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274 results for “baltic sea”
Figure 3 in Phylogeographic patterns in attached and free-living marine macroalga Fucus vesiculosus (Fucaceae, Phaeophyceae) in the Baltic Sea
Figure 3: Distribution of concatenated-barcode mtDNA intergenic spacer (IGS) and 23S haplotypes found within the Baltic sea Fucus vesiculosus population. Circle size is proportional to sample size (n) and form is indicated as A (attached) or F (free-living). Site abbreviations: As, AskÖ; HS, Hiddensee; OL, Olkiluoto; SA, Saaremaa; SE, Seili; TZ, Tvärminne. Scale: 200 km.
Figure 2 in Phylogeographic patterns in attached and free-living marine macroalga Fucus vesiculosus (Fucaceae, Phaeophyceae) in the Baltic Sea
Figure 2: Haplotype network analysis of Fucus vesiculosus using (A) concatenated-barcode mtDNA intergenic spacer (IGS) and 23S, and (B) mtDNA polymorphic region-intergenic spacer (pr-IGS). Circle size is proportional to the haplotype frequency. A branch represents a genetic distance and hash marks represent a single mutation. Branches drawn in broken grey lines represent genetic distances between non-linked haplotypes [not shown in (B)]. All undrawn branches between non-linked haplotypes within B equal <2 mutations. Segment colouration indicates the geographic origin of each haplotype whilst ellipses represent the coverage of each geographic region within the network. Site abbreviations: As, AskÖ; HS, Hiddensee; OL, Olkiluoto; SA, Saaremaa; SE, Seili; TZ, Tvärminne.
Figure 1 in Phylogeographic patterns in attached and free-living marine macroalga Fucus vesiculosus (Fucaceae, Phaeophyceae) in the Baltic Sea
Figure 1: Factorial analysis using mtDNA intergenic spacer (IGS) sequences for several Fucus species. Black, red and grey points represent Fucus vesiculosus, Baltic sea F. vesiculosus, and all other Fucus species, respectively. Species within cluster A: F. vesiculosus, F. spiralis, F. vesiculosus var. spiralis, F. cottonii, F. virsoides, F. guiryi; cluster B: F. ceranoides; cluster C: F. gardneri, F. distichus, F. evanescens.
Dormant phytoplankton "back to life" after 7000 years in Baltic Sea sediments
<p>Trait data conducted with strains of the Baltic Sea diatom <em>Skeletonema marinoi, </em>with strains from different temporal cohorts.<em> </em></p> <p><em>Publication not published!</em></p>
Quantitative real-time PCR assays Q2 for species-specific detection and quantification of Baltic Sea spring bloom dinoflagellates
<p>These are the data behind figures 2 to 7 in the paper: Brink AM, Kremp A and Gorokhova E (2024) Quantitative real-time PCR assays for species-specific detection and quantification of Baltic Sea spring bloom dinoflagellates. Front. Microbiol. 15:1421101. doi: 10.3389/fmicb.2024.1421101</p>
Results of the study "Untangling the Waves: Decomposing Extreme Sea Levels in a non-tidal basin, the Baltic Sea"
<p>This archive stores the data of the study "Untangling the Waves: Decomposing Extreme Sea Levels in a non-tidal basin, the Baltic Sea" submitted to the journal Natural Hazards and Earth System Sciences.</p>
Data from: Primary production calculations for sea ice from bio-optical observations in the Baltic Sea
Bio-optics is a powerful approach for estimating photosynthesis rates, but has seldom been applied to sea ice, where measuring photosynthesis is a challenge. We measured absorption coefficients of chromophoric dissolved organic matter (CDOM), algae, and non-algal particles along with solar radiation, albedo and transmittance at four sea-ice stations in the Gulf of Finland, Baltic Sea. This unique compilation of optical and biological data for Baltic Sea ice was used to build a radiative transfer model describing the light field and the light absorption by algae in 1-cm increments. The maximum quantum yields and photoadaptation of photosynthesis were determined from 14C-incorporation in photosynthetic-irradiance experiments using melted ice. The quantum yields were applied to the radiative transfer model estimating the rate of photosynthesis based on incident solar irradiance measured at 1-min intervals. The calculated depth-integrated mean primary production was 5 mg C m–2 d–1 for the surface layer (0–20 cm ice depth) at Station 3 (fast ice) and 0.5 mg C m–2 d–1 for the bottom layer (20–57 cm ice depth). Additional calculations were performed for typical sea ice in the area in March using all ice types and a typical light spectrum, resulting in depth-integrated mean primary production rates of 34 and 5.6 mg C m–2 d–1 in surface ice and bottom ice, respectively. These calculated rates were compared to rates determined from 14C incorporation experiments with melted ice incubated in situ. The rate of the calculated photosynthesis and the rates measured in situ at Station 3 were lower than those calculated by the bio-optical algorithm for typical conditions in March in the Gulf of Finland by the bio-optical algorithm. Nevertheless, our study shows the applicability of bio-optics for estimating the photosynthesis of sea-ice algae.
