Kinship clustering within an ecologically diverse killer whale metapopulation
Bibliographic record
Abstract
Metapopulation dynamics can be shaped by foraging ecology, and thus be sensitive to shifts in prey availability. Genotyping 204 North Atlantic killer whales at 1346 loci, we investigated whether spatio-temporal population structuring is linked to prey type and distribution. Using population-based methods (reflecting evolutionary means), we report a widespread metapopulation connected across ecological groups based upon nuclear genome SNPs, yet spatial structuring based upon mitogenome haplotypes. These contrasting patterns of markers with maternal and biparental inheritance are consistent with matrilineal site fidelity and philopatry, and male-mediated gene flow among demes. Connectivity between fish-eating and 'mixed-diet' (eating both fish and mammal prey) killer whales, marks a deviation within a species renowned for its marked structure associated with ecology. However, relatedness estimates suggest distinct spatial clusters, and heterogeneity in recent gene flow between them. The contrasting patterns between inference of structure and inference of relatedness suggest that gene flow has been partially restricted over the past two to three generations (50-70 years). This coincides with the collapse of North Atlantic herring stocks in the late 1960s and the subsequent cessation of their seasonal connectivity. Statistically significant association between diet types and assignment of Icelandic killer whales to relatedness-based clusters indicated limited gene flow was maintained through Icelandic 'mixed-diet' whales when herring-mediated connectivity was diminished. Thus, conservation of dietary variation within this metapopulation is critical to ensure genetic health. Our study highlights the role of resource dynamics and foraging ecology in shaping population structure and emphasises the need for transnational management of this widespread migratory species and its prey.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".