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517 results for “Floodplain”
Figures 1–4 in The freshwater medusa Limnocnida and associated plankton in the floodplain of the Ayeyarwaddy River, Myanmar
Figures 1–4. Limnocnida from Myanmar. (1) Whole umbrella showing primary tentacles on one quadrant, and all tentacles on another quadrant. (2) Umbrella margin, showing bases of two primary tentacles with associated secondary tentacles and statocysts. (3) Part of the basal region of a tentacle showing groups of nematocysts. (4) Arrangement of nematocysts near the tip of a tentacle.
Fig. 2 in Effects of flood regime on the diet of Triportheus curtus (Garman, 1890) in an Amazonian floodplain lake
Fig. 2. Variation in river level (measured every three days) during the hydrological cycle from 2008 to 2009 in Lake Amapá. Gray line shows the threshold level for flooding from the Acre River. Main periods of pre-flooding, flooding, and postflooding are indicated at the base of the graph.
Fig. 7. a in Ecomorphological patterns of the fish assemblage in a tropical floodplain: effects of trophic, spatial and phylogenetic structures
Fig. 7. a) Diagram of Canonical Discriminant Analysis for the ecomorphological indices of the fish assemblage grouping in habitat types in the upper Paraná River floodplain (rivers, channels, connected and disconnected lagoons). b) Histograms with the scores of the habitat types for Canonical axis 1.
Fig. 6 in Ecomorphological patterns of the fish assemblage in a tropical floodplain: effects of trophic, spatial and phylogenetic structures
Fig. 6. Diagram of Canonical Discriminant Analysis for the ecomorphological indices of the fish assemblage grouping in trophic guilds in the upper Paraná River floodplain (detritivores, insectivores, piscivores, invertivores, omnivores and herbivores).
Fig. 4 in Ecomorphological patterns of the fish assemblage in a tropical floodplain: effects of trophic, spatial and phylogenetic structures
Fig. 4. Distribution of scores centroids of the 35 species on the first two axes of the Principal Components Analysis (PC 1 and PC 2), applied to the correlation matrix (Pearson) formed by 22 ecomorphological indices. Each polygon defines the morphological space occupied by the species that compose the corresponding trophic guild.
Fig. 5 in Ecomorphological patterns of the fish assemblage in a tropical floodplain: effects of trophic, spatial and phylogenetic structures
Fig. 5. Distribution of scores centroids of the 35 species grouped by habitat type on the first two axes of the Principal Components Analysis (PC 1 and PC 2), applied to the correlation matrix (Pearson) formed by 22 ecomorphological indices. Each polygon defines the morphological space occupied by the species that exploit the corresponding habitat type.
Fig. 3 in Ecomorphological patterns of the fish assemblage in a tropical floodplain: effects of trophic, spatial and phylogenetic structures
Fig. 3. Distribution of scores centroids of the 35 species on the first two axes of the Principal Components Analysis (PC 1 and PC 2), applied to the correlation matrix (Pearson) formed by 22 ecomorphological indices.
Fig. 2 in Ecomorphological patterns of the fish assemblage in a tropical floodplain: effects of trophic, spatial and phylogenetic structures
Fig. 2. Schematic representation of the linear morphometric measurements and the calculated areas: standard length (SL), maximum body height (MBH), body midline height (BMH), maximum body width (MBW), caudal peduncle length (CPdL), caudal peduncle height (CPdH), caudal peduncle width (CPdW), head length (HdL), head height (HdH), head width (HdW), length of snout with the mouth closed (LSC), length of snout with the mouth open (LSO), eye height (EH), mouth height (MH), mouth width (MW), dorsal fin length (DL), dorsal fin height (DH), caudal fin length (CL), caudal fin height (CH), anal fin length (AL), anal fin height (AH), pectoral fin length (PtL), pectoral fin height (PtH), pelvic fin length (PvL), pelvic fin height (PvH), eye area (EA), dorsal fin area (DA), caudal fin area (CA), anal fin area (AA), pectoral fin area (PtA), and pelvic fin area (PvA).
Fig. 1 in Ecomorphological patterns of the fish assemblage in a tropical floodplain: effects of trophic, spatial and phylogenetic structures
Fig. 1. Study area with sampling stations in the upper Paraná River floodplain: rivers: Paraná (1), Baía (2) and Ivinheima (3); channels: Cortado (4), Curutuba (5) and Ipoitã (6); connected lagoons: Garças (7), Guaraná (8) and Finado Raimundo (9); disconnected lagoons: Fechada (10), Ventura (11) and Zé do Paco (12).
