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622 results for “Underwater”
Supplementary material 1 from: Fernandez-Triana J, Kamino T, Maeto K, Yoshiyasu Y, Hirai N (2020) Microgaster godzilla (Hymenoptera, Braconidae, Microgastrinae), an unusual new species from Japan which dives underwater to parasitize its caterpillar host (Lepidoptera, Crambidae, Acentropinae). Journal of Hymenoptera Research 79: 15-26. https://doi.org/10.3897/jhr.79.56162
Wasp parasitization behaviour including diving underwater
Figure 2 from: Fernandez-Triana J, Kamino T, Maeto K, Yoshiyasu Y, Hirai N (2020) Microgaster godzilla (Hymenoptera, Braconidae, Microgastrinae), an unusual new species from Japan which dives underwater to parasitize its caterpillar host (Lepidoptera, Crambidae, Acentropinae). Journal of Hymenoptera Research 79: 15-26. https://doi.org/10.3897/jhr.79.56162
Figure 2 Microgaster godzilla, female holotype. A details of scutellar complex and propodeum B metasoma, dorsal C metapleuron and metasoma, lateral D details of ocelli dorsal E tarsal claw F hypopygium and ovipositor.
Data from: The noise egg: a cheap and simple device to produce low-frequency underwater noise for laboratory and field experiments
Studying the effect of anthropogenic noise on animal behaviour and physiology is a field of growing scientific and management interest. Anthropogenic noise is internationally seen as major environmental concern, but knowledge of the response of animals to noise and its ecological and evolutionary consequences is disparate. Even though fish and invertebrates form the majority of aquatic taxa, the effects of noise on these taxa are largely understudied. Especially the consequences of noise for short-range communication and behavioural interactions are yet unknown. While experimental studies on this subject are thus greatly needed, the expense of the equipment can be a main factor limiting data generation. Speakers that produce low-frequency sounds under water are currently either too large or too expensive to allow for sufficient replication in many research set-ups. Here, we describe a device that can produce a low-frequency sound, which can be used as an experimental source of noise both in aquaria and in the field. The device is completely self-contained and costs around 10 euros per 'noise egg'. The sound created consists of frequency bands (harmonics), which has the advantage that broadband and pulsed sounds, such as sounds produced by vocal fish, are easily detected in a spectrogram. Because the sound from the egg attenuates quickly, it can be used in aquaria and in the field to target certain study species or individuals without affecting a large part of the surrounding area. We have developed the device to study the effects of noise on communication and behaviour in small aquatic animals; however, it could be used for other purposes, such as testing the propagation of certain frequencies in shallow-water habitats. We hope the described method will facilitate the generation of experimental data on the effect of noise on behaviour and communication in aquatic animals in a wide variety of study systems and study areas.
Data from: Point-Combination Transect (PCT): incorporation of small underwater cameras to study fish communities
1. Available underwater visual census methods such as line transects or point count observations are widely used to obtain community data of underwater species assemblages, despite their known pit-falls. As interest in the community structure of aquatic life is growing, there is need for more standardized and replicable methods for acquiring underwater census data. 2. Here, we propose a novel approach, Point-Combination Transect (PCT), which makes use of automated image recording by small digital cameras to eliminate observer and identification biases associated with available underwater visual census methods. We conducted a pilot study at Lake Tanganyika, demonstrating the applicability of PCT on a taxonomically and phenotypically highly diverse assemblage of fishes, the Tanganyikan cichlid species-flock. 3. We conducted 17 PCTs consisting of five GoPro cameras each and identified 22'867 individual cichlids belonging to 61 species on the recorded images. This data was then used to evaluate our method and to compare it to traditional line transect studies conducted in close proximity to our study site at Lake Tanganyika. 4. We show that the analysis of the second hour of PCT image recordings (equivalent to 360 images per camera) leads to reliable estimates of the benthic cichlid community composition in Lake Tanganyika according to species accumulation curves, while minimizing the effect of disturbance of the fish through SCUBA divers. We further show that PCT is robust against observer biases and outperforms traditional line transect methods.
Fig. 2. Heterelmis comalensis. A in Underwater Pupation by the Comal Springs Riffle Beetle, Heterelmis Comalensis Bosse, Tuff, and Brown, 1988 (Coleoptera: Elmidae), with an Update on Culture Techniques
Fig. 2. Heterelmis comalensis. A) Pupa, B) Adult.
