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139 results for “brown bears”
Figure 1 in Current status, distribution, and conservation of brown bear (Ursidae) and wild canids (gray wolf, golden jackal, and red fox; Canidae) in Turkey
Figure 1. The distribution map of brown bear.
Text-fig. 10. Frequencies of anterior premolar patterns in mandibles (data after Tab. 4). in Anterior Premolar Variability In Pleistocene Cave And Brown Bears And Its Significance In Species Determination
Text-fig. 10. Frequencies of anterior premolar patterns in mandibles (data after Tab. 4).
Text-fig. 9. Frequencies of anterior premolar patterns in maxillae (data after Tab. 2). in Anterior Premolar Variability In Pleistocene Cave And Brown Bears And Its Significance In Species Determination
Text-fig. 9. Frequencies of anterior premolar patterns in maxillae (data after Tab. 2).
Range-wide whole-genome resequencing of the brown bear reveals drivers of intraspecies divergence
<p>The brown bear is a textbook example species of the effect of Quaternary glaciation cycles on the present-day geographical distribution of mtDNA haplotypes. We compiled and analysed a range-wide whole-genome dataset of 128 brown bear individuals in order to re-evaluate brown bear population structure and genetic diversity using nuclear markers from autosomes and sex chromosomes. The file 'PLOTCOMMANDS.txt' contains detailed instructions on how to recreate the figures presented within the paper. </p>
Age estimation based on blood DNA methylation levels in brown bears
<p><span>Age is an essential trait for understanding the ecology and management of wildlife. A conventional method of estimating age in wild animals is counting annuli formed in the cementum of teeth. This method has been used in bears despite some disadvantages, such as high invasiveness and the requirement for experienced observers. In this study, we established a novel age estimation method based on DNA methylation levels using blood collected from 49 brown bears</span><span> </span><span>of known ages living in both captivity and the wild. We performed bisulfite pyrosequencing and obtained methylation levels at 39 cytosine-phosphate-guanine (CpG) sites adjacent to 12 genes. The methylation levels of CpGs adjacent to four genes showed a significant correlation with age. The best model was based on DNA methylation levels at just four CpG sites adjacent to a single gene, SLC12A5, and it had high accuracy with a mean absolute error of 1.3 years and median absolute error of 1.0 year after leave-one-out cross-validation. This model represents the first epigenetic method of age estimation in brown bears, which provides benefits over tooth-based methods, including high accuracy, less invasiveness, and a simple procedure. Our model has the potential for application to other bear species, which will greatly improve ecological research, conservation, and management.</span></p>
Data for: Ingredient and nutrient composition of brown bear diets
<p><span>The dietary nutrient profile has metabolic significance and possibly contributes to species' foraging behavior. The brown bear (<em>Ursus arctos</em>) was used as a model species for which dietary ingredient and nutrient concentrations as well as nutrient ratios were determined annually, seasonally and per reproductive class. Brown bears had a vertebrate- and ant-dominated diet in spring and early summer and a berry-dominated diet in fall, which translated into protein-rich and carbohydrate-rich diets, respectively. Fiber concentrations appeared constant over time and averaged at 25 % of dry matter intake. Dietary ingredient proportions differed between reproductive classes; however, these differences did not translate into a difference in dietary nutrient concentrations, suggesting that bears manage to maintain similar nutrient profiles with selection of different ingredients. In terms of nutrient ratios, the dietary protein to non-protein ratio, considered optimal at around 0.2 (on metabolizable energy basis), averaged around 0.2 in this study in fall and around 0.8 in spring and summer. We introduced the minimal non-fat to fat ratio necessary for efficient maintenance metabolism. This ratio varied across seasons but never fell beneath the theoretically estimated minimum to ensure metabolic efficiency. This population thus managed to ingest diets that never exerted a lack of glucogenic substrate, suggesting that metabolic efficiency may either be a driver of active diet selection or that natural resources available to bears did not constitute a constraint in this respect. Given the considerable proportion of fiber in the diet of brown bears, the relevance of this nutrient and its role in foraging behavior might be underestimated.</span></p>
Data from: A test of the green wave hypothesis in omnivorous brown bears across North America
<p>Herbivorous animals tend to seek out plants at intermediate phenological states to improve energy intake while minimizing consumption of fibrous material. In some ecosystems, the timing of green-up is heterogeneous and propagates across space in a wave-like pattern, known as the green wave. Tracking the green wave allows individuals to prolong access to higher-quality forage. While there is a plethora of empirical support for such behavior in herbivorous taxa, the green wave hypothesis (GWH) is nuanced based on factors such as body morphometrics and digestive capacity. Furthermore, little is known about whether other taxa, such as omnivores, track the green wave. Our objective was to assess whether the GWH can be extended to explain the movements of omnivores. Using GPS collar data from seven populations (n = 127 individuals) of brown bears (<em>Ursus</em> <em>arctos</em>) across their entire North American range, we first tested whether bears tracked the green wave. Using conditional resource selection functions, we found that variation in proxies of vegetative forage quality better-explained movement and habitat selection than proxies of forage biomass in over half of the bears in our study, providing evidence of green wave tracking. Second, we assess factors that explained variation in green wave tracking using linear mixed-effects models. Green wave tracking in brown bears was explained by the variation in availability of green-up within spring home ranges, and how green-up transitioned across those home ranges. Our results demonstrate that the GWH can partially explain movement of a non-migratory omnivorous species, extending the generality of the GWH as a broad predictor of animal space use. The green wave is another resource wave brown bears track, and our findings help predict brown bear space use, which can be used to guide conservation and habitat restoration efforts.</p>
Data from: Competition between apex predators? Brown bears decrease wolf kill rate on two continents
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Data from: Behavioural responses of brown bears to roads and hunting disturbance
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Data from: A test of the green wave hypothesis in omnivorous brown bears across North America
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Behavior of brown bears foraging on sockeye salmon in Lake Aleknagik, Alaska (foraging tactics and success)
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Age estimation based on blood DNA methylation levels in brown bears
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Genotype data from: Restoration of transborder connectivity for Fennoscandian brown bears (Ursus arctos)
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The diel niche of brown bears: constraints on adaptive capacity in human-modified landscapes
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Data for: Ingredient and nutrient composition of brown bear diets
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Data from: Steep and deep: Terrain and climate factors explain brown bear (Ursus arctos) alpine den site selection to guide heli-skiing management
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Blood cortisol and fecal cortisol metabolite concentrations following an ACTH challenge in unanesthetized brown bears (Ursus arctos)
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Range-wide whole-genome resequencing of the brown bear reveals drivers of intraspecies divergence
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Autosomal SNP-genotype data of brown bears (Ursus arctos) in Finland
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Estimation of breeding population size using DNA-based pedigree reconstruction in brown bears
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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.
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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.