Fig. 1 in Stability and spatio-temporal structure in fish assemblages of two floodplain lagoons of the lower Orinoco River
Fig. 1. Locations of the two studied lagoons in the right bank of the lower Orinoco river, between the cities of Puerto Ordaz and Ciudad Bolívar, Bolívar State, Venezuela. The arrows in black indicate the lagoons.
Fig. 3 in Stability and spatio-temporal structure in fish assemblages of two floodplain lagoons of the lower Orinoco River
Fig. 3. Percentage abundance of total species (S) and number of species for orders in each habitats of the lagoons. The abbreviations of the habitats are explained in the Fig. 2.
Fig. 4 in Stability and spatio-temporal structure in fish assemblages of two floodplain lagoons of the lower Orinoco River
Fig. 4. Mean values (+ confidence interval) of abundance, biomass and richness by habitats and hydrological phases between lagoons. The abbreviations of the hydrological phases and habitats are explained in the Fig. 2.
Fig. 6. nMDS analysis during high waters and low waters. a and b in Stability and spatio-temporal structure in fish assemblages of two floodplain lagoons of the lower Orinoco River
Fig. 6. nMDS analysis during high waters and low waters. a and b = gill nets sampling; c and d = seine net sampling. Each symbol represents one sample, filled symbols belongs to Las Arhuacas (arh) and those of open symbols to Los Cardonales (car). The dissimilarity between the sampling is approximately proportional to the distance, that is to say to greater distance greater dissimilarity. The abbreviations of the habitats are explained in the Fig. 2.
Fig. 2 in Stability and spatio-temporal structure in fish assemblages of two floodplain lagoons of the lower Orinoco River
Fig. 2. Percentage distribution abundance and biomass of fish by habitats in each hydrological phase in both lagoons. DW = Descent water, LW = Low water, RW = Raise water and HW = High water. RO = Rocky outcrops, FGF = Flooded grass fields, FF = Floodplain forests, B = Beach, AV = Aquatic vegetation, LZFT = Littoral zone with fallen trunks and LZOW = Littoral zone and open waters.
Fig. 2 in Fish larvae assemblages in two floodplain lakes with different degrees of connection to the Paraná River, Brazil
Fig. 2. Larvae abundances for the different species in Xambrê Lake (a) and Saraiva Lake (b) in Ilha Grande National Park, upper Paraná River, during the three studied spawning seasons.
Fig. 5 in Fish larvae assemblages in two floodplain lakes with different degrees of connection to the Paraná River, Brazil
Fig. 5. Sample scores of retained axes (Axes 1, 2, and 3) from the non-metric multidimensional scaling (NMS) controlling for sites (S1 - Saraiva channel, S2 - Saraiva middle, X1 - Xambrê stream and X2 - Xambrê middle) (a; b) and spawning seasons (I, II and III) (c; d). Variation of mean scores axis for sites (e) and spawning seasons (f) in Ilha Grande National Park, upper Paraná River (s.d. = standard deviation).
Fig. 4 in Fish larvae assemblages in two floodplain lakes with different degrees of connection to the Paraná River, Brazil
Fig. 4. Variations in mean species richness (number of species) (a), evenness (E) (b) and Shannon Diversity Index (H') (c) of fish larvae per sampling for Xambrê Lake and Saraiva Lake sites (S1 - Saraiva channel, S2 - Saraiva middle, X1 - Xambrê stream and X2 - Xambrê middle) in Ilha Grande National Park, upper Paraná River, during the three studied spawning seasons (s.d. = standard deviation).
Fig. 3 in Relationships between water transparency and abundance of Cynodontidae species in the Bananal floodplain, Mato Grosso, Brazil
Fig. 3. Cluster dendrogram based on relative abundance in biomass of Cynodontidae species and water transparency from 15 sampling sites in the Bananal floodplain, Mato Grosso, Brazil (UPGMA algorithm, Euclidian distance). See Table 1 for site codes.
Fig. 1 in Relationships between water transparency and abundance of Cynodontidae species in the Bananal floodplain, Mato Grosso, Brazil
Fig. 1. Partial map of South America showing the location of the study area in the Bananal floodplain. The detailed map depicts the sampling sites (circles) in the rios Araguaia and Mortes basins. See Table 1 for site codes.
Fig. 2 in Relationships between water transparency and abundance of Cynodontidae species in the Bananal floodplain, Mato Grosso, Brazil
Fig. 2. Linear regression between relative abundance in biomass (a) and number of individuals (b) of Cynodontidae species and water transparency from 15 sampling sites in the Bananal floodplain, Mato Grosso, Brazil.
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.