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211 results for “tropical fishes”
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. 2 in Fish assemblage in a dammed tropical river: an analysis along the longitudinal and temporal gradients from river to reservoir
Fig. 2. Individual-based rarefaction curves by zone (1, 2, 3, 4) for species richness in the Paraíba do Sul River and Funil Reservoir.
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. 3 in Spatial pattern of a fish assemblage in a seasonal tropical wetland: effects of habitat, herbaceous plant biomass, water depth, and distance from species sources
Fig. 3. Partial regressions testing the effects of water depth (left) and distance from colonizing source (right) on fish species richness collected in 22 plots in Site of Long-Term Sampling (SLTS). Only statistically significant relationships are shown.
Fig. 1 in Spatial pattern of a fish assemblage in a seasonal tropical wetland: effects of habitat, herbaceous plant biomass, water depth, and distance from species sources
Fig. 1. Geographical location of the study area and the Site of Long-Term Sampling (in the area). The system is installed in the Pantanal, Brazil.
Fig. 1 in Turtle cleaners: reef fishes foraging on epibionts of sea turtles in the tropical Southwestern Atlantic, with a summary of this association type
Fig. 1. Reef fishes cleaning sea turtles' hard and soft parts in the Southwestern Atlantic. A porkfish (Anisotremus virginicus) and a group of blue tangs (Acanthurus coeruleus) feed on epibionts on the shell of a moving hawksbill turtle (Eretmochelys imbricata); a barely visible doctorfish (Acanthurus chirurgus) nibbles at the posterior portion of the turtle's shell, and two blue tangs nibble at the left hind limb (a). Photo by M. Granville. One Zelinda's parrotfish (Scarus zelindae) and three blue tangs feed on algae growth on the shell of a male loggerhead turtle (Caretta caretta) near a shipwreck; two Spanish hogfishes (Bodianus rufus) also inspect the turtle (b). Photo by Z. Matheus. Four Spanish hogfish inspect and forage on epibionts on the shell of the same loggerhead turtle; one blue tang and one Zelinda's parrotfish also "escort" the slowly moving turtle (c). Photo by Z. Matheus. A green turtle (Chelonia mydas) remain motionless on the bottom, while a Brazilian blenny (Ophioblennius trinitatis) forages on algae growth on the left lateral portion of the shell; a few smallmouth grunts (Haemulon chrysargyreum) also capitalize upon this situation, and nibble at the turtle's shell (d). Photo by C. Sazima. A sergeant major (Abudefduf saxatilis) nibbles at an algae patch on the anterior part of the shell of a posing and hovering green turtle (e). Photo by Z. Matheus. The herbivorous Rocas damselfish (Stegastes rocasensis) nibbles at the right hind limb of a green turtle posing near algae turfs tended by this damselfish (f). Photo by Z. Matheus.
Fig. 4. Fish assemblage ordination resulting from a in Flow seasonality and fish assemblage in a tropical river, French Guiana, South America
Fig. 4. Fish assemblage ordination resulting from a CA analysis using species (a), family (b), trophic guild (c), and MOS (d) descriptors in the downstream site, Comté River. Bold text indicates the species, family, trophic guild or MOS which contributes most to axes. Dots = samples taken during high waters; triangles = samples takes during low waters. Numbers correspond to fish species in Table 1. Axis scales are indicated in the small box.
Fig. 2. Water level oscillation measured between August 1998 and July 2000 in Flow seasonality and fish assemblage in a tropical river, French Guiana, South America
Fig. 2. Water level oscillation measured between August 1998 and July 2000 at the Hydrological station on the Comté River. The numbers indicate the mean water level during the month of sampling.
Fig. 1 in Flow seasonality and fish assemblage in a tropical river, French Guiana, South America
Fig. 1. Localization of the sampling sites on the Comté River, French Guiana. A = upstream site; B = downstream site; HS = Hydrological station.
