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243 results for “Coastal area”
Fig. 9. Grandidierella osakaensis Ariyama, 1996 in Three Species of Grandidierella (Crustacea: Amphipoda: Aoridae) from Coastal Areas of the Tohoku and Kanto-Tokai Districts, East Japan, with the Description of Two New Species
Fig. 9. Grandidierella osakaensis Ariyama, 1996. Male (OMNH-Ar-10297), 5.8 mm. Habitus, left lateral view, pereopod 7 lost.
Fig. 5 in Three Species of Grandidierella (Crustacea: Amphipoda: Aoridae) from Coastal Areas of the Tohoku and Kanto-Tokai Districts, East Japan, with the Description of Two New Species
Fig. 5. Grandidierella sanrikuensis sp. nov. Holotype, male (OMNH-Ar-10195), 7.7 mm. A, left gnathopod 1, lateral view; B, left gnathopod 2, lateral view; B1, distal part of left gnathopod 2, lateral view, normal setae omitted; C–G, left pereopods 3–7, lateral views. Scales: 0.2 mm.
Distribution. Coastal plains and montane areas of E Kenya and Tanzania. in Nesomyidae
Distribution. Coastal plains and montane areas of E Kenya and Tanzania.
Distribution. NW Mexico (restricted area along the coastal plains in NW Baja California). in Heteromyidae
Distribution. NW Mexico (restricted area along the coastal plains in NW Baja California).
Distribution. Coastal areas of S Sinaloa and Nayarit, Mexico. in Cricetidae
Distribution. Coastal areas of S Sinaloa and Nayarit, Mexico.
Distribution. Coastal areas of Jalisco and Colima states (W Mexico). in Cricetidae
Distribution. Coastal areas of Jalisco and Colima states (W Mexico).
Figure 1 in Towards a framework for invasive aquatic plant survey design in Great Lakes coastal areas
Figure 1. Great Lakes basin showing the five sites where aquatic vegetation sampling occurred. Data credits: Lakes: Great Lakes Aquatic Habitat Framework (GLAHF) Great Lakes shoreline v 1.1, 2014. Basin: Institute for Fisheries Research Great Lakes GIS basin outline GLB_basin_outline_noSLS_IFR, 2004. States/Provinces: ArcGIS Content Team U.S. States and Canada Provinces, 2010.
Figure 4 in Towards a framework for invasive aquatic plant survey design in Great Lakes coastal areas
Figure 4. The predicted richness surface (from forest classification model) showing, (A) predicted plant richness for each grid (sample unit), (B) the grids sampled with rakes (highlighted), and (C) the cells intersected with boat track during the 2019 Milwaukee survey (highlighted).
Health Equity and Synergistic Abatement Strategies of Carbon and Air Pollutant Reduction in China's Eastern Coastal Area
Open the record for dataset details and reuse information.
Fig. 5 in Spatial variation of summer microphytoplankton and zooplankton communities related to environmental parameters in the coastal area of Djerba Island (Tunisia, Eastern Mediterranean) Abstract
Fig. 5: Spatial variations of zooplankton abundance, zooplankton groups, dominant species, species richness and species diversity index along the west and east coasts of Djerba Island.
Fig. 3 in Assessment of coastal fish assemblages before the establishment of a new marine protected area in the central Mediterranean: its role in formulating a zoning proposal Abstract
Fig. 3: Species richness (mean number of species ± S.E.) of fishes recorded along the random courses at each (a) sector, (b) habitat type (POM=Posidonia oceanica meadow; RAR=rockyalgal reef; SOB=soft bottom) and (c) depth range.
FIGURE 4 in Reproductive biology of Parona signata (Actinopterygii: Carangidae), a valuable economic resource, in the coastal area of Mar del Plata, Buenos Aires, Argentina
FIGURE 4 | Frequency distribution of oocyte diameters (n=3,000 oocytes measured of Parona signata). From black bars to white bars: primary growth oocyte, cortical alveoli, yolked oocytes and hydrated oocytes, respectively.
Fig. 2 in Spatial variation of summer microphytoplankton and zooplankton communities related to environmental parameters in the coastal area of Djerba Island (Tunisia, Eastern Mediterranean) Abstract
Fig. 2: Spatial variations of physical-chemical parameters: temperature, salinity, pH, Dissolved Oxygen and/ Depth Transparency along the western and eastern coasts of Djerba Island.
Fig. 1 in A report of 20 unrecorded bacterial species in Korea, isolated from soils of coastal areas in 2022
Fig. 1. Neighbor-joining phylogenetic tree based on 16S rRNA gene sequences showing the relationship between the strains isolated in this study and their closest bacterial species. Bootstrap values over 70% are shown. Scale bar = 0.02 substitutions per nucleotide position.
Supplementary material 1 from: Hartz SM, Rocha EA, Brum FT, Luza AL, Guimarães TFR, Becker FG (2019) Influences of the area, shape and connectivity of coastal lakes on the taxonomic and functional diversity of fish communities in Southern Brazil. Zoologia 36: 1-12. https://doi.org/10.3897/zoologia.36.e23539
: Data type: species data
Supplementary material 2 from: Hartz SM, Rocha EA, Brum FT, Luza AL, Guimarães TFR, Becker FG (2019) Influences of the area, shape and connectivity of coastal lakes on the taxonomic and functional diversity of fish communities in Southern Brazil. Zoologia 36: 1-12. https://doi.org/10.3897/zoologia.36.e23539
: Data type: species data
Figure 2 from: Hartz SM, Rocha EA, Brum FT, Luza AL, Guimarães TFR, Becker FG (2019) Influences of the area, shape and connectivity of coastal lakes on the taxonomic and functional diversity of fish communities in Southern Brazil. Zoologia 36: 1-12. https://doi.org/10.3897/zoologia.36.e23539
Figure 2 The final path model showing the causal relationships between the landscape variables and both the taxonomic and functional diversity of fish communities in the coastal lakes of the Tramandaí River Basin in Southern Brazil. Dotted line = not significant (p > 0.05). The curved double-headed arrows in grey depict correlated errors among variables.
Figure 1 from: Hartz SM, Rocha EA, Brum FT, Luza AL, Guimarães TFR, Becker FG (2019) Influences of the area, shape and connectivity of coastal lakes on the taxonomic and functional diversity of fish communities in Southern Brazil. Zoologia 36: 1-12. https://doi.org/10.3897/zoologia.36.e23539
Figure 1 Hypothetical framework used to build the path model, with plausible causal connections between the landscape variables and both the taxonomic and functional diversity of the fish communities of the coastal lakes of the Tramandaí River Basin in Southern Brazil
Supplementary material 3 from: Hartz SM, Rocha EA, Brum FT, Luza AL, Guimarães TFR, Becker FG (2019) Influences of the area, shape and connectivity of coastal lakes on the taxonomic and functional diversity of fish communities in Southern Brazil. Zoologia 36: 1-12. https://doi.org/10.3897/zoologia.36.e23539
: Data type: species data
Supplementary material 4 from: Hartz SM, Rocha EA, Brum FT, Luza AL, Guimarães TFR, Becker FG (2019) Influences of the area, shape and connectivity of coastal lakes on the taxonomic and functional diversity of fish communities in Southern Brazil. Zoologia 36: 1-12. https://doi.org/10.3897/zoologia.36.e23539
: Data type: species data
ScienceDex guides
Understand access before you commit
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.