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18 results for “Ursus maritimus”
Modeling the demography of species providing extended parental care: A capture-recapture approach with a case study on Polar Bears (Ursus maritimus)
<p><span><span><span><span><span><span><span><span><span><span><span>1. In species providing extended parental care, one or both parents care for altricial young over a period including more than one breeding season. We expect large parental investment and long-term dependency within family units to cause high variability in life trajectories among individuals with complex consequences at the population level. So far, models for estimating demographic parameters in free-ranging animal populations mostly ignore extended parental care, thereby limiting our understanding of its consequences on parents and offspring life histories.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>2. We designed a capture-recapture multi-event model for studying the demography of species providing extended parental care. It handles statistical multiple-year dependency among individual demographic parameters grouped within family units, variable litter size, and uncertainty on the timing at offspring independence. It allows for the evaluation of trade-offs among demographic parameters, the influence of past reproductive history on the caring parent's survival status, breeding probability and litter size probability, while accounting for imperfect detection of family units. We assess the model performance using simulated data, and illustrate its use with a long-term dataset collected on the Svalbard polar bears (<i>Ursus maritimus</i>).</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>3. Our model performed well in terms of bias and mean square error and in estimating demographic parameters in all simulated scenarios, both when offspring departure probability from the family unit occurred at a constant rate or varied during the field season depending on the date of capture. For the polar bear case study, we provide estimates of adult and dependent offspring survival rates, breeding probability and litter size probability. Results showed that the outcome of the previous reproduction influenced breeding probability.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>4. Overall, our results show the importance of accounting for i) the multiple-year statistical dependency within family units, ii) uncertainty on the timing at offspring independence, and iii) past reproductive history of the caring parent. If ignored, estimates obtained for breeding probability, litter size, and survival can be biased. This is of interest in terms of conservation because species providing extended parental care are often long-living mammals vulnerable or threatened with extinction.</span></span></span></span></span></span></span></span></span></span></span></p>
Modeling polar bear (Ursus maritimus) snowdrift den habitat on Alaska's Beaufort Sea coast using SnowDens-3D and ArcticDEM data
<p>Pregnant polar bears (<em>Ursus maritimus</em>) excavate maternal dens in seasonal snowdrifts during fall along Alaska's Beaufort Sea coast to shelter their altricial young during birth and development. With recent sea ice decreases, bears are denning more frequently on land. Each year, the weather and blowing-snow conditions control the creation of snowdrifts across the landscape, and the available snowdrift den habitat can vary widely from one year to the next, depending on the late fall and early winter air temperature, snowfall, and wind speed and direction. We implemented a physics-based, spatiotemporal, polar bear snowdrift den habitat model (SnowDens-3D) across the eastern Alaska Beaufort Sea coast (an area of approximately 17,000 km^2^). High-resolution (2.0 m) topography data were provided by the ArcticDEM, and daily meteorological forcings were provided by NASA's MERRA-2 reanalysis. A 21-year (2000–2020) SnowDens-3D simulation was performed, and model outputs were compared with 91 historical polar bear den locations. The year-specific simulations produced viable den habitat for 98% of the observed den locations. The interannual variation in den habitat area over the 21-year period increased by approximately a factor of three from the minimum year (2001; 554 km^2^) to the maximum year (2017; 1,566 km^2^). This data archive provides the key den and den-habitat datasets produced, used, and analyzed by this project.</p>
Modeling polar bear (Ursus maritimus) snowdrift den habitat on Alaska’s Beaufort Sea coast using SnowDens-3D and ArcticDEM data
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Modeling the demography of species providing extended parental care: A capture-recapture approach with a case study on Polar Bears (Ursus maritimus)
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Data from: "Polar bear (Ursus maritimus) transcriptome assembly and SNP discovery" in Genomic Resources Notes accepted 1 August 2013-30 September 2013
Polar bears (Ursus maritimus) in the Western Hudson Bay subpopulation have been declining in size and body condition for decades, as climate change causes earlier sea ice breakup, reduced hunting time on the ice, and an increasingly long fasting season. As Western Hudson Bay females have decreased in size, rates of litter production and average litter size have also decreased, while cub mortality and average time to independence have increased. Although these changes have potential evolutionary consequences, little is yet known about the adaptive genetic variation in body size or fat accumulation that would have to underlie any such change. In this study, we used high-throughput Illumina sequencing to develop SNPs from pooled blood and fat transcriptomes, using samples from five adult female polar bears and five (unrelated) dependent cubs. In total, we generated 371,258 transcripts of which 36,755 were deemed to be "full length" (i.e., covered more than 90% of their best BLAST hit), and we identified 63,020 SNPs. Since this study was conducted, we have used a subset of these SNPs to develop an Illumina BeadArray for quantitative genetics research in Western Hudson Bay.
