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1,579 results for “Baltics”
Figure 5 in Fucus vesiculosus adapted to a life in the Baltic Sea: impacts on recruitment, growth, re-establishment and restoration
Figure 5: Boxplot showing germination (%) of Fucus vesiculosus zygotes after 7 days of exposure under laboratory conditions to exudates from Cladophora glomerata, Ulva intestinalis, Pylaiella littoralis, Ceramium tenuicorne and Hildenbrandia rubra. All treatments differed (p <0.001) from the control (one way ANOVA). n = 6 for all treatments.
Figure 4 in Fucus vesiculosus adapted to a life in the Baltic Sea: impacts on recruitment, growth, re-establishment and restoration
Figure 4: Boxplot showing number of Fucus vesiculosus juveniles per dm2 on five different types of substratum. (A) Askö, after 5 months, n = 10 except ceramic tile (n = 7) and Hildenbrandia treatment (n = 9). (B) Räfsnäs after 4 months, sample size n = 6. Note major difference in scales for y-axes in each panel. Letters (A–E) above bars show groups that differ significantly (at p = 0.05) within each site according to Tukey HSD post hoc test.
Figure 2 in Seaweed resources of the Baltic Sea, Kattegat and German and Danish North Sea coasts
Figure 2: Loose-lying Furcellaria lumbricalis-Coccotylus truncatus community in the Kassari Bay, West Estonian Archipelago Sea (Photo: K. Kaljurand).
Figure 3 in Seaweed resources of the Baltic Sea, Kattegat and German and Danish North Sea coasts
Figure 3: Interannual variation (1980–2017) of the total community biomass (BM), the total Furcellaria lumbricalis biomass and the area of the loose-lying red algal community in the Kassari Bay, West Estonian Archipelago Sea. Data after Martin et al. (2006a), updated with data of the Estonian Marine Institute on annual monitorings 2003–2017.
Vertical distribution of heterotrophic nanoflagellates in the Baltic Proper
<p>This dataset contains data on the abundance of prokaryotes, heterotrophic nanoflagellates (HNF), specific lineages of HNF and environmental factors in the Baltic Sea collected during four cruises of r/v Baltica (National Fisheries Research Institute) in 2021. The Excel file includes six sheets:</p> <ol> <li>The "Parameters-Data" sheet lists all parameters for data presented in the "Data" sheet. Column A (Name) contains the variables names, column B (Unit) contains units in which they were measured, column C (Method/Device) contains information on the methodology, and column D (Comments) contains additional information</li> <li>The "Data" sheet contains data in a wide format for all variables listed in the "Parameters-Data" sheet measured at sampling depths. The first row contains variable names (listed in Column A of the Parameters-Data sheet) with units in square brackets</li> <li>The "Parameter-Size" sheet lists parameters for data presented in the "Size" sheet in the same format as described for the "Parameters-Data" sheet. Starting from row 5 in columns A and B, the number of measured HNF cells for each sample is given </li> <li>The "Size" sheet contains size measurements of HNF in the samples in a long format. The number of cells measured in each sample is provided in the "Parameter-Size" sheet</li> <li>The "Parameters-CTD depth profiles" sheet lists parameters for data presented in the "CTD depth profiles" sheet in the same format as described for the "Parameters-Data" sheet.</li> <li>The "CTD depth profiles" sheet contains full-depth profiles of variables measured with a CTD probe with 1 m resolution.</li> </ol>
Chesapeake Bay and Baltic Sea phytoplankton sample metadata
<p>We analyze the relationship between species richness, salinity and resource use efficiency from 10712 summer (June to September) surface phytoplankton samples from the Chesapeake Bay (n=3967) and the Baltic Sea (n=6745). As sample species richness (alpha diversity) has a U-shape distribution along an estuarine salinity gradient and species richness is known to scale with resource use efficiency – an important ecosystem function, we hypothesized that the ecosystem function can be predicted from salinity.</p>
Figure 4 in A new genus of predatory midge in the Monohelea complex from Eocene Baltic amber (Diptera: Ceratopogonidae)
Figure 4. Schizohelea baltica (Szadziewski, 1988), comb. nov., female MAIG 5624. A) Total habitus. B) Head. C) Distal tarsomeres and claws of hind legs.