SQUID- Stereo Quantitative Underwater Image Dataset
<p>Underwater Single Image Color Restoration</p> <p>SQUID- Stereo Quantitative Underwater Image Dataset</p> <p><a href="http://www.eng.tau.ac.il/~berman">Dana Berman</a>, Deborah Levy, <a href="http://www.eng.tau.ac.il/~avidan/">Shai Avidan, </a><a href="https://www.viseaon.haifa.ac.il/">Tali Treibitz</a></p> <p> </p> <p>Abstract</p> <p>Underwater images suffer from color distortion and low contrast, because light is attenuated while it propagates through water. Attenuation under water varies with wavelength, unlike terrestrial images where attenuation is assumed to be spectrally uniform. The attenuation depends both on the water body and the 3D structure of the scene, making color restoration difficult. Unlike existing single underwater image enhancement techniques, our method takes into account multiple spectral profiles of different water types. By estimating just two additional global parameters: the attenuation ratios of the blue-red and blue-green color channels, the problem is reduced to single image dehazing, where all color channels have the same attenuation coefficients. Since the water type is unknown, we evaluate different parameters out of an existing library of water types. Each type leads to a different restored image and the best result is automatically chosen based on color distribution. We collected a dataset of images taken in different locations with varying water properties, showing color charts in the scenes. Moreover, to obtain ground truth, the 3D structure of the scene was calculated based on stereo imaging. This dataset enables a quantitative evaluation of restoration algorithms on natural images and shows the advantage of our method.</p> <p> </p> <p>Publication</p> <p>The paper is availbale on <a href="https://arxiv.org/abs/1811.01343">arXiv</a>.</p> <p>If you use this dataset please cite it as SQUID [ref].<br> [Ref] Berman, Dana, Deborah Levy, Shai Avidan, and Tali Treibitz. "Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset." IEEE Transactions on Pattern Analysis and Machine Intelligence (2020).<br> <br> Bibtex entry:<br> @article{berman2020underwater,<br> title={Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset},<br> author={Berman, Dana and Levy, Deborah and Avidan, Shai and Treibitz, Tali},<br> journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},<br> year={2020}<br> }</p> <p>Source Code</p> <p>The code is availbale on GitHub: <a href="https://github.com/danaberman/underwater-hl">https://github.com/danaberman/underwater-hl</a>.</p> <p>Dataset</p> <p>The dataset includes RAW images, TIF files, camera clibration files, and distance maps.<br> The database contains 57 stereo pairs from four different sites in Israel, two in the Red Sea (representing tropical water) and two in the Mediterranean Sea (temperate water). In the Red Sea the sites were a coral reef ('Katzaa') which is 10-15 meters deep (15 pairs) and a shipwreck ('Satil'), 20-30 meters deep (8 pairs). In the Mediterranean Sea both sites were rocky reef environments, separated by 30km, Nachsholim at 3-6 meters depth (13 pairs), and Mikhmoret at 10-12 meters depth (21 pairs).<br> <br> For convenience it is divided to the 4 dive sites.<br> <br> <a href="http://csms.haifa.ac.il/profiles/tTreibitz/datasets/ambient_forwardlooking/files/README.md">README file</a>.<br> If you use this data, please <a href="http://csms.haifa.ac.il/profiles/tTreibitz/datasets/ambient_forwardlooking/underwater_haze_lines_and_dataset.bib">cite the paper</a>.<br> To evaluate your own results, please use this <a href="http://csms.haifa.ac.il/profiles/tTreibitz/datasets/ambient_forwardlooking/files/underwater-dataset-evaluation-undisorted-params.zip">evaluation code</a>.</p> <p><br> </p> <p>References</p> <p><strong>[Drews et al. 2013]</strong> P. Drews, E. Nascimento, F. Moraes, S. Botelho, and M. Campos. Transmission estimation in underwater single images. In <em>Proc. IEEE ICCV Underwater Vision Workshop, pages 825–830,</em> 2013.<br> <strong>[Peng et al. 2015]</strong> Y.-T. Peng, X. Zhao, and P. C. Cosman. Single underwater image enhancement using depth estimation based on blurriness. In <em>Proc. IEEE ICIP</em>, 2015.<br> <strong>[Ancuti et al. 2016]</strong> C. Ancuti, C. O. Ancuti, C. De Vleeschouwer, R. Garcia, and A. C. Bovik. Multi-scale underwater descattering. In <em>Proc. ICPR</em>, 2016.<br> <strong>[Ancuti et al. 2017]</strong> C. O. Ancuti, C. Ancuti, C. De Vleeschouwer, L. Neumann, and R. Garcia. Color transfer for underwater dehazing and depth estimation. In <em>Proc. IEEE ICIP</em>, 2017<em>(All color transfers were done with a single image)</em>.<br> <strong>[Emberton et al. 2017]</strong>S. Emberton, L. Chittka, and A. Cavallaro, Underwater image and video dehazing with pure haze region segmentation, <em>Computer Vision and Image Understanding</em>, 2017.<br> <strong>[Ancuti et al. 2018]</strong> . O. Ancuti, C. Ancuti, C. De Vleeschouwer, and P. Bekaert. Color balance and fusion for underwater image enhancement. IEEE Transactions on Image Processing, 27(1):379–393, 2018.</p>
Carcharhinus amblyrhynchos and Carcharhinus albimarginatus underwater acoustic telemetry data - Chagos Archipelago 2014-2018