Data from: Design of a 9K SNP chip for polar bears (Ursus maritimus) from RAD and transcriptome sequencing
Single-nucleotide polymorphisms (SNPs) offer numerous advantages over anonymous markers such as microsatellites, including improved estimation of population parameters, finer-scale resolution of population structure and more precise genomic dissection of quantitative traits. However, many SNPs are needed to equal the resolution of a single microsatellite, and reliable large-scale genotyping of SNPs remains a challenge in nonmodel species. Here, we document the creation of a 9K Illumina Infinium BeadChip for polar bears (Ursus maritimus), which will be used to investigate: (i) the fine-scale population structure among Canadian polar bears and (ii) the genomic architecture of phenotypic traits in the Western Hudson Bay subpopulation. To this end, we used restriction-site associated DNA (RAD) sequencing from 38 bears across their circumpolar range, as well as blood/fat transcriptome sequencing of 10 individuals from Western Hudson Bay. Six-thousand RAD SNPs and 3000 transcriptomic SNPs were selected for the chip, based primarily on genomic spacing and gene function respectively. Of the 9000 SNPs ordered from Illumina, 8042 were successfully printed, and – after genotyping 1450 polar bears – 5441 of these SNPs were found to be well clustered and polymorphic. Using this array, we show rapid linkage disequilibrium decay among polar bears, we demonstrate that in a subsample of 78 individuals, our SNPs detect known genetic structure more clearly than 24 microsatellites genotyped for the same individuals and that these results are not driven by the SNP ascertainment scheme. Here, we present one of the first large-scale genotyping resources designed for a threatened species.
Data from: Assessing polar bear (Ursus maritimus) population structure in the Hudson Bay region using SNPs
Defining subpopulations using genetics has traditionally used data from microsatellite markers to investigate population structure; however, single-nucleotide polymorphisms (SNPs) have emerged as a tool for detection of fine-scale structure. In Hudson Bay, Canada, three polar bear (Ursus maritimus) subpopulations (Foxe Basin (FB), Southern Hudson Bay (SH), and Western Hudson Bay (WH)) have been delineated based on mark–recapture studies, radiotelemetry and satellite telemetry, return of marked animals in the subsistence harvest, and population genetics using microsatellites. We used SNPs to detect fine-scale population structure in polar bears from the Hudson Bay region and compared our results to the current designations using 414 individuals genotyped at 2,603 SNPs. Analyses based on discriminant analysis of principal components (DAPC) and STRUCTURE support the presence of four genetic clusters: (i) Western—including individuals sampled in WH, SH (excluding Akimiski Island in James Bay), and southern FB (south of Southampton Island); (ii) Northern—individuals sampled in northern FB (Baffin Island) and Davis Strait (DS) (Labrador coast); (iii) Southeast—individuals from SH (Akimiski Island in James Bay); and (iv) Northeast—individuals from DS (Baffin Island). Population structure differed from microsatellite studies and current management designations demonstrating the value of using SNPs for fine-scale population delineation in polar bears.
