Identifying mechanisms of genetic differentiation among populations in vagile species: historical factors dominate genetic differentiation in seabirds
Bibliographic record
Abstract
Elucidating the factors underlying the origin and maintenance of genetic variation among populations is crucial for our understanding of their ecology and evolution, and also to help identify conservation priorities. While intrinsic movement has been hypothesized as the major determinant of population genetic structuring in abundant vagile species, growing evidence indicates that vagility does not always predict genetic differentiation. However, identifying the determinants of genetic structuring can be challenging, and these are largely unknown for most vagile species. Although, in principle, levels of gene flow can be inferred from neutral allele frequency divergence among populations, underlying assumptions may be unrealistic. Moreover, molecular studies have suggested that contemporary gene flow has often not overridden historical influences on population genetic structure, which indicates potential inadequacies of any interpretations that fail to consider the influence of history in shaping that structure. This exhaustive review of the theoretical and empirical literature investigates the determinants of population genetic differentiation using seabirds as a model system for vagile taxa. Seabirds provide a tractable group within which to identify the determinants of genetic differentiation, given their widespread distribution in marine habitats and an abundance of ecological and genetic studies conducted on this group. Herein we evaluate mitochondrial DNA (mtDNA) variation in 73 seabird species. Lack of mutation-drift equilibrium observed in 19% of species coincided with lower estimates of genetic differentiation, suggesting that dynamic demographic histories can often lead to erroneous interpretations of contemporary gene flow, even in vagile species. Presence of land across the species sampling range, or sampling of breeding colonies representing ice-free Pleistocene refuge zones, appear to be associated with genetic differentiation in Tropical and Southern Temperate species, respectively, indicating that long-term barriers and persistence of populations are important for their genetic structuring. Conversely, biotic factors commonly considered to influence population genetic structure, such as spatial segregation during foraging, were inconsistently associated with population genetic differentiation. In light of these results, we recommend that genetic studies should consider potential historical events when identifying determinants of genetic differentiation among populations to avoid overestimating the role of contemporary factors, even for highly vagile taxa.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".