<p>A wide array of technologies are available for gaining insight into the movement of wild aquatic animals. Although acoustic telemetry may lack the fine-scale resolution of some satellite tracking technologies, the substantially longer battery life can yield important long-term data on behaviour and movement for low per-unit cost. Typically, however, receiver arrays are designed to maximise spatial coverage at the cost of positional accuracy leading to potentially longer detection gaps as individuals move out of range between monitored locations. This is particularly true when these technologies are deployed to monitor species in hard-to-access locations. We develop a novel approach to analysing acoustic telemetry data, using the timing and duration of gaps between animal detections to classify movement behaviours into 'restricted' or potential wider 'out of range' movements synonymous with longer distance dispersal. We apply this method to investigate spatial and temporal segregation of inferred movement patterns in two sympatric species of reef shark within a large, remote Marine Protected Area. Drivers of these movements were identified using generalised linear mixed models and multi-model inference. Species, diel period and season were significant predictors of 'out of range' movements. Silvertip sharks were overall more likely to undertake 'out of range' movements, compared to grey reef sharks, indicating spatial segregation, and corroborating previous stable isotope work between these two species. High individual variability in 'out of range' movements in both species was also identified. We present a novel gap analysis of telemetry data to help infer differential movement and space use patterns where acoustic coverage is imperfect and other tracking methods impractical. In remote locations, inference may be the best available tool and this approach shows that acoustic telemetry gap analysis can be used for comparative studies in fish ecology, or combined with other research techniques to better understand functional mechanisms driving behaviour.</p>
Supplementary 1: Underwater photogrammetry for close-range 3D imaging of dry-sensitive objects: The case study of cephalopod beaks
<ul> <li>Technical advances in 3D imaging have contributed to quantifying and understanding biological variability and complexity. However, small, dry-sensitive objects are not easy to reconstruct using common and easily available techniques such as photogrammetry, surface scanning, or micro-CT scanning. Here we use cephalopod beaks as an example as their size, thickness, transparency, and dry-sensitive nature make them particularly challenging. We developed a new, underwater, photogrammetry protocol in order to add these types of biological structures to the panel of photogrammetric possibilities.</li> <li>We used a camera with a macro-photography mode in a waterproof housing fixed in a tank with clear water. The beak was painted and fixed on a colored rotating support. Three angles of view, two acquisitions, and around 300 pictures per specimen were taken in order to reconstruct a full 3D-model. These models were compared to others obtained with micro-CT scanning to verify their accuracy.</li> <li>The models can be obtained quickly and cheaply compared to micro-CT scanning, and have sufficient precision for quantitative inter-specific morphological analyses. Our work shows that underwater photogrammetry is a fast, non-invasive, efficient, and accurate way to reconstruct 3D models of dry-sensitive objects while conserving their shape. While the reconstruction of the shape is accurate, some internal parts cannot be reconstructed with photogrammetry as they are not visible. In contrast, these structures are visible using reconstructions based on micro-CT scanning. The mean difference between both methods is very small (10<sup>-5</sup> to 10<sup>-4</sup> mm) and is significantly lower than differences between meshes of different individuals.</li> <li>This photogrammetry protocol is portable, easy-to-use, fast, and reproducible. Micro-CT scanning, in contrast, is time-consuming, expensive and non-portable. This protocol can be applied to reconstruct the 3D shape of many other dry-sensitive objects such as shells of shellfish, cartilage, plants and other chitinous materials.</li> </ul>
Video S2. The rebound behavior of the monolith underwater after repeatable press-release.
Open the record for dataset details and reuse information.
Fig. 1 in Short communication First report of underwater oviposition by the island bluetail damselfly, Ischnura genei (Zygoptera, Coenagrionidae)
Fig. 1 - Female Ischnura genei photographed during underwater oviposition (left) and immediately after climbing out of the water (right). / Femmina di Ischnura genei fotografata durante l'ovodeposizione subacquea (a sinistra) e immediatamente dopo essersi arrampicata fuori dall'acqua (a destra).
Figure 5 in Underwater acoustic behavior of bearded seals (Erignathus barbatus) in the northeastern Chukchi Sea, 2007-2010
Figure 5. Notched box and whisker plots comparing monthly variation of the duration (s) of each bearded seal call type (A: AL1(T), B: AL1i(T), C: AL2(T), D: AL3(M), E: AL4(T), F: AL5(T), G: AL6(T) and H: AL7(A)) among three different years (2008: white, 2009: light gray, and 2010: dark gray). The notch represents the 95% simultaneous confidence interval on the means; dots indicate outliers. Nonoverlapping notches denote a significant difference.
