Population genomics of harbour seal <i>Phoca vitulina</i> from northern British Columbia through California and comparison to the Atlantic subspecies
Bibliographic record
Abstract
The harbour seal Phoca vitulina is a ubiquitous pinniped species found throughout coastal waters of the Northern Hemisphere. Harbour seal impacts on ecosystem dynamics may be significant due to their high abundance and food web position. Two subspecies exist in North America, P. v. richardii in the Pacific Ocean and P. v. vitulina in the Atlantic. Strong natal philopatry of harbour seals can result in fine-scale genetic structure and isolation by distance. Management of harbour seals is expected to benefit from improved resolution of seal population structure and dynamics. Here, we use genotyping-by-sequencing to genotype 146 harbour seals from the eastern Pacific Ocean (i.e. British Columbia (BC), Oregon and California) and the western Atlantic Ocean (i.e. Québec, Newfoundland and Labrador). Using 12,742 identified variants, we confirm the recently identified elevated genetic diversity in the eastern Pacific relative to the western Atlantic and greatest differentiation between the subspecies. Further, we demonstrate that this is independent of reference genome bias or other potential technical artefacts. Coast-specific analyses with 8933 and 3828 variants in Pacific and Atlantic subspecies, respectively, identify divergence between BC and Oregon-California, and between Québec and Newfoundland-Labrador. Unexpected PCA outlier clusters were observed in two populations due to cryptic relatedness of individuals; subsequently, closely related samples were removed. Admixture analysis indicates an isolation-by-distance signature where Oregon seals contained some of the BC signature, whereas California did not. Additional sampling is needed in the central and north coast of BC to determine whether a discrete separation of populations exists within the region.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".