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Figure 2 in The benthic and pelagic phases of Muraenolepis marmorata (Muraenolepididae) off the Kerguelen Plateau (Indian sector of the Southern Ocean)
Figure 2. – Geographical pelagic survey coverage off the Kerguelen Islands during the "IPEKER" (1995), "ICHTYOKER 1, 2 & 3" (1998-2000) and "MYCTO 3 D" (2014) cruises. Each station includes four depths hauls (subsurface, 50, 150, 300 m). Yellow circles are day stations, deep blue diamond- shaped are night stations.
Figure 4 in The benthic and pelagic phases of Muraenolepis marmorata (Muraenolepididae) off the Kerguelen Plateau (Indian sector of the Southern Ocean)
Figure 4. – Length Frequency Distributions (LFD) of Muraenolepis marmorata from POKER 1 (2006), POKER 2 (2010) Kerguelen Islands fish bottom biomass surveys and by-catch in the bottom longline fishery (2006-2016) off the Kerguelen Islands. Photo: Muraenolepis marmorata (photo ©POKER 2).
Figure 2 in Growth of the oblique-banded grouper (Epinephelus radiatus) on the coasts of Reunion Island (SW Indian Ocean)
Figure 2. - Von Bertalanffy growth curves of Epinephelus radiatus from Reunion Island fitted to all data (n = 57).
Depth variation in benthic community response to repeated marine heatwaves on remote Central Indian Ocean reefs
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Western Indian Ocean blue whale dataset
<p>The analysis of the large volumes of data resulting from continuous and long-term monitoring of blue whales unmistakably benefits from the automated detection of target signals. Automatic detection methods must be reliable and robust to gather statistically relevant elements and contribute to answering blue whale ecological unknowns. Therefore, systematic performance analysis of detection and classification methods developed for the passive context is crucial.</p> <p>These datasets were annotated to support my Ph.D work <em>Detection and classification in passive acoustic contexts: Application to blue whale low-frequency signals</em>. They are based on recordings from Ocean Bottom Seismometers (RR41 and RR48) deployed during the <a href="http://www.rhum-rum.net/en/">RHUM-RUM</a> experiment, in the western Indian Ocean. All RHUM-RUM recordings are freely available from the <a href="http://seismology.resif.fr/">RESIF</a> data center, under the code name YV (<a href="https://doi.org/10.15778/RESIF.YV2011">https://doi.org/10.15778/RESIF.YV2011</a>). Find more information on RHUM-RUM on <a href="https://www.researchgate.net/project/RHUM-RUM">Researchgate</a>.</p> <p>All blue whales calls within the provided acoustic recordings were manually annotated using the software <a href="http://ravensoundsoftware.com">Raven Pro 1.5</a>. The analyst selected boxes describing the begin and end times and, minimum and maximum frequencies of each call (Dataset 1) or each unit (Dataset 2).</p> <p><br> <strong>Dataset 1 - Antarctic blue whale calls</strong><br> Contains:</p> <ul> <li>Sound file <em>RR48_2013_D151.wav</em> where Antarctic blue whale calls are recorded continuously for more than 21 hours (from 01:20 to 22:40); </li> <li>Annotation file <em>Annotation_RR48_2013_D151.txt</em> with the box information of 845 Antarctic blue whale calls (+ some other interfering events); and,</li> <li>Call time of arrivals estimated from events detected by the stochastic matched filter and corresponding whale location in the file <em>Localisation_RR48_2013_D151.txt</em>.</li> </ul> <p>This dataset supports research presented in:<br> L. Bouffaut, R. Dréo, V. Labat, A. Boudraa and G. Barruol “Passive stochastic matched filter for antarctic blue whale call detection,” in J. Acoust. Soc. Am, vol. 144, no. 2, pp. 955-965 (2018). DOI: <a href="https://doi.org/10.1121/1.5050520">10.1121/1.5050520</a></p> <p>Additional information:<br> - Detailed information on this dataset on my <a href="https://leabouffaut.home.blog/2020/01/22/antarctic-blue-whale-dataset/">personal website</a> <br> - Stochastic matched filter package on <a href="https://leabouffaut.github.io/SMF_package/ ">Github</a> DOI: <a href="https://doi.org/10.5281/zenodo.3613787">10.5281/zenodo.3613787</a><br> - Localization method research paper on <a href="https://www.researchgate.net/publication/322570729_Antarctic_Blue_Whale_localization_with_Ocean_Bottom_Seismometers_in_Southern_Indian_Ocean">Researchgate</a> | <a href="https://doi.org/10.1016/j.dsr2.2018.04.005">Deep sea research paper</a> </p> <p><strong>Dataset 2 - Blue whale call units</strong><br> Contains:</p> <ul> <li>Sound files <em>RR41_2013_D132.wav</em>, <em>RR41_2013_D135.wav</em>, and <em>RR48_2013_D138.wav</em>,</li> <li>Corresponding annotation file <em>Annotation.txt</em> with box information of various blue whale call units from Antarctic blue whales, Madagascar pygmy blue whales and P-calls (+ some other interfering events).</li> </ul> <p>In total this dataset contains more than 4000 annotated units.</p> <p>This dataset supports research presented in:<br> L. Bouffaut, S.Madhusudhana, V. Labat, A. Boudraa and H. Klinck, “Automated blue whale song transcription across variable acoustic contexts,” in IEEE OCEANS’19 Marseille, student poster competition, France, pp. 2-7 (2019) DOI: <a href="https://doi.org/10.1109/OCEANSE.2019.8867471">10.1109/OCEANSE.2019.8867471</a><br> who received the First Prize and Norman Miller Award and was therefore also published in the IEEE OES Beacon Newsletter (September 2019 vol. 8, no. 3, pp. 44-49)</p> <p>Detailed information on this dataset on my <a href="https://leabouffaut.home.blog/2020/01/22/blue-whale-call-units-dataset/">personal website</a>.</p>
Sewn boats in the Qatar Museums collection, Doha: baggāras and kettuvallams as records of a Western Indian Ocean technological tradition DATASET
