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26 results for “gentoo”
Rediscovery Datasets: Connecting Duplicate Reports of LibreOffice and Gentoo
<p>We present two defect rediscovery datasets mined from Bugzilla (supplementary to previously published datasets: Zenodo, http://doi.org/10.5281/zenodo.400614). These datasets capture data for two groups of open source software projects: LibreOffice and Gentoo. The datasets contain information about the inter-relationships among duplicate defects.<br> </p> <p><strong>File Descriptions</strong></p> <ul> <li>libreoffice.csv - LibreOffice Defect Rediscovery dataset</li> <li>gentoo.csv - Gentoo Defect Rediscovery dataset</li> </ul> <p> </p> <ul> <li>libreoffice.relations.csv - Inter-relations of rediscovered defects of LibreOffice</li> <li>gentoo.relations.csv - Inter-relations of rediscovered defects of Gentoo</li> </ul>
Calories Derived from Lipids in Adelie and Gentoo Penguin Diets at Palmer Station, 2022–2023
This dataset contains measurements of caloric energy (in kilojoules) derived from lipids in regurgitated diet samples collected from Adélie and gentoo penguins during the PAL2223 and PAL2324 field seasons near Palmer Station, along the western Antarctic Peninsula. Diet samples were homogenized through blending, and lipids were subsequently extracted for calorimetric analysis to quantify energy content. These data were used in support of the manuscript "Trophic transfer of lipid-derived energy through Adélie and Gentoo penguins near Palmer Station along the west Antarctic Peninsula", published in *Polar Biology* 48, 110 (2025), by Shavonna M. Bent et al. https://doi.org/10.1007/s00300-025-03430-5
NeuroGentoo Presentation - Bringing the Power of Gentoo Package Management to (Neuro)Scientific Software Environments
<p>Neuroscience, one of the most computation-reliant fields in the natural sciences, is dependent upon dozens of highly complex software suites, which scientists are often forced to manage manually. Upstream developers often ship bundled dependencies to better support this flawed workflow, and in the resulting mess documenting and reproducing analysis pipelines is neigh-impossible. We seek to correct these shortcoming of both modern software distribution as well as modern data science, by integrating high-quality ebuilds for neuroscientific software into the Gentoo Science Overlay. We also seek to publish a simple NuroGentoo world file (along with appropriate usage instructions) to allow scientists with access to OpenStack, Amazon Elastic Computing, or Docker to launch up and build a system fit for reproducing data analysis run on other NeuroGentoo systems with minimum effort.</p>
Data from: Sulfur isotopic discrimination factors differ among avian tissues and diets: Insights from a case study in Gentoo Penguins (Pygoscelis papua)
<p>The use of stable isotopes of sulfur (δ<sup>34</sup>S) to infer avian diets, foraging habitats, and movements is relatively uncommon, resulting in a lack of information on patterns of δ<sup>34</sup>S incorporation in avian tissue. In a controlled study of Gentoo Penguins (<em>Pygoscelis</em> <em>papua</em>), we found that diet-tissue isotopic discrimination factors (Δ<sup>34</sup>S<sub>diet-tissue</sub>) differed among egg components and feathers synthesized from a common diet, ranging from -0.4 to -1.7 ‰. We also found that methodical choices such as lipid extraction and prey tissue selection influenced calculated Δ<sup>34</sup>S<sub>diet-tissue</sub> values. Specifically, Δ<sup>34</sup>S<sub>diet-tissue</sub> values were lower (i.e., more negative) when calculated using whole fish relative to fish muscle and lipid-extraction biased egg yolk, but not fish tissue, δ<sup>34</sup>S values. Δ<sup>34</sup>S<sub>diet-tissue</sub> values obtained for Gentoo Penguins fed a marine fish diet were generally lower than those reported for freshwater-fish-consuming Double-crested Cormorants (<em>Phalacrocorax</em> <em>auritus</em>), the only other bird species in which Δ<sup>34</sup>S<sub>diet-tissue</sub> has been quantified. We found support for the hypothesis that tissue Δ<sup>34</sup>S<sub>diet-tissue</sub> values are inversely related to dietary δ<sup>34</sup>S values in birds, similar to what has been observed in mammals. Given<span> this relationship, the discrimination factors reported here for </span>Gentoo Penguins <span>may be broadly applicable to other avian species with a similar marine diet.</span> Finally, we provide recommendations for future studies seeking to quantify Δ<sup>34</sup>S<sub>diet-tissue</sub> in avian tissues and guidance to allow for greater application of sulfur stable isotope analysis in ornithological research.</p>
Data from: Sulfur isotopic discrimination factors differ among avian tissues and diets: Insights from a case study in Gentoo Penguins (Pygoscelis papua)
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Datasets supporting: Coastal regions of the northern Antarctic Peninsula are key for gentoo populations
