Estimating Effective Sizes of Canada’s Polar Bear Populations
Bibliographic record
Abstract
Arctic climate continues to warm more rapidly than the rest of the planet, and species distributions are expected to change profoundly. As the Arctic’s apex predator, the polar bear (Ursus maritimus) is greatly impacted by many aspects of the changing Arctic environment. We do not have a clear understanding of polar bear population structure and estimates of important demographic parameters are out of date or lacking for many populations. Effective population size (Ne) is an important metric when addressing the persistence of a species and is proportional to the level of genetic diversity within a population. My study uses fecal, harvest tissue, and biopsy samples to explore estimators of Ne and to investigate the contemporary and historic trends in Ne for the Canadian Arctic populations of polar bears. My results suggest that the linkage disequilibrium method of estimating contemporary Ne is most appropriate for monitoring projects that uses non-invasively collected, or degraded samples as this method can produce precise estimates of Ne with only 322 SNPs. Contemporary estimates of Ne and corresponding ratios of effective to census size (Ne/Nc) for four previously defined genetic clusters are: Polar Basin (Ne=145, Ne/Nc=0.07), Arctic Archipelago (Ne=360, Ne/Nc=0.04), M’Clintock Channel (Ne=149, Ne/Nc=0.21), and the Hudson Bay Complex (Ne=307, Ne/Nc=0.07). Given recent evidence of migration between M’Clintock Channel and the Arctic Archipelago, I suggest that conservation efforts focus on the Hudson Bay Complex and Polar Basin regions due to their low connectivity with other clusters and their low effective sizes. My analysis of historic demographic trends suggests the four genetic cluster within the Canadian Arctic have independently experienced declines in effective size over the last 500 Ky, with only slight periods of recovery during times of global cooling. These results indicate current estimates of Ne likely represent a historic low in Ne and therefore an already reduce level of genetic diversity. Future studies should aim to better understand the dynamics between the Arctic Archipelago and M’Clintock Channel as the connectivity between these regions is likely to be vital for the long-term persistence of the polar bear.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".