<p>The files in this archive comprise photographs, 3D digital models, naval lines drawings and construction drawings of the sewn boats in the collection of Qatar Museums, surveyed by the authors in April 2019. They relate to the following article:</p> <p>Cooper, J.P., Ghidoni, A., Zazzaro, C., and Ombrato, L., 2020, <em>Sewn boats in the Qatar Museums collection, Doha: baggāras and kettuvallams as records of a Western Indian Ocean technological tradition</em>. doi: 10.1111/1095-9270.12422</p> <p>At the time of data deposition, this was at the page-proofs stage with the <em>International Journal of Nautical Archaeology. </em></p>
Environmental correlates of reptile variation on the Houtman Abrolhos archipelago, eastern Indian Ocean
Aim: To examine the relationships between island environmental attributes, both biotic and abiotic, and three measures of reptilian variation – species assemblage, species richness, and body size distributions. Location: Houtman Abrolhos archipelago, Western Australia. Taxon: Reptiles. Methods: Nineteen islands were sampled from 2002 - 2012 using foraging and trapping. Body size (snout-vent length) was measured on first capture. Island size varied from 0.3 - 587 ha, encompassing the three geomorphic island types, the three bathymetric groups, and a range of other environmental attributes. Results: From about 1500 captures, 24 reptile species were recorded, including three previously undocumented on the archipelago, and 55 records of species not previously recorded on specific islands. Four significantly different reptile assemblage groups were identified. These were highly correlated with geomorphological composition - two groups encompassing the three large aeolianite islands; another the high rock islands and the largest composite island; and a fourth consisting of the remaining composite islands with one very small high rock island. Both assemblage and richness on islands were significantly correlated with island area, geomorphology and native plant species richness. Of the 13 species captured frequently, eleven showed statistically significant inter-island variation in body size, and two exhibited sexual dimorphism. In three species, size was also correlated with environmental attributes, including reptile species richness, native plant richness, geomorphology and island area. Six of the eleven species captured on the two largest islands (both aeolianite) differed in size on these adjacent islands. Main Conclusions: High inter-island variation in body size and assemblage composition suggest strong differential selection since the most recent isolation event at 6,500 bp. Anthropogenic disturbances over the last 150 years have resulted in several island extinctions. Species assemblage and richness are strongly associated with environmental attributes. Inter-island body size variation in three species revealed idiosyncratic responses to environmental pressures. Results provide guidance for effective conservation and management strategies, and evidence for the extinction debts inherent in more recently fragmented mainland habitats.
FIGURE 2. Sinobatis kotlyari n in A new deepwater legskate, Sinobatis kotlyari n. sp. (Rajiformes, Anacanthobatidae) from the southeastern Indian Ocean on Broken Ridge
FIGURE 2. Sinobatis kotlyari n. sp., holotype male 331 mm TL, ZMMU P- 17178, in total dorsal view.
Figure 1. - World map representing all the locations mentioned in the dataset. Areas of particular interest are represented with the same colour (⬤ Madagascar, ⬤ Western Indian Ocean, ⬤ Papuasia, ⬤ New Caledonia, ⬤ South Pacific). Grey spots gather all the other locations.
Figure 1. - World map representing all the locations mentioned in the dataset. Areas of particular interest are represented with the same colour (⬤ Madagascar, ⬤ Western Indian Ocean, ⬤ Papuasia, ⬤ New Caledonia, ⬤ South Pacific). Grey spots gather all the other locations.
Fig. 1 in Rhinobatos sainsburyi n.sp. and Aptychotrema timorensis n.sp. -Two New Shovelnose Rays (Batoidea: Rhinobatidae) from the Eastern Indian Ocean
Fig. 1. Ventral view of the snout of the holotype of Aptychotrema timorensis n.sp. (CSIRO CA1258).
FIG. 70 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 70. — Distribution map of Acalypha urophylla Boivin ex Baill. in Madagascar.
FIG. 68 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 68. — Distribution map of Acalypha tremula I.Montero & Cardiel in Madagascar.
FIG. 67 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 67. — Distribution map of Acalypha spachiana Baill. in Madagascar.
FIG. 64 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 64. — Distribution map of Acalypha richardiana Baill. in Comoros Archipelago.
FIG. 63 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 63. — Distribution map of Acalypha radula Baker in Madagascar.
FIG. 62 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 62. — Distribution map of Acalypha rabesahalana I.Montero & Cardiel in Madagascar.
FIG. 56 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 56. — Distribution map of Acalypha menavody (Leandri) I.Montero & Cardiel in Madagascar.
FIG. 59 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 59. — Distribution map of Acalypha perrieri Leandri in Madagascar.
FIG. 55 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 55. — Distribution map of Acalypha medibracteata Radcl.-Sm. & Govaerts in Madagascar.
FIG. 61 in Monograph of Acalypha L. (Euphorbiaceae) of the Western Indian Ocean Region, with the description of a new species from Mayotte
FIG. 61. — Distribution map of Acalypha poiretii Spreng. in Mascarene Islands.
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.