<p>Southern Ocean ecosystems are rapidly changing due to climate variability. An apparent beneficiary of such change in the western Antarctic Peninsula (WAP) is the gentoo penguin <em>Pygoscelis papua</em>, which has increased its population size and expanded its range southward in the last 20 years. To better understand how this species has responded to large-scale changes, we tracked individuals during the non-breeding winter period from five colonies across the latitudinal range of breeding sites in the WAP, including from a recently-established colony. Results highlight latitudinal gradients in movement; strong associations with shallow, coastal habitats along the entire Antarctic Peninsula; and movements that are independent of, yet constrained by, sea ice. It is clear that coastal habitats essential to gentoo penguins during the breeding season are similarly critical during winter. Larger movements of birds from northern colonies in the WAP further suggest that leap-frog migration may influence colonization events by facilitating nest-area prospecting and use of new haul-out sites. Our results support efforts to develop a marine protected area around the WAP. Winter habitats used by gentoo penguins outline high priority areas for improving management of the spatiotemporally concentrated krill (<em>Euphausia superba</em>) fishery that operates in this region during winter.</p>
Data from: Variation in the ecstatic display call of the Gentoo Penguin (Pygoscelis papua) across regional geographic scales
Geographic variation in bird vocalizations is common and has been associated with genetic differences and speciation, as well as with short-term changes in response to anthropogenic noise. Because vocalizations are used for individual recognition in many species, geographic variation in these traits may affect mate choice, pair bonding, and territory defense. Anecdotal evidence suggests the existence of geographic variation in vocalizations between isolated populations of Gentoo Penguins (Pygoscelis papua), but there have been no comprehensive studies of Gentoo Penguin vocalizations across a broad geographic range. We used acoustic recordings of ambient colony sound at 22 breeding colonies in the Antarctic Peninsula and South Shetland Islands, South Georgia, the Falkland Islands, and Argentina to address 2 main questions regarding Gentoo Penguin vocalizations: (1) How do ecstatic display calls vary both within and between individuals, colonies, and regions? (2) Can ecstatic display calls be used to distinguish subspecies? We found high levels of variation between individuals and between colonies, but little additional variation between regions or subspecies. We found no trends to suggest a latitudinal gradient in vocal characteristics, although we did find that some measures varied with relative distance between colonies. Although we found significant differences at the colony level, unknown calls could not easily be categorized to colony or region by machine learning. We conclude that the vocal soundscape of each colony is driven by variation between individuals within a colony and, developing independently from neighboring colonies, becomes differentiated from other colonies through a process of drift. Although individual calls could, in most cases, be identified to subspecies by machine learning, our analysis suggests that subspecies differences may be driven by variation among colonies and that subspecies identification may be unreliable using acoustics alone.
Gentoo penguins (Pygoscelis papua) react to underwater sounds
<p>Marine mammals and diving birds face several physiological challenges under water, affecting their thermoregulation and locomotion as well as their sensory systems. Therefore, marine mammals have modified ears for improved underwater hearing. <a name="_Hlk5740480">Underwater hearing in marine birds have been studied in a few species, but for the record-holding divers, such as penguins, there are no detailed data</a>. We played underwater noise bursts to gentoo penguins<i> (Pygoscelis papua)</i> in a large tank at sound pressure levels between 100 and 120 dB re 1 µPa rms. The penguins showed a graded reaction to the noise bursts, ranging from no reactions at 100 dB to strong reactions in more than 62% of the playbacks at 120 dB re 1 µPa. The responses were always directed away from the sound source. The fact that penguins can detect and react to underwater stimuli may indicate that they make use of sound stimuli for orientation and prey detection during dives. Further, it suggests that penguins may be sensitive to anthropogenic noise, like many species of marine mammals.</p>
Species delimitation beyond phylogenomics: integrative approaches reveal gentoo penguin speciation
<p>Isolation and adaptation to new environments are important steps for reproductive isolation and consequently speciation. Seabirds have low phenotypic variation along their ranges in the absence of clear geographic or environmental barriers to dispersal. Despite the lacking visible phenotypic differences, the number of taxa for the gentoo penguin (<em>Pygoscelis papua</em>, Forster 1781) in the Southern Ocean has been under debate for the last decade, ranging from one to six different taxa. Here, we provide several lines of evidence from genomics, ecology, morphological data, and a complete systematic review that supports four distinctive gentoo penguin species, including the description of a new species. We also provide future niche projections for each of these species. Gentoo penguin genomes (n = 64) recover four main lineages: the northern gentoo (from South America), the southern gentoo (Antarctic Peninsula and maritime Antarctica, south of the Antarctic Polar Front, APF), the southeastern gentoo (from Kerguelen Islands), and the eastern gentoo (colonies located at lower latitudes north of the