Figure 3 in A new genus of predatory midge in the Monohelea complex from Eocene Baltic amber (Diptera: Ceratopogonidae)
Figure 3. Male genitalia of genera in the Monohelea complex. A) Aedeagus of Allohelea israelensis Szadziewski and Alwin-Kownacka, 2016 in Alwin-Kownacka et al. (2016), redrawn from Alwin-Kownacka et al. (2016). B) Aedeagus of Isthmohelea disjuncta Ingram and Macfie, 1931, redrawn from Wirth and Grogan (1988). C) Aedeagus of Monohelea mediterranea Szadziewski et al., 2020, redrawn and modified from Szadziewski et al. (2020). D) Aedeagus of Austrohelea shannoni (Wirth and Blanton, 1972), redrawn and modified from Ronderos et al. (2017). E) Aedeagus of Downeshelea stonei (Wirth, 1953), redrawn from Wirth and Grogan (1988). F) Aedeagus of Schizohelea leucopeza (Meigen, 1804), extant male from Norway, coll. MAIG. G) Aedeagus of Monogedania clunipes (Loew, 1850), MAIG 3391. H) Dorsal aspect of male genitalia of Monogedania clunipes (Loew, 1850), redrawn from Szadziewski (1988).
Figure 2 in A new genus of predatory midge in the Monohelea complex from Eocene Baltic amber (Diptera: Ceratopogonidae)
Figure 2. Male of Monogedania clunipes. A) Lateral aspect, MAIG 6010. B) Head and antenna, MAIG 5621. C) Hind tarsi, MAIG 6010. D) Abdomen with inverted genitalia, MAIG 5621. E–F) Lateral views of genitalia, photograph (E), illustration (F), MAIG 6694. Abbreviations: aed–aedeagus, gst–gonostylus, gx–gonocoxite, par– parameres, st 9–sternite 9, tg 9–tergite 9,?–penis.
Figure 1 in A new genus of predatory midge in the Monohelea complex from Eocene Baltic amber (Diptera: Ceratopogonidae)
Figure 1. Monogedania clunipes (Loew, 1850). A) Male, from collection of Artur Michalski. B) Female, MAIG 2109.
Fig. 1–4 in A New Species Of Globicornis (Hadrotoma) (Coleoptera, Dermestidae, Megatominae) From Baltic Amber
Fig. 1–4. Globicornis (Hadrotoma) ingelehmannae sp. n. (holotype): 1 — habitus, dorsal aspect; 2 — habitus, ventral aspect (→ = prosternal "collar"); 3 — antennal club (schematically); 4 — holotype of G. (H.) ambericus Háva, Prokop et Herrmann, 2006.
Fig. 1 in New Records Of The Dipteran Genera Triphleba (Phoridae) And Prosphyracephala (Diopsidae) In Rovno And Baltic Ambers
Fig. 1. Triphleba schulmanae: a — lateral view, b — dorsal view, c — anterodorsal view, with exposed bifurcate antennae; Prosphyracephala aff. succini: d — habitus, e — wings; Prosphyracephala kerneggeri: f — ventral, g — dorsal; Prosphyracephala succini: h — habitus.
Fig. 6. A in New species of belytine and diapriine wasps (Hymenoptera: Diapriidae) from Eocene Baltic amber
Fig. 6. A. Basalys villumi sp. nov., paratype (NHMD-608369), habitus in lateral view. B–D. Doliopria baltica sp. nov., holotype (NHMD-608374). B. Habitus in lateral view. C. Head in lateral view. D. Mesosoma and metasoma in lateral view. E–H. Spilomicrus succinalis sp. nov. E–F. Holotype (NHMD-607131). E. Habitus in ventrolateral view. F. Head and mesosoma in dorsal view. G. Paratype (NHMD-608344), habitus in lateral view. H. Paratype (NHMD-608354), habitus in lateral view. Abbreviations: asp = anterior scutellar pit; te = tergite excision. Scale bars: A, E–H = 1 mm; B = 0.5 mm; C–D = 0.25 mm.
Fig. 5. A–C in New species of belytine and diapriine wasps (Hymenoptera: Diapriidae) from Eocene Baltic amber
Fig. 5. A–C. Pantolyta chemyrevae sp. nov., holotype (NHMD-608448). A. Habitus in dorsolateral view. B. Head and mesosoma in dorsal view. C. Petiole in lateral view. D–E. Pantolyta similis sp. nov., holotype (NHMD-608468). D. Habitus in lateral view. E. Mesosoma, petiole and anterior gaster in dorsal view. F–H. Basalys villumi sp. nov., holotype (NHMD-608360). F. Habitus in lateral view. G. Head in lateral view. H. Head and mesosoma in dorsal view. Abbreviations: asp = anterior scutellar pit; fe = flagellomere emargination; mpk = median propodeal keel. Scale bars: A, D, F = 1 mm; B, E, G–H = 0.5 mm; C = 0.25 mm.
