$dens)</p>
Tables, figures, and country data complementing the European Union One Health Zoonoses 2022 Report
<p>European Food Safety Authority; European Centre for Disease Prevention and Control</p><p>All summary tables and figures produced for the European Union One Health 2022 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><p>Supplementary datasets submitted are given in the related identifier section, however for clarity we give here the information on what they refer to:</p><p><strong>10.5281/zenodo.10255165 </strong>Foodborne outbreaks</p><p><strong>10.5281/zenodo.10256864 </strong>Disease status</p><p><strong>10.5281/zenodo.10255061 </strong>Animal Population</p><p><strong>10.5281/zenodo.10246432 </strong>Prevalence</p><p><i><strong>Sample-based data submitted by specific countries</strong></i></p><p><strong>10.5281/zenodo.10257184 </strong>Finland</p><p><strong>10.5281/zenodo.10257162 </strong>Croatia</p><p><strong>10.5281/zenodo.10257105 </strong>Norway</p><p><strong>10.5281/zenodo.10257034 </strong>Luxembourg</p><p><strong>10.5281/zenodo.10257142 </strong>United Kingdom (Northern Ireland)</p><p><strong>10.5281/zenodo.10257210 </strong>Ireland</p><p><strong>10.5281/zenodo.10257388 </strong>Sweden</p><p>Journal article: 10.2903/j.efsa. 2023.8442 </p><p>Citation</p><p>EFSA (European Food Safety Authority) & ECDC (European Centre for Disease Prevention and Control). (2023). Tables, figures, and country data complementing the European Union One Health Zoonoses 2022 Report [Dataset]. <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.10057302&data=05%7C01%7C%7Cd53ce1fd0eeb4b027cb608dbf6528f55%7C406a174be31548bdaa0acdaddc44250b%7C1%7C0%7C638374606688640910%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=46n1ois6rCgqRamDnk4%2B42K2XGwwg1T1nvG5ezYqqyg%3D&reserved=0">https://doi.org/10.5281/zenodo.10057302</a></p>
Short tandem repeat expansions in LRP12 are absent in familial and sporadic amyotrophic lateral sclerosis patients of European ancestry
<p>In patients of Asian ancestry, a heterozygous CGG repeat expansion of >100 units in <i>LRP12</i> is the cause of oculopharyngodistal myopathy type 1 (OPDM1), and has been associated with amyotrophic lateral sclerosis (ALS) when repeat lengths are between 61-100 units, although with unusually long disease duration and without significant upper motor neuron involvement. This study investigated if <i>LRP12</i> CGG tandem repeats were expanded in ALS patients of European ancestry. We screened whole-genome sequencing data from 608 sporadic ALS patients, 35 familial ALS probands, and 4,703 neurologically normal controls for the <i>LRP12</i> CGG expansion using ExpansionHunter v4. All individuals had <i>LRP12 </i>CGG repeat lengths between 3-25 units. Our results suggest that <i>LRP12 </i>CGG repeat expansions may only be present in ALS patients of Asian ancestry with atypical clinical presentations.</p>
Regional differences in thermoregulation between two European butterfly communities
<p>Understanding how different organisms cope with changing temperatures is vital for predicting future species' distributions and highlighting those at risk from climate change. As ectotherms, butterflies are sensitive to temperature changes, but the factors affecting butterfly thermoregulation are not fully understood.</p> <p>We investigated which factors influence thermoregulatory ability in a subset of a Mediterranean butterfly community. We measured adult thoracic temperature and environmental temperature (787 butterflies; 23 species) and compared buffering ability (defined as the ability to maintain a consistent body temperature across a range of air temperatures) and buffering mechanisms to previously published results from Great Britain. Finally, we tested whether thermoregulatory ability could explain species' demographic trends in Catalonia.</p> <p>The sampled sites in each region differ climatically, with higher temperatures and solar radiation but lower wind speeds in the Catalan sites. Both butterfly communities show nonlinear responses to temperature, suggesting a change in behaviour, from heat-seeking to heat avoidance, at approximately 22 °C. However, the communities differ in the use of buffering mechanisms, with British populations depending more on microclimates for thermoregulation compared to Catalan populations.</p> <p>Contrary to the results from British populations, we did not find a relationship between region-wide demographic trends and butterfly thermoregulation, which may be due to the interplay between thermoregulation and the habitat changes occurring in each region. Thus, although Catalan butterfly populations seem to be able to thermoregulate successfully at present, evidence of heat avoidance suggests this situation may change in the future.</p>
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.