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290 results for “sea turtles”
FIGURE 5 in Hexapleomera urashima sp. nov. (Crustacea: Tanaidacea), a tanaidid epibiotic on loggerhead sea turtles at Yakushima Island, Japan
FIGURE 5. Hexapleomera urashima sp. nov., male. A–D, allotype; E, paratype (ICHUM-5393). A, body, dorsal; B, antennule (three of five aesthetascs not illustrated); C, antenna; D, E, cheliped, outer view. Scale bars: A, 1 mm; B–E, 0.1 mm.
FIGURE 3 in Hexapleomera urashima sp. nov. (Crustacea: Tanaidacea), a tanaidid epibiotic on loggerhead sea turtles at Yakushima Island, Japan
FIGURE 3. Hexapleomera urashima sp. nov., female. A–E, H, I, K, L, holotype; F, G, paratype (ICHUM-5383); J, paratype (ICHUM-5386). A, body, dorsal view; A1, pleonites 3–5 and pleotelson, dorsal view, setae on pleonites and uropods omitted; B, body, lateral view; C, antennule (one of four aesthetascs not illustrated); C1, antennule, articles 3 and 4; D, antenna; E, labrum; F, G, left and right mandibles; H, labium; I, maxillule; J, maxilla; K, maxillipeds, dorsal view, most setae on left palp and setal ornamentation omitted; K1, distal portion of maxillipedal endites, dorsal view; L, epignath; M, cheliped, outer view; M1, chelipedal fixed finger, outer view, most setae omitted. Scale bars: A, B, 1 mm; others, 0.1 mm.
FIGURE 6 in Hexapleomera urashima sp. nov. (Crustacea: Tanaidacea), a tanaidid epibiotic on loggerhead sea turtles at Yakushima Island, Japan
FIGURE 6. Hexapleomera urashima sp. nov., male. A, D, E, G–Q, allotype; B, C, paratype (ICHUM-5391); F, paratype (ICHUM-5390). A, labrum; B, C, left and right mandibles; D, labium; E, right maxillule; F, left maxilliped, setal ornamentation omitted; G, epignath; H–M, right pereopods 1–6; M1, distal portion of right pereopod 6; N–P, right pleopods 1– 3, most setal ornamentations omitted; N1, O1, P1, same, endopod, most setal ornamentation omitted; Q, right uropod. Scale bars: 0.1 mm.
Fig. 1 in Predaceous fire ants (Hymenoptera: Formicidae) at sea turtle (Testudines: Cheloniidae) nesting beaches and hatcheries in El Salvador
Fig. 1. Locations of study sites in El Salvador. Two sea turtle nesting beaches (diamonds) and 14 hatcheries (dots) were monitored along the coast of El Salvador in 2012. A = Bola de Monte; B = Barra de Santiago; C = Los Cobanos; D = San Diego; E = Toluca; F = Las Bocanitas; G = Zunganera; H = Costa del Sol 1; I = Costa del Sol 2; J = Isla Tasajera; K = San Juan del Gozo; L = Punta San Juan; M: La Pirraya; N = Las Isletas; O = El Espino; P = El Maculis; Q = El Tamarindo.
Highly feminised sex-ratio estimations for the world's third-largest nesting aggregation of loggerhead sea turtles
<p>All data uploaded is in a CSV format.</p> <p>TempVariation contains the daily average temperatures for each island (pooling data between years and beaches).</p> <p>LumTempYear contains the comparison between temperature and luminosity for each beach for all 3 years of data collection.</p> <p>LumTemp contains pools the data from LumTempYear so that there is one average temperature reading per beach. The weightings column states the percentage nesting occurring on that beach.</p> <p>BeachHist builds upon LumTemp including the estimated proportion of nests experiencing critically high temperatures, based on the daily temperatures received from the TempVariation.</p> <p> </p>
Figure 3 in Spatial and temporal nesting pattern of Sea Turtles in Alas Purwo National Park, and its implications for conservation management practices
Figure 3. Number of four sea turtles nesting in each hypothetical station during survey period: (A) L.olivacea, (B) C. mydas, (C) E. imbricata, and (D) D. coriacea.
