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1,579 results for “Baltics”
Fig. 1 in Rock Crawlers in Baltic Amber (Notoptera: Mantophasmatodea)
Fig. 1. Photomicrograph of holotype of Adicophasma grylloblattoides Arillo and Engel, new species
FIGURE 7 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 7: Distribution of the fossil E. glaesi and of the four extant species of the genus Eunicolina, shown on paleogeographic map of Europe (c. 40 Mya) (adapted from maps given by Charbit et al. 2007, Swedo, Sontag 2013, Scotese 1997).
FIGURE 6 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 6: Genito-anal area: A – Disposition of genital and anal shields (drawn from the extant species E. travei) Aa, Ab: ventral view, female (a), male (b); Ac: male lateral view. Eunicolina glaesi n. sp.: B-C – extremity of the opisthosoma, lateral view (B) and interpretation (Ca, Cb, Cc).
FIGURE 5 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 5: Eunicolina glaesi n. sp.: A – Oculo-pustular zone. bo.p: trichobthria, la?: supposed insertion of the la seta; lb: seta lb; ly: post-ocular lyriform organ; B – Detail of the PI tarsus showing the bidactylus claw, one of the two tarsal solnidia (ω). F?: possible famulus of the tarsus. Some insertions of setae are marked by circles.
FIGURE 3 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 3:. Eunicolina glaesi n. sp.: A – Dorsal shield, anterior part; B – Detail of the posterior trichobothrium; C – Ventral view of epimeral plates and detail of ornamentation. Abbreviations: AS: additional posterior seate of the infracapitulum; bo.a, bo.p: anterior and posterior bothridia; CH: Chelicera; cha, chb cheliceral setae; gr, la: ocular and lateral setae of the dorsal shield; PI, PII: legs I and II; Pp: palp. ω1: tarsal solenidion of the palp.
FIGURE 1 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 1: Eunicolina glaesi n. sp. — A. Lateral view, right side. B. Oculo-pustular zone, details. C. Detail of the cuticle, pattern in the lateral zone. D. Enlarged view of the acetabula IV, showing the villosity in pit PT ("puits tØgumentaire" in Coineau 1964). Abbreviations: BO.A, BO.P: anterior and posterior trichobothria; la, lb: lateral setae of the dorsal shield; da, db, dc: dorsal setae of the dorsal shield; EPI IV: fourth epimeral plate; PI, PIV: first and fourth legs. Star: possible lateral eye.
FIGURE 4 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 4: Eunicolina glaesi n. sp.: A – The holotype piece, CHHC 588-13 (Hoffeins collection); B – Lateral view of the specimen of Eunicolina glaesi sp.nov.; C – Ventral view of infracapitulum and leg I.
Modeling cyanobacteria life cycle dynamics and historical nitrogen fixation in the Baltic Proper - Datasets
<p>Observational and model datasets used in: Modeling cyanobacteria life cycle dynamics and historical nitrogen fixation in the Baltic Proper.</p>
Generated data for "Limited ventilation of the central Baltic Sea due to elevated oxygen consumption" paper
<p>This data are essential for reproducing the figures from Naumov et al. "Limited ventilation of the central Baltic Sea due to elevated oxygen consumption" paper. Each archive is named after one of the ten figures and includes the data necessary for that specific figure. Some data are used in more than one figure. In some cases, performing a particular type of analysis with the given data (linear regression, for instance) is necessary to fully reproduce the figure.</p>
Fig. 1. A in A comparative analysis of the Baltic and Rovno amber arthropod faunas: representative samples
Fig. 1. A piece of Rovno amber (UA-662) with more than 50 inclusions.
Bio-Optic bio-shortwave model code, initial conditions, river and boundary forcing for "Estimating the seaonal impact of optically significant water constituents on surface heating rates in the Western Baltic Sea" paper.
