Mechanisms of population differentiation in seabirds
Bibliographic record
Abstract
Despite recent advances in population genetic theory and empirical research, the extent of genetic differentiation among natural populations of animals remains difficult to predict. We reviewed studies of geographic variation in mitochondrial DNA in seabirds to test the importance of various factors in generating population genetic and phylogeographic structure. The extent of population genetic and phylogeographic structure varies extensively among species. Species fragmented by land or ice invariably exhibit population genetic structure and most also have phylogeographic structure. However, many populations (26 of 37) display genetic structure in the absence of land, suggesting that other barriers to gene flow exist. In these populations, the extent of genetic structure is best explained by nonbreeding distribution: almost all species with two or more population-specific nonbreeding areas (or seasons) have phylogeographic structure, and all species that are resident at or near breeding colonies year-round have population genetic structure. Geographic distance between colonies and foraging range appeared to have a weak influence on the extent of population genetic structure, but little evidence was found for an effect of colony dispersion or population bottlenecks. In two species (Galapagos petrel, Pterodroma phaeopygia, and Xantus's murrelet, Synthliboramphus hypoleucus), population genetic structure, and even phylogeographic structure, exist in the absence of any recognizable physical or nonphysical barrier, suggesting that other selective or behavioural processes such as philopatry may limit gene flow. Retained ancestral variation may be masking barriers to dispersal in some species, especially at high latitudes. Allopatric speciation undoubtedly occurs in this group, but reproductive isolation also appears to have evolved through founder-induced speciation, and there is strong evidence that parapatric and sympatric speciation occur. While many questions remain unanswered, results of the present review should aid conservation efforts by enabling managers to predict the extent of population differentiation in species that have not yet been studied using molecular markers, and, thus, enable the identification of management units and evolutionary significant units for conservation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".