Figure 2 in The Black Sea-Eastern Mediterranean flyway of the globally threatened European turtle dove (Streptopelia turtur)
Figure 2. Turtle dove sightings (1900–2020) during wintering periods (black square) and postbreeding migration periods (gray circle), as recorded with citizen science. The scale of grays: density of recovery lines for the Eastern flyway (left) and the Black SeaEastern Mediterranean flyway (right). Black lines: direction of recovery lines for ringed birds from the Eastern and Black Sea-Eastern Mediterranean flyways.
Fig. 1 in First multicenter coprological survey on helminth parasite communities of free-living loggerhead sea turtles Caretta caretta (Linnaeus, 1758) from the Adriatic Sea and Northern Ionian Sea
Fig. 1. Map of the four turtle rescue centres located along the medium low Adriatic Sea and Northern Ionian Sea of the Italian Mediterranean coast.
Figure 2 in Human induced trauma and directed take inhibits sea turtle recovery in the Commonwealth of the Northern Mariana Islands
Figure 2. Total number of green (Chelonia mydas), hawksbill (Eretmochelys imbricata), and olive ridley (Lepidochelys olivacea) and unknown sea turtle recoveries per year represented in the CNMI stranding database 2005 to 2016 (n = 89).
Fig. 22 in The Ecology And Migrations Of Sea Turtles 8. Tests Of The Developmental Habitat Hypothesis
Fig. 22. Mean, range, and one standard deviation for Chelonia mydas at three maturity stages (see Methods) at three study sites in Bermuda and Panama and at Tortuguero, Costa Rica. Sample size is shown below each bar. Maturity status is based on laparoscopy except for nesting females from Tortuguero. Statistics for stage 1 individuals in Panama are affected by the absence of small immatures at this site (see Results – C. mydas, Panama). Statistics for stage 2 individuals from Bermuda are affected by departure of stage 2 animals from Bermuda waters (see Departure – C. mydas, Bermuda). Data for nesting females were provided by Sebastian Troëng and the Sea Turtle Conservancy.
Extreme rainfall events and cooling of sea turtle clutches: implications in the face of climate warming
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Data from: The geomagnetic environment in which sea turtle eggs incubate affects subsequent magnetic navigation behavior of hatchlings
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Data from: Synchronised nesting aggregations are associated with enhanced capacity for extended embryonic arrest in olive ridley sea turtles
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Transcriptomic analysis of pre-ovipositional embryonic arrest in the green sea turtle (Chelonia mydas)
GEO Series GSE197628. Chelonia mydas. 15 samples. Type: Expression profiling by high throughput sequencing.
Impact of gas emboli and hyperbaric treatment on respiratory function of loggerhead sea turtles (Caretta caretta)
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Accelerometer, gyroscope and pressure data associated with behaviors of free-ranging hawksbill sea turtles (Chelonia mydas)
<p> </p> <p>Data accompanying the paper: Jeantet, L., Vigon, V., Geiger, S., & Chevallier, D. (2021). Fully convolutional neural network: A solution to infer animal behaviours from multi-sensor data. <em>Ecological Modelling</em>, <em>450</em>, 109555.. doi : <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.ecolmodel.2021.109555" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ecolmodel.2021.109555</a></p> <p> </p> <p>In this paper we developped a fully convolutional network, the V-Net, to automatically identify the behaviors of green turtle from acceleration, gyroscope, depth sensor data. With minimal preprocessing, we obtained a F1-score of 81.1% and a Global accuracy of 97.2%. </p> <p> </p> <p><strong>Associated Github with the V-Net script : </strong><a href="https://github.com/jeantetlorene/Vnet_seaturtle_behavior">https://github.com/jeantetlorene/Vnet_seaturtle_behavior</a></p> <p> </p> <p>The dataset comprised the raw acceleration, gyroscope and depth sequence of 13 free-ranging green turtles associated with the behaviors. The indiviuals were equipped with a on-board video recorder combined with an accelerometer, gyroscope, magnetometer and luminosity, temperature and depth sensors using four suction cups and an automatic release system over a two-day periods (see Jeantet et al. 2020 for details and the