<p>Bio-Optic bio-shortwave model code, initial conditions, river and boundary forcing as well as selected model output used for analysis and producing figures in the paper "Estimating the seaonal impact of optically significant water constituents on surface heating rates in the Western Baltic Sea". Contact Bronwyn Cahill if you have questions at: bronwyn.cahill@io-warnemuende.de</p>
Dataset from publication: Long-term changes in bloom dynamics of Southern and Central Baltic cold-water phytoplankton
<p>This data set contains the output of the numerical ocean model GETM used in the publication "Long-term changes in bloom dynamics of Southern and Central Baltic cold-water phytoplankton"</p>
Bio-optical observations of the Baltic Sea and coastal areas, 2008-2012
<p>This a dataset of optical-biogeochemical measurement results was collected during 2008-2012 as part of spring and summer cruises with R/V Aranda as well as from flow-through water samples taken with the Ferrybox system on M/S Finnmaid. The majority of observations were made in the Gulf of Finland, Baltic Proper, Archipelago Sea, and Gulf of Bothnia in the Baltic Sea. A number of riverine and inshore observations are also included. The data collection is owned by the Finnish Environment Institute SYKE and made available under a CC-BY-NC licence. </p> <p>Detail on methods and protocols are provided in the following papers </p> <ul> <li>Simis, Stefan GH; Ylöstalo, Pasi; Kallio, Kari Y; Spilling, Kristian; Kutser, Tiitt. 2017. Contrasting seasonality in optical-biogeochemical properties of the Baltic Sea. PLoS One 12(4), e0173357. https://doi.org/10.1371/journal.pone.0173357</li> <li>Ylöstalo, Pasi; Seppälä, Jukka; Kaitala, Seppo; Maunula, Petri; Simis, Stefan. 2016. Loadings of dissolved organic matter and nutrients from the Neva River into the Gulf of Finland–Biogeochemical composition and spatial distribution within the salinity gradient. Marine Chemistry 186, 58-71. https://doi.org/10.1016/j.marchem.2016.07.004</li> </ul> <p>A large number of individuals took part in these bio-optical research cruises over the years. The authors of this dataset are particularly grateful to the contributions by international visitors, students and volunteers taking part in one or more cruises, as well as crew and support staff operating the research vessel and ship-of-opportunity. </p> <p>Variables included in the dataset include: </p> <table> <tbody> <tr> <td>Column name</td> <td>unit/format</td> <td>Description</td> </tr> <tr> <td>Secchi</td> <td>m</td> <td>Secchi disk depth</td> </tr> <tr> <td>AirTemp(38)</td> <td>°C, 01H</td> <td>Air temperature from ship weather channel 38, 1-h average</td> </tr> <tr> <td>SeaTemp(42)</td> <td>°C, 01H</td> <td>Sea temperature from ship weather channel 42, 1-h average</td> </tr> <tr> <td>WindSpeed(92)</td> <td>m/s, 10M</td> <td>Wind speed from ship weather channel 92, 10-min average</td> </tr> <tr> <td>WindDir(96)</td> <td>°, 10M</td> <td>Wind direction from ship weather channel 96, 10-min average</td> </tr> <tr> <td>Salinity(104)</td> <td>PSU, 01H</td> <td>Salinity from ship weather channel 104, 1-h average</td> </tr> <tr> <td>Rel.humid(54)</td> <td>%, 01H</td> <td>Relative humidity from ship weather channel 54, 1-h average</td> </tr> <tr> <td>Chla</td> <td>mg/m3</td> <td>Chlorophyll-a concentration (cold ethanol extraction and calibrated fluorescence)</td> </tr> <tr> <td>TSM_avg</td> <td>mg/L</td> <td>Total Suspended Matter Dry Weight, Average</td> </tr> <tr> <td>OSM_avg</td> <td>mg/L</td> <td>Dry weight of Organic fraction of TSM, Average</td> </tr> <tr> <td>ISM_avg</td> <td>mg/L</td> <td>Dry weight of Inorganic fraction of TSM, Average</td> </tr> <tr> <td>DOC_avg</td> <td>µM</td> <td>Dissolved Organic Carbon concentration, Average</td> </tr> <tr> <td>TDN_avg</td> <td>µM</td> <td>Total Dissolved Nitrogen concentration, Average</td> </tr> <tr> <td>NH4</td> <td>µM</td> <td>Ammonium concentration</td> </tr> <tr> <td>NO32</td> <td>µM</td> <td>Nitrate-Nitrate concentration</td> </tr> <tr> <td>NO2</td> <td>µM</td> <td>Nitrite concentration</td> </tr> <tr> <td>PO4</td> <td>µM</td> <td>Phosphate concentration</td> </tr> <tr> <td>SiO4</td> <td>µM</td> <td>Silicate concentration</td> </tr> <tr> <td>TN</td> <td>µM</td> <td>Total nitrogen concentration</td> </tr> <tr> <td>TP</td> <td>µM</td> <td>Total phosphorous concentration</td> </tr> <tr> <td>pH</td> <td>pH</td> <td>pH value</td> </tr> <tr> <td>Temp_CTD</td> <td>°C</td> <td>Water temperature measured by Seabird CTD on sampling rosette</td> </tr> <tr> <td>Salinity_CTD</td> <td>SSU</td> <td>Salinity measured by Seabird CTD on sampling rosette</td> </tr> <tr> <td>POC</td> <td>µM</td> <td>Particulate Organic Carbon concentration, Average</td> </tr> <tr> <td>PON</td> <td>µM</td> <td>Particulate Organic Nitrogen concentration, Average</td> </tr> <tr> <td>POP</td> <td>µM</td> <td>Particulate Organic Phosphorus concentration, Average (30.973762 g/Mol)</td> </tr> <tr> <td>Turbidity</td> <td>PSU</td> <td>Turbidity</td> </tr> <tr> <td>aCDOM</td> <td>m^-1</td> <td>spectral absorption coefficient of coloured dissolved organic matter</td> </tr> <tr> <td>CloudCover</td> <td>0-1</td> <td>Fraction (0-1) of cloud cover assesed from photos taken in the field.</td> </tr> <tr> <td>Kd</td> <td>m^-1</td> <td>spectral Vertical diffuse downwelling irradiance coefficient</td> </tr> <tr> <td>a_nap</td> <td>m^-1</td> <td>spectral absorption coefficient by non-pigmented fraction of suspended matter</td> </tr> <tr> <td>a_tsm</td> <td>m^-1</td> <td>spectral absorption coefficient by suspened matter</td> </tr> <tr> <td>R0</td> <td>-</td> <td>spectral Subsurface Irradiance Reflectance</td> </tr> <tr> <td>pigments</td> <td>mg/m3</td> <td>Chlorophyll and other pigments extracted and quantified using a combination of calibrated fluorometry and HPLC</td> </tr> </tbody> </table>
