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274 results for “baltic sea”
Data from: Parallel speciation or long-distance dispersal? Lessons from seaweeds (Fucus) in the Baltic Sea
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Data from: Echinorhynchus salmonis Müller, 1784 (Acanthocephala: Echinorhynchidae) from the Bothnian Bay, Baltic Sea: morphological variability and radial asymmetry of proboscis hooks
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Community weighted mean traits of multi-trophic communities in the Baltic Sea
<p>The dataset contains the time-series of community weighted mean traits of four organism groups (phytoplankton, zooplankton, benthos, fish) in three different areas of the Baltic Sea and the associated R code to make the figures as in Pecuchet et al. <em>Ecography </em></p>
Data from: Evidence for adaptive phenotypic differentiation in Baltic Sea sticklebacks
The evidence for adaptive phenotypic differentiation in mobile marine species remains scarce, partly due to the difficulty of obtaining quantitative genetic data to demonstrate the genetic basis of the observed phenotypic differentiation. Using a combination of phenotypic and molecular genetic approaches, we elucidated the relative roles of natural selection and genetic drift in explaining lateral plate number differentiation in threespine sticklebacks (Gasterosteus aculeatus) across the entire Baltic Sea basin (ca. 392 000 km2). We found that phenotypic differentiation (PST = 0.213) in plate number exceeded that in neutral markers (FST = 0.008), suggesting an adaptive basis for the observed differentiation. Since a close correspondence was found between plate phenotype and genotype at a QTL (STN381) tightly linked to the gene (Ectodysplasin) underlying plate variation, the evidence for adaptive differentiation was confirmed by comparison of FST at the QTL (FSTQ = 0.089) with FST at neutral marker loci. Hence, the results provide a comprehensive demonstration of adaptive phenotypic differentiation in a high gene flow marine environment with direct, rather than inferred, verification for the genetic basis of this differentiation. In general, the results illustrate the utility of PST – FST – FSTQ comparisons in uncovering footprints of natural selection and evolution, and add to the growing evidence for adaptive genetic differentiation in high-gene flow marine environments, including that of the relatively young Baltic Sea.
Data from: Local adaptation and oceanographic connectivity patterns explain genetic differentiation of a marine diatom across the North Sea-Baltic Sea salinity gradient
Drivers of population genetic structure are still poorly understood in marine micro-organisms. We exploited the North Sea–Baltic Sea transition for investigating the seascape genetics of a marine diatom, Skeletonema marinoi. Eight polymorphic microsatellite loci were analysed in 354 individuals from ten locations to analyse population structure of the species along a 1500-km-long salinity gradient ranging from 3 to 30 psu. To test for salinity adaptation, salinity reaction norms were determined for sets of strains originating from three different salinity regimes of the gradient. Modelled oceanographic connectivity was compared to directional relative migration by correlation analyses to examine oceanographic drivers. Population genetic analyses showed distinct genetic divergence of a low-salinity Baltic Sea population and a high-salinity North Sea population, coinciding with the most evident physical dispersal barrier in the area, the Danish Straits. Baltic Sea populations displayed reduced genetic diversity compared to North Sea populations. Growth optima of low salinity isolates were significantly lower than those of strains from higher native salinities, indicating local salinity adaptation. Although the North Sea–Baltic Sea transition was identified as a barrier to gene flow, migration between Baltic Sea and North Sea populations occurred. However, the presence of differentiated neutral markers on each side of the transition zone suggests that migrants are maladapted. It is concluded that local salinity adaptation, supported by oceanographic connectivity patterns creating an asymmetric migration pattern between the Baltic Sea and the North Sea, determines genetic differentiation patterns in the transition zone.
Spatial genetic structure in a crustacean herbivore highlights the need for local considerations in Baltic Sea biodiversity management
<p>Incorporating species' eco-evolutionary responses to human-caused disturbances remains a challenge in marine management efforts. A prerequisite is knowledge of geographic structure and scale of genetic diversity and connectivity - the so-called seascape genetic patterns. The Baltic Sea is an excellent model system for studies linking seascape genetics with effects of anthropogenic stress. However, seascape genetic patterns in this area are only described for a few species and are completely unknown for invertebrate herbivores, which constitute a critical part of the ecosystem. This information is crucial for sustainable management, particularly under future scenarios of rapid environmental change. Here, we investigate the population genetic structure among 31 locations throughout the Baltic Sea, of which 45 % were located in marine protected areas, in one of the most important herbivores of this region, the isopod crustacean <i>Idotea balthica</i>, using an array of 33,774 genome-wide SNP markers derived from 2b-RAD sequencing. In addition, we generate a biophysical connectivity matrix for <i>I. balthica</i> from a combination of oceanographic current models and estimated life history traits. We find population structure on scales of hundreds of kilometers across the Baltic Sea, where genomic patterns in most cases closely match biophysical connectivity, indicating passive transport with oceanographic currents as an important mean of dispersal in this species. We also find a reduced genetic diversity in terms of heterozygosity along the main salinity gradient of the Baltic Sea, suggesting periods of low population size. Our results provide crucial information for management of a key ecosystem species under expected changes in temperature and salinity following global climate change in a marine coastal area.</p>
FIGURE 7 in Baltic Sea Gastrotricha—one new species and one new record of Chaetonotida from Poland
FIGURE 7. Aspidiophorus lamellophorus Balsamo, Hummon, Todaro et Tongiorgi, 1997. Habitus.