Fig. 3. A–C in New species of belytine and diapriine wasps (Hymenoptera: Diapriidae) from Eocene Baltic amber
Fig. 3. A–C. Cinetus elongatus sp. nov., holotype (NHMD-608402). A. Habitus in lateral view. B. Head in lateral view. C. Mesosoma and petiole in lateral view. D–H. Pantoclis globosa sp. nov. D–F. Holotype (NHMD-608414). D. Habitus in lateral view. E. Habitus in dorsal view. F. Gaster in lateral view. G–H. Paratype (NHMD-608394). G. Habitus in lateral view. H. Habitus in dorsal view. Abbreviations: asp = anterior scutellar pit; fe = flagellomere emargination; mtr = metapleural ridge. Scale bars: A = 2 mm; B–E, G–H = 1 mm; F = 0.5 mm.
Fig. 2. A–D in New species of belytine and diapriine wasps (Hymenoptera: Diapriidae) from Eocene Baltic amber
Fig. 2. A–D. Belyta knudhoejgaardi sp. nov. A–C. Holotype (NHMD-608408). A. habitus in lateral view. B. Mesosoma and petiole in lateral view. C. Petiole and gaster in dorsal view. D. Paratype NHMD-608400, habitus in lateral view. E–F. Cinetus breviscapus sp. nov., holotype (NHMD-300622). E. Habitus in lateral view. F. Head in lateral view. Abbreviations: fe = flagellomere emargination; mlr = mesopleural longitudinal ridge; mpk = median propodeal keel. Scale bars: A = 2 mm; B, F = 0.5 mm; C–E = 1 mm.
Fig. 4 in New species of belytine and diapriine wasps (Hymenoptera: Diapriidae) from Eocene Baltic amber
Fig. 4. Pantolyta augustinusii sp. nov. A–D. Holotype (NHMD-300829). A. Habitus in dorsal view. B. Head in frontal view. C. Detail of the anterior mesosoma in dorsal view. D. Gaster and petiole in lateral view.E. Paratype (NHMD-608391), habitus in lateral view. F. Paratype (NHMD-608406), habitus in lateral view. G. Paratype (NHMD-608412), habitus in lateral view. H. Paratype (NHMD-608404), habitus in dorsal view. Abbreviations: asp = anterior scutellar pit; fe = flagellomere emargination; t = toruli. Scale bars: A–B, D–H = 1 mm; C = 0.5 mm.
Thetis Baltic Sea simulation: model and observation data sets
<p>Model and observation data sets used in article "Adjoint-based optimization of a regional water elevation model".</p>
ADCP and GETM simulation data in the Baltic Proper
<p>The dataset is complementary material of the Liblik et al. 2022 study https://doi.org/10.5194/os-2021-123.</p> <p>The dataset includes: 1) 6 months of ADCP current data in MatLab mat format collected at the eastern coast of Baltic Proper. 2) GETM model data (zipped netcdf files) at the zonal transect (see Fig. 1 https://doi.org/10.5194/os-2021-123).</p>
Estimating the abundance of the critically endangered Baltic Proper harbour porpoise (Phocoena phocoena) population using passive acoustic monitoring
<p>Knowing the abundance of a population is a crucial component to assess its conservation status and develop effective conservation plans. For most cetaceans, abundance estimation is difficult given their cryptic and mobile nature, especially when the population is small and has a transnational distribution. In the Baltic Sea, the number of harbour porpoises (<i>Phocoena phocoena</i>) has collapsed since the mid-20<sup>th</sup> century and the Baltic Proper harbour porpoise is listed as Critically Endangered by the IUCN and HELCOM; however, its abundance remains unknown. Here, one of the largest ever passive acoustic monitoring studies was carried out by eight Baltic Sea nations to estimate the abundance of the Baltic Proper harbour porpoise for the first time. By logging porpoise echolocation signals at 298 stations during May 2011-April 2013, calibrating the loggers' spatial detection performance at sea, and measuring the click rate of tagged individuals, we estimated an abundance of 71-1,105 individuals (95% CI, point estimate 491) during May-October within the population's proposed management border. The small abundance estimate strongly supports that the Baltic Proper harbour porpoise is facing an extremely high risk of extinction, and highlights the need for immediate and efficient conservation actions through international cooperation. It also provides a starting point in monitoring the trend of the population abundance to evaluate the effectiveness of management measures and determine its interactions with the larger neighbouring Belt Sea population. Further, we offer evidence that design-based passive acoustic monitoring can generate reliable estimates of the abundance of rare and cryptic animal populations across large spatial scales.</p>
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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.