Data for: High focus on threatened species and habitats may undermine biodiversity conservation: evidence from the northern Baltic Sea
<p><span>Conservation policies and environmental impact assessments commonly target threatened species and habitats. Nevertheless, macroecological research provides reasons why also common species should be considered. </span><span>We investigate the consequences of focusing solely on legally protected species and habitats in a spatial conservation planning context using a comprehensive, benthic marine dataset from the northern Baltic Sea</span><span>. </span><span>Using spatial prioritization and surrogacy analysis, we </span><span>show that the common approach in conservation planning, where legally listed threatened species and habitats are the focus of conservation efforts, could lead to poor outcomes for common species (and therefore biodiversity as a whole), allowing them to decline in the future.</span> <span> </span><span>If conservation efforts were aimed solely at threatened species, common species would experience a loss of 62% coverage. In contrast, if conservation plans were based only on common species, threatened species would suffer a loss of 1%.</span><span> Threatened species are rare and their ecological niches distinct, making them poor surrogates for biodiversity. The best results are achieved by unified planning for all species and habitats. The minimal step towards acknowledging common species in conservation planning would be the inclusion of the richness of common species, complemented by information on indicator species or species of high importance for ecosystem functioning. The trade-off between planning for rare and common species should be evaluated, to minimize losses to biodiversity. </span></p>
Effects of hypoxia and spawning on mitochondrial metabolism and bioenergetics of the blue mussel Mytilus spp. from the Baltic Sea
<p>We studied the effect of short-term hypoxia (7 days) and spawning (pre-spawning, and 3 h and 72 h post-spawning) on mitochondrial respiration, reactive oxygen species (ROS) production, and energy budget of the mussels Mytilus edulis. The data set reports oxygen consumption, efflux of reactive oxygen species (H2O2), fractional electrol leak (ratio of H2O2 efflux to O2 consumption) in isolated mitochondria, as well as the biochemical composition and energy content of the gills and the digestive gland tissues, tissue energy demand (measured as the activity to the electron transport system) and cellular energy allogation (CEA) in the tissues of the mussels.</p>
Near-bottom Oxygen observations from Western Baltic Sea
<p>The provided dataset includes the near-bottom oxygen observations (NBO) from the western Baltic Sea (8.5-16°E and 53.67-57.5°N) and is presented in detail by Friedland, Vock, Piehl (2023, https://www.mdpi.com/2073-4441/15/18/3235).</p> <p>The provided data consists of a couple of individual dataset from several freely usable sources: IOW measurement database, ICES Dataset of Hydrography, Boknis Eck time series, EU Copernicus Marine Data Store and the databases of the Mecklenburg Western Pomerania state office for Environment, Conservation and Geology (LUNG-MV) and the Schleswig-Holstein state office for the Environment (LfU-SH) respectively. From the different databases, we extracted the measured dissolved oxygen concentrations (or the measured oxygen saturation, which was converted following Weiss (1970)), location (longitude, latitude, water depth) and depth of the measurement. Aiming to unify the data in the joint dataset, the different datasets were transformed to mg/l, duplicates were removed and measurements at the same time and location obtained by different methods were averaged. Due to many inconsistencies between the measurement depth and bathymetric depth as well as large variations in the measured bathymetric depth of the respective measuring stations, the measured bathymetric depth given in the datasets was replaced by the bathymetric depth retrieved from iowtopo and EMODnet Bathymetry. The datasets mentioned above, included measurements of dissolved oxygen from the whole water column. To sort out the NBO, the deepest measurement was used, if it was close enough to the bottom using as threshold: for water depths below 16m, measurements within the lower 25% of the water column and for water depths above 16m measurements from a maximum of 4 meters above the sea floor were selected.</p>
Bulk Carbon and Amino Acid nitrogen isotope data from Baltic cod (Gadus morhua) and European flounder (Platichthys flesus) muscle tissue samples from the western and central Baltic Sea
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Centurial life history parameters in Baltic cod (Gadus morhua)
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Data for: High focus on threatened species and habitats may undermine biodiversity conservation: evidence from the northern Baltic Sea
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Moving towards a better understanding of iterative evolution: an example from the late Silurian Monograptidae (Graptolithina) of the Baltic Basin
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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.