Data from: Platichthys solemdali sp. nov. (Actinopterygii, Pleuronectiformes): a new flounder species from the Baltic Sea
The European flounders Platichthys flesus (Linnaeus, 1758) displays two contrasting reproductive behaviors in the Baltic Sea: offshore spawning of pelagic eggs and coastal spawning of demersal eggs, a behavior observed exclusively in the Baltic Sea. Previous studies showed marked differences in behavioral, physiological, and life-history traits of flounders with pelagic and demersal eggs. Furthermore, a recent study demonstrated that flounders with pelagic and demersal eggs represent two reproductively isolated, parapatric species arising from two distinct colonization events from the same ancestral population. Using morphological data we first established that the syntypes on which the original description of P. flesus was based belong the pelagic-spawning lineage. We then used a combination of morphological and physiological characters as well as genome-wide genetic data to describe flounders with demersal eggs as a new species: Platichthys solemdali sp. nov. The new species can be clearly distinguished from P. flesus based on egg morphology, egg and sperm physiology as well as via population genetic and phylogenetic analyses. While the two species do show some minor morphological differences in the number of anal and dorsal fin rays, no external morphological feature can be used to unambiguously identify individuals to species. Therefore, we developed a simple molecular diagnostic test able to unambiguously distinguish P. solemdali from P. flesus with a single PCR reaction, a tool that should be useful to fishery scientists and managers, as well as to ecologist studying these species.
Figure 2 in Population dynamics of Pseudocalanus minutus elongatus in the Gulf of Gdansk (southern Baltic Sea) - experimental and numerical results
Figure 2. Vertical profiles of temperature (◦C) (A, B) and salinity (PSU) (C, D) at station J23 in 2006 and 2007, respectively.
Figure 6 in Population dynamics of Pseudocalanus minutus elongatus in the Gulf of Gdansk (southern Baltic Sea) - experimental and numerical results
Figure 6. Mean abundance of Pseudocalanus minutus elongatus from all stations and station J23 in the Gulf of Gdańsk for 2006 and 2007.
Figure 5 in Population dynamics of Pseudocalanus minutus elongatus in the Gulf of Gdansk (southern Baltic Sea) - experimental and numerical results
Figure 5. Vertical profiles of abundance (ind. m–3) of nauplii, CI to CV and adults (females and males) at station J23 for 2006 and 2007.
Figure 9 in Population dynamics of Pseudocalanus minutus elongatus in the Gulf of Gdansk (southern Baltic Sea) - experimental and numerical results
Figure 9. Total biomass (mg C m–3) of Pseudocalanus minutus elongatus as vertical mean concentrations at three stations (1, 2, 3 = J23) in the Gulf of Gdańsk; numerical simulations.
Figure 4 in Population dynamics of Pseudocalanus minutus elongatus in the Gulf of Gdansk (southern Baltic Sea) - experimental and numerical results
Figure 4. Stage structure of Pseudocalanus minutus elongatus in the Gulf of Gdańsk at station J23 for 2006 and 2007.
Figure 3 in Population dynamics of Pseudocalanus minutus elongatus in the Gulf of Gdansk (southern Baltic Sea) - experimental and numerical results
Figure 3. Taxonomical structure of Copepoda in the Gulf of Gdańsk (southern Baltic Sea) including data from all stations for 2006 and 2007.
Figure 11 in Population dynamics of Pseudocalanus minutus elongatus in the Gulf of Gdansk (southern Baltic Sea) - experimental and numerical results
Figure 11. Observed and simulated (based on monthly averaged) biomasses (mgm–3) of w.w. Pseudocalanus minutus elongatus at station J23 = 3 in the Gulf of Gdańsk. Calculated average values of all stations are also presented.
Figure 1 in Invasion of Eurytemora sibling species (Copepoda: Temoridae) from north America into the Baltic Sea and European Atlantic coast estuaries
Figure 1. Locations of the studied populations of E. affinis and E. carolleeae. Place names are listed in Table 1.
Figure 7 in Population dynamics of Pseudocalanus minutus elongatus in the Gulf of Gdansk (southern Baltic Sea) - experimental and numerical results
Figure 7. Weighted mean depth (WMD) of nauplii (N), copepodites (C1–3, C4–5) and adult (F, M) stages of Pseudocalanus minutus elongatus at station J23 in the Gulf of Gdańsk.
Figure 5 in Invasion of Eurytemora sibling species (Copepoda: Temoridae) from north America into the Baltic Sea and European Atlantic coast estuaries
Figure 5. Distribution of Eurytemora affinis and Eurytemora carolleeae individuals calculated on the base of indices: ind.1, ind.2, ind.3 (see text) (A) for females and (B) for males. Eurytemora affinis from the Gulf of Finland (open squares), from the Gulf of Riga (open triangles) and from the Vistula lagoon (open circles). E. carolleeae from the Gulf of Finland (filled square) and from the Gulf of Riga (filled triangles).
Figure 8 in Population dynamics of Pseudocalanus minutus elongatus in the Gulf of Gdansk (southern Baltic Sea) - experimental and numerical results
Figure 8. Vertical mean biomasses (mg C m–3) of eggs (Egg–N2), nauplii (N3–N6), younger copepodites (C1–C3), older copepodites (C4–C5) and adults at three stations (1, 2, 3 = J23) in the Gulf of Gdańsk; numerical simulations.
Figure 4 in Invasion of Eurytemora sibling species (Copepoda: Temoridae) from north America into the Baltic Sea and European Atlantic coast estuaries
Figure 4. Chosen morphological characters for analysis of Eurytemora carolleeae (A–C) and Eurytemora affinis (D–F): length and width of furcal branches (A, D), parts of male P5 swimming legs proportions (C, F), female genital segment (B, E).
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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.