Data from: Sympatric population divergence within a highly pelagic seabird species complex (Hydrobates spp.)
Bibliographic record
Abstract
Both physical and non-physical barriers can restrict gene flow among seabird populations. Understanding the relative importance of non-physical barriers, such as breeding phenology, is key to understanding seabird biodiversity. We investigated drivers of diversification in the Leach’s storm-petrel species complex (Hydrobates spp.) by examining population genetic structure across its range. Variation in the mitochondrial control region and six microsatellite loci was assayed in birds sampled from breeding colonies throughout the North Atlantic and North Pacific (H. leucorhoa leucorhoa), as well as from San Benito Islands (H. l. chapmani), and two seasonal populations in Guadalupe (summer breeding H. socorroensis and winter breeding H. cheimomnestes), Mexico. Weak but significant differentiation was found between populations of H. l. leucorhoa breeding in the Atlantic versus North Pacific, as well as between H. l. chapmani and H. l. leucorhoa, and between H. socorroensis and H. cheimomnestes within Guadalupe. In contrast, strong differentiation in both mitochondrial DNA and microsatellites was found between H. leucorhoa and both H. socorroensis and H. cheimomnestes. Phylogenetic reconstruction suggested the Guadalupe seasonal breeding populations are sister taxa, at least in their mitochondrial DNA. Non-physical barriers to gene flow appear to be more important than physical barriers in driving divergence within the Leach’s storm-petrel species complex. In particular, allochronic speciation may have occurred between the seasonal populations within Guadalupe. Further work should include higher resolution sequencing to confirm results, and an increased sampling effort, particularly within the California area, to fully resolve the relationship between H. l. leucorhoa and H. l. chapmani.
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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 | 0.001 | 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) | 0.006 | 0.001 |
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".