Fig. 3 in Mercury distribution in different tissues and trophic levels of fish from a tropical reservoir, Brazil
Fig. 3. Mean concentrations and ratios of mercury in different tissues of omnivorous (a), carnivorous (b), and detritivorous fishes (c) collected from Vigário Reservoir. Error bars represent one standard deviation of the mean.
Fig. 1 in Mercury distribution in different tissues and trophic levels of fish from a tropical reservoir, Brazil
Fig. 1. Map of Vigário reservoir, showing its drainage basin (Piraí river, Paraíba do Sul river and Santana reservoir). Black arrows indicate the water flow. (Source: Gomes et al., 2008).
Fig. 2 in Mercury distribution in different tissues and trophic levels of fish from a tropical reservoir, Brazil
Fig. 2. Mean concentrations and ratios of mercury in muscle of fish collected from Vigário reservoir. Different letters indicate significant difference between groups: inorganic (ab) and organic mercury concentrations (xyz), and ratios of organic mercury (αβγ). Error bars represent the standard deviation of the mean.
Fig. 1 in Effects of tourist visitation and supplementary feeding on fish assemblage composition on a tropical reef in the Southwestern Atlantic
Fig. 1. Non-Metric Multi-Dimensional Scaling (MDS) plot of fish assemblages samples of the Picãozinho reef in each of the two studied situations. Dark triangles = PT (presence of tourists) and light triangles = AT (absence of tourists).
Fig. 1 in Fishes associated with spinner dolphins at Fernando de Noronha Archipelago, tropical Western Atlantic: an update and overview
Fig. 1. Six selected fish species recorded in association with spinner dolphins (Stenella longirostris) at Fernando de Noronha Archipelago. Black durgon (Melichthys niger), a particle-forager and browser that feeds on dolphin wastes habitually in the Dolphins' Bay (a). Photo by I. Sazima. Scaled sardine (Harengula jaguana), a particle-forager that feeds on dolphin wastes occasionally while the dolphins cruise close to sandy beaches (b). Photo by C. Sazima. Bermuda chub (Kyphosus sectatrix), a browser and particle-forager that feeds on dolphin wastes occasionally in the Dolphins' Bay (c). Photo by C. Sazima. Black jack (Caranx lugubris), a roving carnivore that feeds on dolphin wastes occasionally in the Dolphins' Bay (d). Photo by J. P. Krajewski. Whalesucker (Remora australis), a hitch-hiker on cetaceans that forages on spinner dolphin wastes and cleans them of parasites and dead tissue (e). Photo by J. M. Silva Jr. Yellowfin tuna (Thunnus albacares), a roving carnivore that joins spinner dolphins while the latter forage for schooling fish and squids in their hunting grounds around the archipelago (f). Photo by G. Marcovaldi (Banco de Imagens Projeto TAMAR-IBAMA).
Fig. 5. Correlation between PCA axis 1 in Fish assemblages of tropical floodplain lagoons: exploring the role of connectivity in a dry year
Fig. 5. Correlation between PCA axis 1 and species richness (a), density (b), and biomass (c) in connected [February (), May (), November ()] and disconnected lagoons, May (), August (), November ()]. Arrows indicate the direction of the limnological variables influence.
Fig. 4 in Fish assemblages of tropical floodplain lagoons: exploring the role of connectivity in a dry year
Fig. 4. DCA ordination of sample sites by month in connected [February (), May (), November ()] and disconnected lagoons [, May (), August (), November ()]. Arrows indicate the direction of influence of species in the ordination.
Fig. 2 in Fish assemblages of tropical floodplain lagoons: exploring the role of connectivity in a dry year
Fig. 2. Daily variation of pluviometric (a) and hydrometric levels (c) of the Paraná River in 2000, measured at Porto São José municipality, and difference between mean monthly pluviometric (b) and hydrometric levels (d) in 2000 (x) and the last 10 1 years (x). Data supplied by DNAEE (Departamento Nacional de Águas e Energia Elétrica). Dashed line indicates water level 2 required for initial inundation of the floodplain (Veríssimo, 1994).
