Population structure and divergence time among East Greenland and West Greenland/Eastern Canadian Arctic narwhals, Monodon monoceros
Bibliographic record
Abstract
Abstract The narwhal ( Monodon monoceros ) is an Arctic endemic odontocete that is particularly sensitive to climate change. Narwhals are also a key species in subsistence hunts in both Canada and Greenland. Understanding the genetic population structure is crucial to help management authorities set sustainable harvest quotas to avoid overexploitation of vulnerable narwhal groups. Additionally, estimates of population divergence times and their correlation with potential environmental drivers may be informative regarding the effects of environmental change. Herein, 2236 genome-wide single-nucleotide polymorphisms from 40 narwhals were used to infer population structure and divergence times. Samples were collected in six localities, one in East Greenland, four in West Greenland and one in the Eastern Canadian Arctic. The highest degree of genetic differentiation was observed between narwhals from Kangertittivaq (East Greenland) and Tasiujaq (Eastern Canadian Arctic), with a θ of 0.021 (95% confidence interval (CI): 0.014–0.028). While some locations in West Greenland also exhibited significant levels of differentiation (e.g., Uummannaq vs Qeqertarsuaq, θ = 0.011, 95% CI: 0.004–0.020), the East Greenland narwhals were most distinct based on both θ (varying from 0.01, 95% CI: 0–0.01 with Uummannaq to 0.021 95% CI: 0.014–0.028 with Tasiujaq) and clustering analyses. Our results are relevant to the management of narwhals in East Greenland, where current hunting levels are likely unsustainable. The divergence time estimated between East Greenland and West Greenland/Eastern Canadian Arctic suggests that narwhals in these two areas became separated during the Last Glacial Maximum, offering additional insight into the long-term population dynamics during climate change.
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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) | 0.000 | 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".