Population Genomics and Quantitative Genetics of Polar Bears (Ursus maritimus)
Bibliographic record
Abstract
Polar bears (Ursus maritimus) were among the first large mammals to be assessed for genetic variation in the wild, and they remain a common subject of genetics studies. Although recent advances in genotyping technology have allowed for more accurate determination of population structure and the detection of adaptive variation, most modern research has focused on historical divergence between polar bears and brown bears—a topic with little relevance to current management. The goal of this dissertation is to develop and use large datasets to better describe contemporary genetic variation in polar bears. To this end, I first describe a reanalysis of global polar bear population structure using nuclear microsatellites and mitochondrial DNA. This reanalysis was necessitated by the publication of a study suffering from flaws in design and analysis, most notably non-convergence of BAYESASS, a program used to estimate migration rates. In this reanalysis, I have rectified these errors, and—in contrast to the original study—I show that there is no evidence of strong directional movement in response to recent climate-change-induced loss of sea ice. Second, I describe the development of a custom 9K Illumina Infinium BeadChip for polar bears from restriction-site associated DNA (RAD) and transcriptome sequencing. I show the utility of this chip for sex determination of samples from harvested individuals, and that it gives realistic estimates of population structure and linkage disequilibrium (LD) decay. Third, I perform a more comprehensive Canada-wide population genetic analysis using genotypes from this BeadChip, which provides higher resolution than microsatellites. I confirm the presence of four moderately differentiated genetic clusters of polar bears across the Canadian Arctic, including the Beaufort Sea, the Canadian Arctic Archipelago, Norwegian Bay, and the Hudson Bay Complex. I also confirm the presence of east–west substructure within the Canadian Arctic Archipelago and north–south substructure within the Hudson Bay Complex. Evidence for adaptive differentiation between these clusters is limited. For the two remaining data chapters, I narrow my focus to the Western Hudson Bay management unit, where Environment and Climate Change Canada researchers have conducted mark–recapture studies and collected phenotypic data since 1966. First, I describe the construction of a 4449-individual multigenerational pedigree for Western Hudson Bay bears—among the most extensive pedigrees for any large mammal in the world. I show that inbreeding is rare in this subpopulation, and I document the first known pair of identical twin bears and six new cases of cub adoption. These results are discussed in the context of inclusive fitness theory. Finally, I use this pedigree to estimate the heritability of four routinely measured adult traits: head length, zygomatic breadth, body length, and axillary girth (a measure that is partially dependent on fatness). I then use the BeadChip to perform association studies of these traits. I find moderate heritability (h2 = 0.34–0.48) for strictly skeletal traits and lower heritability (h2 = 0.17) for axillary girth, and I show that variability in these traits is not convincingly affected by any genes of large effect in LD with markers on the BeadChip. Implications for future adaptation are discussed. Collectively, this dissertation represents the most comprehensive assessment of contemporary polar bear genetic variation that has ever been conducted, not only within Western Hudson Bay, but also at the Canadian and circumpolar levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".