FIGURE 4 in Checklist of Gastrotricha of the Polish Baltic Sea with the first reports of Heterolepidoderma joermungandri Kånneby, 2011, and Turbanella hyalina Schultze, 1853
FIGURE 4. Heterolepidoderma joermungandri Kånneby, 2011. Adult specimen—habitus.
FIGURE 11. Turbanella hyalina Schultze, 1853 in Checklist of Gastrotricha of the Polish Baltic Sea with the first reports of Heterolepidoderma joermungandri Kånneby, 2011, and Turbanella hyalina Schultze, 1853
FIGURE 11. Turbanella hyalina Schultze, 1853. Adult specimen—habitus.
Supplementary material 1 from: Vivó-Pons A, Wallin-Kihlberg I, Olsson J, Ljungberg P, Behrens J, Lindegren M (2023) The devil is in the details: exploring how functionally distinct round goby is among native fish in the Baltic Sea. NeoBiota 89: 161-186. https://doi.org/10.3897/neobiota.89.110203
Supplementary information
Multitemporal DSMs and orthomosaics of a beach nourishment at the Baltic Sea
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Fig. 7. Cottus microstomus Heckel, 1837 in A new species of the genus Cottus (Scorpaeniformes, Cottidae) from the Baltic Sea Basin and its phylogenetic placement
Fig. 7. Cottus microstomus Heckel, 1837 (ZIN 56723), SL 78.4 mm, Siesartis River, Neman/Nemunas River basin (Lithuania).
Fig. 6 in A new species of the genus Cottus (Scorpaeniformes, Cottidae) from the Baltic Sea Basin and its phylogenetic placement
Fig. 6. Bayesian phylogenetic tree of the freshwater species of Cottidae reconstructed using mtDNA control region sequences. Bayesian posterior probabilities (on the top side) and bootstrap values from a ML analysis (on the down side) are shown. Results of species delimitation with bPTP support values are presented.
Figure 2 in New records from the southern North Sea and first records from the Baltic Sea of Kornmannia leptoderma
Figure 2: Life cycle stages of Kornmannia leptoderma, raised from material collected in Mönkeberg (A–E) and Heiligenhafen (F–H). Primary thallus disks after (A) 3 months, (B) 4 months and (C) 10 months, in (C) surrounded by five secondary thallus disks. (D) secondary basal disk bearing a young erect tubular thallus on the left and newly germinated filaments on the right (after 12 months). (E) primary disk and two dead tubular thalli (after 15 months). (F) and (G) primary basal disk bearing two erect tubular thallus branches of different size and surrounded by early filamentous stages of secondary disks (5.5 months). (H) biflagellate swarmer. Arrows indicate flagella in (H) and tubular sporophytes in other images, the latter appear often blurred because images were taken with an inverted microscope through the bottom of the culture vessel. Length of scale bars: 50 µm in (A), (B), (D), (F) and (G), 1 mm in (C) and (E), 20 µm in (H).
Fig. 3 in Planktonic Ciliates of the Neva Estuary (Baltic Sea): Community Structure and Spatial Distribution
Fig. 3. Distribution patterns of ciliate abundance (ind ml–1, dark bars) and biomass (× 10–3 µg C ml–1, empty bars) in the Neva Estuary.
Fig. 4 in Planktonic Ciliates of the Neva Estuary (Baltic Sea): Community Structure and Spatial Distribution
Fig. 4. Relative abundance (%) of different size groups of ciliates in the Neva Estuary. Data are not presented for four stations (indicated by points) with extremely low ciliate abundances (<0.1 ind ml–1).
Fig. 7. Relative ATPase activity treated with 21 in Seasonal variation of phenolic compounds in Zostera marina (Zosteraceae) from the Baltic Sea
Fig. 7. Relative ATPase activity treated with 21 in micromolar range.
Fig. 3 in Seasonal variation of phenolic compounds in Zostera marina (Zosteraceae) from the Baltic Sea
Fig. 3. Chemical structure and HMBC key correlations of 7′′,8′′ -didehydrosalvianolic acid B.
Figure 3 in Hatching success in brackish water of Perca fluviatilis eggs obtained from the western Baltic Sea
Figure 3. - Distribution of the overall clades of perch Perca fluviatilis in Europe, upper map and western Baltic Sea, lower map; Sweden (SWE), Denmark (DEN) and Germany (GER). The pie charts show the relative distribution within a sampling site, and the size of the pie chart the relative sample size. * = fusion of 2 sample sites, ** = fusion of 3 sample sites, *** = fusion of 5 sample sites, **** = fusion of 6 sample sites. Colours are uniform with colours in figure 2.
Figure 2 in Hatching success in brackish water of Perca fluviatilis eggs obtained from the western Baltic Sea
Figure 2. - Haplotype network of perch Perca fluviatilis in Europe (n = 707). Each line represents one base pair substitution. Two component numbers (x-y) refers to clade number (x) and haplotype (y). Circle sizes are relative to number of individuals (see text for references).
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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.