Individual differences in migratory behavior shape population genetic structure and microhabitat choice in sympatric blackcaps (<i>Sylvia atricapilla</i>)
Bibliographic record
Abstract
In migratory birds, traits such as orientation and distance are known to have a strong genetic background, and they often exhibit considerable within-population variation. How this variation relates to evolutionary responses to ongoing selection is unknown because the underlying mechanisms that translate environmental changes into population genetic changes are unclear. We show that within-population genetic structure in southern German blackcaps (Sylvia atricapilla) is related to individual differences in migratory behavior. Our 3-year study revealed a positive correlation between individual migratory origins, denoted via isotope (δ (2)H) values, and genetic distances. Genetic diversity and admixture differed not only across a recently established migratory polymorphism with NW- and SW-migrating birds but also across δ (2)H clusters within the same migratory route. Our results suggest assortment based on individual migratory origins which would facilitate evolutionary responses. We scrutinized arrival times and microhabitat choice as potential mechanisms mediating between individual variation in migratory behavior and assortment. We found significant support that microhabitat choice, rather than timing of arrival, is associated with individual variation in migratory origins. Moreover, examining genetic diversity across the migratory divide, we found migrants following the NW route to be genetically more distinct from each other compared with migrants following the traditional SW route. Our study suggests that migratory behavior shapes population genetic structure in blackcaps not only across the migratory divide but also on an individual level independent of the divide. Thus, within-population variation in migratory behavior might play an important role in translating environmental change into genetic 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".