associated article). The accelerometer, gyroscope, magnetometer recorded at 20 Hz and the pressure, temperature and luminosity sensors at 1 Hz. The cameras were programmed to record until nightfall (6 pm) and resume at daybreak (6 am). The magnetometer, luminosity and temperature data are not provided in this dataset. </p> <p>For each individual, the data collected by the devices was correlated with observed behaviors from video recordings. Unlabeled sequences, primarily night recordings, were excluded, resulting in the creation of one file per day of deployment for each individual. A total of 46 behaviors were observed and are described in detail in Jeantet et al. (2020). The labels for these behaviors are found in the column "beh." The behaviors were grouped into six main categories: Breathing, Feeding, Gliding, Resting, Scratching, and Swimming. Any other observed behavior was categorized as Other. The associated labels for the categories can be found in the column "beh_merge."</p> <p>To process the depth data and increase the sampling rate to 20 Hz, we used a linear interpolation technique. We called this new variable "Pressure_corr". Additionally, we calculated the pressure difference ("Pressure_diff") between each measuring point (originally at 1 Hz).</p> <p>"In total, the green turtle dataset contained 68.6 hours of labelled sequences from 13 individuals (approximately 5.29 hours per individual, max = 14.67 hours, min = 0.96 hours, standard deviation = 3.39 hours). The predominant behavior observed in the videos was Resting, totaling over 34.3 hours, followed by Swimming and Breathing, with 22.3 hours and 5.7 hours, respectively. The other behaviors were expressed in minority (Gliding: 2.3 hours, Feeding: 1.8 hours, Scratching: 1.2 hours and Other: 1 hour). "</p> <p> </p> <p>The folder contains 16 Python matrices, each with 11 columns (AccX, AccY, AccZ, GyrX, GyrY, GyrZ, Depth, beh, beh_merge, Pressure_corr, Pressur_diff) and a number of rows corresponding to the deployment duration. The title of each file indicates the camera number used (CC-07-XX) and the deployment day (DD-MM-YYYY), with an additional number if the file was split due to unlabeled sequences.</p> <p> </p> <p>The folder also contains two dictionaries (behInd_to_behName, behName_to_behInd) that specify the behaviors associated with each number used as a label in the "beh" column. Two dictionaries (behInd_to_behName_cat, behName_to_behInd_cat) that specify the behavioral categories associated with each number used as a label in the "beh_merge" column. Additionally, there is a dictionary (dico_info) that provides the names of the matrix columns and the frequence of recording.</p> <p> </p> <p><strong>Please cite this dataset as :</strong> </p> <p>Jeantet, L., Planas-Bielsa, V., Benhamou, S., Geiger, S., Martin, J., Siegwalt, F., Lelong, P., Gresser, J., Etienne, D., Hielard, G., Arque, A., Regis, S., Lecerf, N., Frouin, C., Benhalilou, A., Murgale, C., Maillet, T., Andreani, L., Campistron, G., … Chevallier, D. (2024). Accelerometer, gyroscope and pressure data associated with behaviors of free-ranging hawksbill sea turtles (Chelonia mydas) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11643602</p> <p> </p>
FIGURE 6 in A new species of turtle-headed sea Snake (Emydocephalus: Elapidae) endemic to Western Australia
FIGURE 6. Typical cephalic scalation in Emydocephalus annulatus (upper) and Emydocephalus orarius sp. nov. (lower)
FIGURE 4 in A new species of turtle-headed sea Snake (Emydocephalus: Elapidae) endemic to Western Australia
FIGURE 4. Maximum likelihood tree of Emydocephalus species using dataset. Scale bar represents nucleotide substitutions per base pair.
FIGURE 3 in A new species of turtle-headed sea Snake (Emydocephalus: Elapidae) endemic to Western Australia
FIGURE 3. ND4 maximum clade credibility species. Scale bar represents nucleotide substitutions per base pair.
FIGURE 1 in A new species of turtle-headed sea Snake (Emydocephalus: Elapidae) endemic to Western Australia
FIGURE 1. Distribution of Emydocephalus species. Compiled from tissue samples, museum records and literature (Alcala 2000; Dotsenko 2010; Rasmussen and Ineich, 2010). Green=E. orarius sp. nov.; yellow=E. ijimae; turquoise=E. annulatus (Timor Sea); blue=E. annulatus (Coral Sea); red=E. cf. annulatus (specific identity currently unclear).
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.