Tufted Puffins exhibit low levels of genetic differentiation among breeding colonies in North America
Bibliographic record
Abstract
Abstract Tufted Puffins (Fratercula cirrhata) are experiencing population declines in some parts of their distribution, making this a species of increased conservation interest. Genetic data will help to identify Tufted Puffin populations of conservation importance and provide an important tool for developing conservation management plans. This species is broadly distributed across the North Pacific Ocean but little is known about the extent of genetic variation and differentiation across their range. In this study, we examine mitochondrial DNA (mtDNA), 8 microsatellite loci and 1,260 single nucleotide polymorphisms (SNPs) to determine the extent of gene flow among 7 breeding colonies (Oregon to the western Aleutians) in the North American breeding range of the species and identify potential barriers to dispersal. Our results show that most breeding colonies form a single genetic cluster, and mtDNA data show substantial historical gene flow among populations. For the microsatellite dataset, all FST comparisons that include St. Lazaria, in southeast Alaska, except Oregon, which had a small sample size, were significant as were comparisons between Triangle Island and the two westernmost sampling sites of Buldir and Aiktak. For the SNP dataset, FST comparisons were low and nonsignificant, further suggesting that breeding colonies form a single panmictic population. Individuals were more closely related to individuals from the same colony, and we found a weak relationship between genetic and geographic distance. This suggests that dispersal among colonies is high, likely facilitated by an overlap in wintering ranges among colonies. The high connectivity among breeding colonies indicates that Tufted Puffins form a single conservation unit, although future genetic studies should incorporate a whole genome sequencing approach to assessing how functional genetic diversity varies across their distribution.
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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".