Circumpolar phylogeography and demographic history of beluga whales reflect past climatic fluctuations
Bibliographic record
Abstract
Several Arctic marine mammal species are predicted to be negatively impacted by rapid sea ice loss associated with ongoing ocean warming. However, consequences for Arctic whales remain uncertain. To investigate how Arctic whales responded to past climatic fluctuations, we analysed 206 mitochondrial genomes from beluga whales (Delphinapterus leucas) sampled across their circumpolar range, and four nuclear genomes, covering both the Atlantic and the Pacific Arctic region. We found four well-differentiated mitochondrial lineages, which were established before the onset of the last glacial expansion ~110 thousand years ago. Our findings suggested these lineages diverged in allopatry, reflecting isolation of populations during glacial periods when the Arctic sea-shelf was covered by multiyear sea ice. Subsequent population expansion and secondary contact between the Atlantic and Pacific Oceans shaped the current geographic distribution of lineages, and may have facilitated mitochondrial introgression. Our demographic reconstructions based on both mitochondrial and nuclear genomes showed markedly lower population sizes during the Last Glacial Maximum (LGM) compared to the preceding Eemian and current Holocene interglacial periods. Habitat modelling similarly revealed less suitable habitat during the LGM (glacial) than at present (interglacial). Together, our findings suggested the association between climate, population size, and available habitat in belugas. Forecasts for year 2100 showed that beluga habitat will decrease and shift northwards as oceans continue to warm, putatively leading to population declines in some beluga populations. Finally, we identified vulnerable populations which, if extirpated as a consequence of ocean warming, will lead to a substantial decline of species-wide haplotype diversity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".