Population genetic structure and gene flow of Adélie penguins (<i>Pygoscelis adeliae</i>) breeding throughout the western Antarctic Peninsula
Bibliographic record
Abstract
Abstract Adélie penguins (Pygoscelis adeliae) are responding to ocean–climate variability throughout the marine ecosystem of the western Antarctic Peninsula (WAP) where some breeding colonies have declined by 80%. Nuclear and mitochondrial DNA (mtDNA) markers were used to understand historical population genetic structure and gene flow given relatively recent and continuing reductions in sea ice habitats and changes in numbers of breeding adults at colonies throughout the WAP. Genetic diversity, spatial genetic structure, genetic signatures of fluctuations in population demography and gene flow were assessed in four regional Adélie penguin colonies. The analyses indicated little genetic structure overall based on bi-parentally inherited microsatellite markers (FST=-0.006–0.004). No significant variance was observed in overall haplotype frequency (mtDNAΦST=0.017;P=0.112). Some comparisons with Charcot Island were significant, suggestive of female-biased philopatry. Estimates of gene flow based on a two-population coalescent model were asymmetrical from the species’ regional core to its northern range. Breeding Adélie penguins of the WAP are a panmictic population and hold adequate genetic diversity and dispersal capacity to be resilient to environmental change.
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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".