Reproductive consequences of natal dispersal in a highly philopatric seabird
Bibliographic record
Abstract
Natal and breeding dispersal have a major impact on gene flow and population structure. We examined the consequences of natal dispersal on the reproductive success (proportion of pairs rearing chicks) of colonial-breeding Thick-billed murres (Uria lomvia). Reproductive success increased with distance dispersed for the first and second breeding attempt. The increase in breeding success leveled off at natal dispersal distances above 7 m. Our results were consistent with the idea that the relationship between dispersal and reproductive success is caused by site availability and mate choice as birds willing to disperse farther had a greater choice of potential sites and mates. This hypothesis was supported by the fact that birds dispersing farther were more likely to pair with an experienced breeder, which increases the likelihood of breeding success for young breeders. Explanations for increasing breeding success with increased dispersal based on inbreeding effects were unlikely because most breeding failures were caused by egg loss rather than infertility or nestling death. However, we could not explain why >50% of birds return within 3 m of the natal site, despite having an up to 50% lower reproductive success than birds dispersing 7 m or more.
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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 | 0.000 | 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".