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Fig. 3 in Refining the Occurrence of Viral Encephalopathy and Retinopathy, Photobacteriosis, and Vibriosis in Connection with Seawater Physicochemical Parameters: A Five-Year Case Study Abstract
Fig. 3: Presence/absence of fish diseases in the years 2011-2015. (A: VER - Viral Encephalopathy & Retinopathy, B: PHDP - Photobacteriosis, C: VAO1 - Vibriosis). For the presence of disease, the value was [1], and for absence, it was [0].
Fig. 5 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract
Fig. 5: Distribution and abundance maps of eggs during May (A, B) and July 2010 (C-E), in the NE Aegean Sea. The major patches are indicated by different colours, while the size of the circles is scaled by the maximum abundance per species and period (Table 2). The number of each patch indicates the ranking according to the abundance of individuals in each patch. The small black cross symbols show the centres of gravity (CG) of each major patch (i.e. those patches having more than 10% of the overall abundance; Table 3). The large cross indicates the CG of the population. The length of the cross axes indicate the isotropy of the egg distribution. The 200m isobaths are also shown (dark contour line).
Fig. 4 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract
Fig. 4: Box-and-whisker plots for temperature (oC; at 10 m depth), salinity (at 10 m depth), log-transformed integrated fluorescence (μg l-1) and log-transformed mesozooplankton biomass (mg m-2) between three groups of sampling stations: L – Lemnos plateau, O – offshore pelagic area north of Lemnos island, and T- Thracian Sea shelf. Boxes indicate median and interquartile ranges, whiskers delineate full ranges. F-values are provided for comparisons of the parameters between the three groups (L, O, T) and within each season. For comparisons that did not meet the assumptions of the analysis of variance, the Kruskal-Wallis statistic H is provided. Asterisks indicate significant differences: *p <0.05, **p <0.01, ***p <0.001. Post-hoc multiple comparisons were performed with a Student-Newman-Keul's test, where statistically significant differences among groups are indicated by letters a, b, c on the left side of each box. Groups with the same letter do not differ significantly.
Fig. 3 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract
Fig. 3: Contour maps of the vertical distribution of temperature (oC; left column), salinity (middle column) and fluorescence (μg Chlα l-1; right column) during May 2010 along transect A (A-C) and transect B (D-F), and during July 2010 along transects A (H-J) and B (K-M). Y-axis: depth of the water column; X-axis: distance (nmi) from the northern sampling station (0 nmi) to the southern station. The position (distance, nmi) of the sampling stations along the transects are shown in white, dashed lines on top of the temperature contour maps.
Fig. 2 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract
Fig. 2: Temperature (oC, 10 m depth; A, E), salinity (10 m; B, F), integrated fluorescence (μg Chl-a l-1, 0-100 m; C, G) and mesozooplankton biomass (mg m-2; D, H) during May (A-D) and July 2010 (E-H) in the study area.
Fig. 1 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract
Fig. 1: Ichthyoplankton (shown as open red circles) and CTD sampling stations (shown as filled red circles) during May and July 2010. The isobaths of 100 and 200 m are shown (light and dark blue lines, respectively). Black arrows indicate the main circulation pattern in the area: LIS - Lemnos-Imvros stream, SG - Samothraki gyre (Somarakis et al., 2002). The sampling stations of transects A and B (grey lines) show the vertical structure of the water column in Figure 3.
Fig. 3 in The nematode assemblage as a tool for the assessment of marine ecological quality status: a case-study in the Central Adriatic Sea
Fig. 3: Composition of colonizers-persisters (c-p) at each station and in each period. The c-p1 and c-p5 were excluded because they were not found in the study area.
Fig. 2 in The nematode assemblage as a tool for the assessment of marine ecological quality status: a case-study in the Central Adriatic Sea
Fig. 2: a) Shannon Index; b) Pielou Index; c) Maturity Index; d) Index of Trophic Dominance calculated for the nematode assemblage at each station in the study area.
Fig 4 in Diversity and taxonomic structure of aquatic macroinvertebrates in a fluvio-lacustrine system in south-west Côte d'Ivoire: The case of the Soubré hydroelectric dam lake
Fig 4: Hierarchical classification of sampling stations based on the similarity of assemblages of aquatic macroinvertebrate families.
Fig 6 in Evaluating the sustainability of fishery resources and fishing gears: Case study of Ngoyè and Elabè, Kribi, South Cameroon
Fig 6: Size structure of the three most fish species caught by bottom-set gillnet: a) Pseudotolithus typus; b) Pseudotolithus senegalensis; c) Cynoglossus sp.