Data from: Genetic relationships of extant brown bears (Ursus arctos) and polar bears (Ursus maritimus)
Polar bears (Ursus maritimus) and brown bears (Ursus arctos) are closely related species for which extensive mitochondrial and nuclear phylogenetic genetic comparisons have been made. We used previously-published genotype data for 8 microsatellite DNA loci from 930 brown bears in 19 populations and 473 polar bears in 16 populations to compare the population genetic relationships of extant populations of the species. Genetic distances (Nei standard distance = 1.157), the proportion of private alleles (52% of alleles are not shared by the species), and Bayesian cluster analysis are consistent with morphological and life history characteristics that distinguish polar bears and brown bears as different species with little or no gene flow among extant populations.
Data from: Icing-related injuries in polar bears (Ursus maritimus) at high latitudes
<p>Climate change has broad ecological implications for wildlife, especially for species that rely on temperature-sensitive habitats. For polar bears (<em>Ursus maritimus</em>), loss of Arctic sea ice reduces access to prey and lengthens seasonal fasting periods leading to behavioral, nutritional, and reproductive impacts that may result in population declines. Secondary factors, such as disease and contaminants can exacerbate primary stressors and new health-related conditions are likely to emerge. For example, once unusual but now increasingly frequent warming cycles are creating unprecedented icing conditions that have demographic consequences for cold-adapted mammals.</p> <p>We report on icing-related lesions observed in wild polar bears during live-capture research in two high-latitude subpopulations, Kane Basin (KB) and East Greenland (EG), between 2012 and 2022. We observed ice build-up, hair loss (alopecia), and skin ulcerations primarily affecting the feet of adult bears as well as other parts of the body. The most severely affected individuals had blocks of ice up to 30 cm in diameter adhered to the foot pads, deep, bleeding ulcerations of foot pads and exhibited lameness. These injuries have not been observed during previous research in these areas or reported in the scientific literature, suggesting this may be a new phenomenon. To provide context for our observations, we conducted interviews with Indigenous polar bear subsistence hunters in West and East Greenland and Nunavut to document Indigenous knowledge about the potential causes and frequency of these injuries.</p>
Data from: Assessing polar bear (Ursus maritimus) population structure in the Hudson Bay region using SNPs
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Data from: "Polar bear (Ursus maritimus) transcriptome assembly and SNP discovery" in Genomic Resources Notes accepted 1 August 2013-30 September 2013
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Data from: Design of a 9K SNP chip for polar bears (Ursus maritimus) from RAD and transcriptome sequencing
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Data from: Extensive sampling of polar bears (Ursus maritimus) in the Northwest Passage (Canadian Arctic Archipelago) reveals population differentiation across multiple spatial and temporal scales
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Data from: Icing-related injuries in polar bears (Ursus maritimus) at high latitudes
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Data from: Genetic relationships of extant brown bears (Ursus arctos) and polar bears (Ursus maritimus)
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On following pages: 8. Polar Bear (Ursus maritimus). in Ursidae
On following pages: 8. Polar Bear (Ursus maritimus).
Data from: Molecular phylogeny and SNP variation of polar bears (Ursus maritimus), brown bears (U. arctos) and black bears (U. americanus) derived from genome sequences
We assessed the relationships of polar bears (Ursus maritimus), brown bears (U. arctos), and black bears (U. americanus) with high throughput genomic sequencing data with an average coverage of 25X for each species. A total of 1.4 billion 100-bp paired-end reads was assembled using the polar bear and annotated giant panda (Ailuropoda melanoleuca) genome sequences as references. We identified 13.8 million single nucleotide polymorphisms (SNP) in the three species aligned to the polar bear genome. These data indicate that polar bears and brown bears share more SNP with each other than either does with black bears. Concatenation and coalescence-based analysis of consensus sequences of approximately one million base pairs of ultra-conserved elements (UCE) in the nuclear genome resulted in a phylogeny with black bears as the sister group to brown and polar bears, and all brown bears are in a separate clade from polar bears. Genotypes for 162 SNP loci of 336 bears from Alaska and Montana showed that the species are genetically differentiated and there is geographic population structure of brown and black bears but not polar bears.
Data from: Molecular phylogeny and SNP variation of polar bears (Ursus maritimus), brown bears (U. arctos) and black bears (U. americanus) derived from genome sequences
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