APF). Our analysis of selection across the genome recovered between 42 and 101 genes under selection for each of the four species, demonstrating that the four species are experiencing differing selective pressures that have caused them to diverge adaptively. The function of these genes affects traits that include reproduction, thermoregulation, osmoregulation, feed efficiency, and morphological variation. Morphological data were taken from museum individuals of all lineages, including from South Georgia gentoos, which have previously been considered a distinct taxon. Multivariate morphological comparisons of all pairs of lineages showed that the northern, southern, southeastern, and South Georgia gentoo penguins are morphologically distinct from each other (p < 0.05 for all pairwise comparisons), while the eastern lineage is intermediate in size and overlaps in morphospace with other lineages. This result also suggests that body size across latitudes is in direct contrast to Bergmann's rule. Here, we describe the southeastern gentoo penguin from Kerguelen Island and confirm the taxonomic rank of gentoos from Macquarie Island and South Georgia Island as subspecies. Species distribution modelling suggests that climate change will expand the favourable space for the southern range expansion of the southern gentoo penguin but would result in a net loss of suitable habitats for compensatory niche shift relocation for the northern and southeastern gentoos. Despite this, amongst the three subantarctic species, the northern and southeastern gentoos possess high neutral and adaptive genetic diversity, including genes related to cold and heat response. This may represent a higher potential to evolve under environmental changes compared with the eastern gentoo penguin; therefore, the future resilience of each species remains uncertain. This study reinforces the urgent need for explicit recognition and protection of the four regional gentoo species based on their genetic, morphological, and ecological distinctiveness.</p>
Datasets supporting: Coastal regions of the northern Antarctic Peninsula are key for gentoo populations
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Species delimitation beyond phylogenomics: integrative approaches reveal gentoo penguin speciation
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Data from: Population structure and phylogeography of the Gentoo Penguin (Pygoscelis papua) across the Scotia Arc
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Gentoo penguins (Pygoscelis papua) react to underwater sounds
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Data from: Variation in the ecstatic display call of the Gentoo Penguin (Pygoscelis papua) across regional geographic scales
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Structural size measurements and isotopic signatures of foraging among adult male and female gentoo penguins (Pygoscelis papua) nesting along the Palmer Archipelago near Palmer Station, 2007-2009
Sexual segregation in vertebrate foraging niche is often associated with sexual size dimorphism (SSD), i.e., ecological sexual dimorphism. We examined ecological sexual dimorphism among sympatric nesting Pygoscelis penguins near Palmer Station, Antarctica, asking whether environmental variability in the form of winter sea ice is associated with differences in male and female pre-breeding foraging niche. Each season, study nests, where pairs of adults were present, were individually marked and chosen before the onset of egg-laying, and consistently monitored. When study nests were found at the one-egg stage, both adults were captured to obtain blood samples used for molecular sexing and stable isotope analyses, and measurements of structural size and body mass. At the time of capture, each adult penguin was quickly blood sampled (~1 ml) from the brachial vein. After handling, individuals at study nests were further monitored to ensure the pair reached clutch completion, i.e., two eggs. Molecular analyses were conducted at Simon Fraser University following standard PCR protocols, and stable isotope analyses were conducted at the Stable Isotope Facility at the University of California, Davis using an elemental analyzer interfaced with an isotope ratio mass spectrometer
Gentoo Penguin
Drawing uploaded to scidraw.io on: 15 August 2019
A Large Corpus of C Source Code based on Gentoo packages
<p>Corpus of C packages extracted from the Gentoo packages, created for the JSEP publication.</p>
Figure 1a from: Ioanas H, Saab B, Rudin M (2017) Gentoo Linux for Neuroscience - a replicable, flexible, scalable, rolling-release environment that provides direct access to development software. Research Ideas and Outcomes 3: e12095. https://doi.org/10.3897/rio.3.e12095
Figure 1a - Minimal (excluding all optional features) dependency graph of the contributed neuroscience package set.
Figure 1b from: Ioanas H, Saab B, Rudin M (2017) Gentoo Linux for Neuroscience - a replicable, flexible, scalable, rolling-release environment that provides direct access to development software. Research Ideas and Outcomes 3: e12095. https://doi.org/10.3897/rio.3.e12095
Figure 1b - Maximal (including all optional features) dependency graph of the contributed neuroscience package set.
Gentoo Penguin
Drawing uploaded to scidraw.io on: 15 August 2019
ScienceDex guides
Understand access before you commit
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.