Figure 1 in Underwater acoustic behavior of bearded seals (Erignathus barbatus) in the northeastern Chukchi Sea, 2007-2010
Figure 1. Recording station locations in the northeastern Chukchi Sea (Alaska, U.S.A.) for the 2007–2008, 2008–2009, and 2009–2010 overwinter programs (A) and for the summer 2009 and 2010 programs (B). Specifics on sampling effort are given in Table 1.
Figure 3 in Underwater acoustic behavior of bearded seals (Erignathus barbatus) in the northeastern Chukchi Sea, 2007-2010
Figure 3. Number of male bearded seal calls per 20 min sample for each overwinter recording station. Red lines indicate recording start and end.
Protistan metabolism across the western North Atlantic Ocean revealed through autonomous underwater profiling
<p>Metatranscriptomic assembly, predicted open reading frames, counts, and annotation files from seawater samples obtained in the western North Atlantic Ocean. GitHub notebooks are located here: <a href="https://github.com/cnatalie/BATS">https://github.com/cnatalie/BATS</a>. Assembly was created using the <em>eukrhythmic</em> pipeline: <a href="https://github.com/AlexanderLabWHOI/eukrhythmic">https://github.com/AlexanderLabWHOI/eukrhythmic</a></p> <ul> <li>merged_merged.fasta.gz = Final assembly, merged across 44 metatranscriptomes using 4 different assemblers</li> <li>merged.fasta.transdecoder.pep.zip = Open reading frames of final assembly, predicted by Transdecoder </li> <li>merged.fasta.transdecoder-estimated-taxonomy.out.zip = EUKulele-derived taxonomic annotations of ORFs using a combined EukProt, PhyloDB, and RefSeq reference database</li> <li>newtaxa.eukprot.merged.fasta.transdecoder-estimated-taxonomy.out.zip = similar to above, but manually curated mid-level taxonomy for supergroups of interest</li> <li>eggnog.emapper.annotations.zip = eggnog-mapper annotations of ORFs</li> <li>table.tab.zip = counts associated with ORFs (merged.fasta.transdecoder.pep) generated with Salmon</li> <li>TPM_table.tab.zip = community-wide TPM (normalized) counts associated with ORFs (merged.fasta.transdecoder.pep) generated with Salmon</li> <li>copiesperL_ORFs_FactorIncluded.csv.zip = raw counts associated with ORFs (merged.fasta.transdecoder.pep) converted to copies per L taking into account spiked-in RNA standard concentration (copies), standard reads mapped, volume of seawater filtered, and dilution factor used in library preparation</li> <li>assembly.table.tab.zip = counts associated with final assembly (merged_merged.fasta) generated with Salmon</li> <li>SamplesViewReportCLIO_AE1913merged_trans210506_updated220606exclusive.zip = Exclusive spectral counts associated with ORFs (merged.fasta.transdecoder.pep). Peptide-spectrum matches were performed using Sequest algorithm within IseNode Proteome Discoverer 2.2.0.388 (Thermo Fisher Scientific). Scaffold 5.1.2 (Proteome Software) was used for protein grouping and exclusive spectral counting. Note, the (+x) data has been removed from protein names, which indicates whether (and how many) proteins sharing peptides were designated into the same protein group. </li> <li>cds.length2.tab.zip = Length of proteins (ORFs) in nucleotide base pairs</li> <li>CTD.zip = CTD files from cruise AE1913</li> </ul>
Dataset for "A Fuel Cell Power Supply System Equipped with Artificial Gill Membranes for Underwater Applications"
<p>This data file contains the experimental data pertaining to the manuscript <br>"A Fuel Cell Power Supply System Equipped with Artificial Gill Membranes for Underwater Applications" by Lucas Merckelbach and Prokopios Georgopanos.</p> <p>Table of Contents</p> <p>-------------------</p> <p>experiments: data files and description/notes taken for each experiment reported in the manuscript, as well as the python script to create Figure 3 of the manuscript.</p> <p>The directory contains a README file with further information and instructions.</p>
Underwater Images
<p>Underwater image database</p>
Underwater Images
<p>Underwater Images</p>
Underwater Images
<p>Underwater Images</p>
Underwater Images
<p>Underwater Images</p>
FIGURE 5. Munidopsis papanui n in New records of Munidopsis (Crustacea: Anomura: Galatheidae) from New Zealand with description of two new species from a seamount and underwater canyon
FIGURE 5. Munidopsis papanui n. sp., holotype, ♂, NMNZ CR. 10023: A, right antennule,
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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.