Fig. 1 in Fish assemblages of tropical floodplain lagoons: exploring the role of connectivity in a dry year
Fig. 1. Study area with location of sampling sites in connected (1-6) and disconnected lagoons (7-15): 1 (Leopoldo),
Species ecology explains the various spatial components of genetic diversity in tropical reef fishes
<p>Generating genomic data for 19 tropical reef fish species of the Western Indian Ocean, we investigate how species ecology influences genetic diver- sity patterns from local to regional scales. We distinguish between the α, β and γ components of genetic diversity, which we subsequently link to six ecological traits. We find that the α and γ components of genetic diversity are strongly correlated so that species with a high total regional genetic diversity display systematically high local diversity. The α and γ diversity components are negatively associated with species abundance recorded using underwater visual surveys and positively with body size. Pelagic larval duration is found to be negatively related to genetic β diversity supporting its role as a dispersal trait in marine fishes. Deviation from the neutral theory of molecular evolution motivates further effort to understand the processes shaping genetic diversity and ultimately the diversification of the exceptional diversity of tropical reef fishes.</p>
A deep learning dataset for underwater object detection of tropical freshwater fish species in northern Australia
<p>This dataset includes 44,112 images with 82,904 bounding box annotations for 23 tropical freshwater fish taxa from northern Australia. </p> <p>Images were derived from Remote Underwater Video (RUV) deployments in deep channel and shallow lowland billabongs, Kakadu National Park, Northern Territory Australia. RUV deployments were conducted during the <a href="https://www.dcceew.gov.au/science-research/supervising-scientist">Supervising Scientists</a> annual fish monitoring program in the 2016, 2017 and 2018 recessional flow period (dry season). More information can be found <a href="https://www.dcceew.gov.au/sites/default/files/documents/ss-atr-2020-21.pdf">here</a>.</p> <ul> <li>All images are in .jpg format and are 1920x1080 in dimension.</li> <li>Bounding box annotations are in COCO format. </li> </ul> <p>Two .zip files are included:</p> <ul> <li><a href="https://zenodo.org/api/files/990412db-e633-4f82-9b32-6990ef439ccd/202210-KakaduFishAI-CompactModel.zip">202210-KakaduFishAI-CompactModel.zip</a>: includes compact model weights in tensorflow format (.pb) trained using Azure's Custom Vision platform. This model is suitable for edge devices due to its reduced size. Code is provided to use the compact model for inferencing. </li> <li> <a href="https://zenodo.org/api/files/990412db-e633-4f82-9b32-6990ef439ccd/202210-KakaduFishAI-TrainingData.zip">202210-KakaduFishAI-TrainingData.zip</a>: includes all images and one COCO (.json) file with annotations. </li> </ul> <p>Fish taxa include: </p> <ol> <li><em>Ambassis agrammus</em></li> <li><em>Ambassis macleayi</em></li> <li><em>Amniataba percoides</em></li> <li><em>Craterocephalus stercusmuscarum</em></li> <li><em>Denariusa bandata</em></li> <li><em>Glossamia aprion</em></li> <li><em>Glossogobius</em> spp.</li> <li><em>Hephaestus fuliginosus</em></li> <li><em>Lates calcarifer</em></li> <li><em>Leiopotherapon unicolor</em></li> <li><em>Liza ordensis</em></li> <li><em>Megalops cyprinoides</em></li> <li><em>Melanotaenia nigrans</em></li> <li><em>Melanotaenia splendida inornata</em></li> <li><em>Mogurnda mogurnda</em></li> <li><em>Nemetalosa erebi</em></li> <li><em>Neoarius</em> spp.</li> <li><em>Neosilurus</em> spp.</li> <li><em>Oxyeleotris</em> spp.</li> <li><em>Scleropages jardinii</em></li> <li><em>Strongylura kreffti</em></li> <li><em>Syncomistes butleri</em></li> <li><em>Toxotes chatareus</em></li> </ol> <p>If you use this data for your own deep learning project we'd love to hear about how you used this dataset: andrew.jansen@environment.gov.au.</p>
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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.