Fig 5 in Evaluating the sustainability of fishery resources and fishing gears: Case study of Ngoyè and Elabè, Kribi, South Cameroon
Fig 5: Size structure of the three most fish species caught by beach seine: a) Ilisha Africana; b) Pseudotolithus senegalensis; c) Pseudotolithus typus
Fig. 2 in A New Measure Of Conservation Value Combining Rarity And Ecological Diversity: A Case Study With Light Trap Collected Caddisflies (Insecta: Trichoptera)
Fig. 2. The Rarity and Ecological Diversity (RED)-index of the different aquatic habitats (aquatic habitats with the same letter are not significantly different at p = 0.05 by non-parametric Tukey-test)
Fig. 1 in A New Measure Of Conservation Value Combining Rarity And Ecological Diversity: A Case Study With Light Trap Collected Caddisflies (Insecta: Trichoptera)
Fig. 1. The map of Hungary with the position of the sampling sites (filled squares show light traps)
Fig. 3 in A New Measure Of Conservation Value Combining Rarity And Ecological Diversity: A Case Study With Light Trap Collected Caddisflies (Insecta: Trichoptera)
Fig. 3. The diversity (A) and RAR-index (B) of the different aquatic habitats (aquatic habitats with the same letter are not significantly different at p = 0.05 by non-parametric Tukey-test)
Fig. 3 in Quantitative Biogeographic Characterization Of Hungary Based On The Distribution Data Of Land Snails (Mollusca,Gastropoda): A Case Of Nestedness Of Species Ranges With Extensive Overlap Of Biotic Elements
Fig. 3. Distribution maps of four biotic elements found by PRABCLUS: (a) highland species, (b) general species, (c) localizes species distributed in the northern and (d) south–eastern parts of Hungary. The different shadings indicate the areas where>70%,>30%, and>0% of the species of an ele-
Fig. 1 in Quantitative Biogeographic Characterization Of Hungary Based On The Distribution Data Of Land Snails (Mollusca,Gastropoda): A Case Of Nestedness Of Species Ranges With Extensive Overlap Of Biotic Elements
Fig. 1. Biogeographic classification of Hungary based on distribution data of land snails according to the (a) hierarchical clustering of the (b) spatial units (ca. 50 km × 50 km). For clustering, the Sørensen–index and Ward–Orlóci fusion method was used. Shades of grey indicate main partitions of the cluster hierarchy, circled numbers 1–6 indicate lower level partitions mentioned in the text, numbers 1–49 identify spatial units (a) in the cluster foot and (b) in the map. Capital letters correspond to IndVal species groups listed in the text and in Appendix, lines associated to letters refer to
Fig. 2 in Quantitative Biogeographic Characterization Of Hungary Based On The Distribution Data Of Land Snails (Mollusca,Gastropoda): A Case Of Nestedness Of Species Ranges With Extensive Overlap Of Biotic Elements
Fig. 2. First two dimensions of the metric multidimensional scaling of the range data of the Hungarian land snail species. 1–4: biotic elements found by PRABCLUS; N: noise component.
Fig. 1 in Spinosaurs As Phytosaur Mimics: A Case Of Convergent Evolution Between Two Extinct Archosauriform Clades
Fig. 1. Convergently shared craniodental characters between Spinosauridae (A) and Phytosauria with "brachyrostral" skull (B). Characters: 1. anterior ends of premaxilla and dentary are rounded, laterally and ventrally expanded and bear enlarged teeth ("rosettes"); 2. a concavity posterior to the premaxillary "rosette" that bears smaller teeth that accommodates the lower jaw "rosette" when the mouth is closed, accompanied by a medial constriction of this part of a snout; 3. a ventrally convex margin of the upper jaw behind concavity bearing enlarged teeth; 4. down-turn of the upper jaw towards its tip so that the anteroventral part of the nondentigerous region of the premaxillary "rosette" is at the same level with the tooth row in more posterior region; 5. laterally flattened snout that is moderately deepened dorsoventrally, unlike the dorsoventrally compressed condition in crocodilians; 6. relatively small size of an antorbital fenestra; 7. a bony palate that is formed by medial extensions of adjacent bones (e.g., premaxilla, maxilla); 8. a concavity in the anterior part of the dentary that receives a ventral expansion of the upper jaw; 9. lower teeth behind the dentary "rosette" significantly smaller than those of the "rosette". Images used in A are modified from Bertin (2010) and Ibrahim et al.
Fig. 2 in Spinosaurs As Phytosaur Mimics: A Case Of Convergent Evolution Between Two Extinct Archosauriform Clades
Fig. 2. Cranial evolution of Phytosauria (A) and Spinosauridae (B), with lateral and dorsal views of the skull/snout, shared morphological changes highlighted. Phytosauria is represented by the early-diverging, dolichorostral Parasuchus hislopi and the laterdiverging, brachyrostral Machaeroprosopus mccauleyi. Spinosauridae is represented by the early-diverging Suchomimus tenerensis and the later-diverging Spinosaurus aegyptiacus. Images used in A are modified from Datta et al. (2021), and those of B, from Sereno et al. (1998) and Ibrahim et al. (2020), respectively.
Fig. 3 in Spinosaurs As Phytosaur Mimics: A Case Of Convergent Evolution Between Two Extinct Archosauriform Clades
Fig. 3. Differences between the snouts of early-diverging (Baryonyx walkeri, after Bertin, 2010) and later-diverging (Oxalaia quilombensis, after Kellner et al., 2011) spinosaurid taxa in ventral (A) and lateral (B) views, with morphological differences highlighted.
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.