Sex interacts with fledge date to influence dispersal probability in <i>Fratercula arctica</i> (Atlantic Puffin)
Bibliographic record
Abstract
Abstract Dispersal is a fundamental life-history component of species, affecting ecological and evolutionary processes. Sex-specific patterns of dispersal may arise to alleviate the effects of inbreeding, kin competition, or limited resources, and are common in many taxa. We examined sex-biased dispersal of Fratercula arctica (Atlantic Puffin) hatched on Machias Seal Island to 4 breeding colonies in the Gulf of Maine using mark–recapture data. We evaluated if one sex disperses more frequently, if there is a sex bias in the breeding colony choice of dispersed F. arctica, and if sex interacts with other individual factors to influence dispersal. There was no significant difference in the frequency that female and male F. arctica dispersed, or the breeding colony they dispersed to. However, we found that with increasing fledge date, female F. arctica were more likely to disperse and males were less likely to disperse, with this relationship being weaker for male F. arctica. Fledge date was unrelated to body condition, and so other rearing conditions or broader environmental constraints reflected by fledge date may be more influential for females when making dispersal decisions. Our results suggest the smaller Gulf of Maine colonies receive a balanced sex ratio of immigrants from Machias Seal Island, which improves our understanding of metapopulation dynamics. The frequency of dispersal differed among years, and was not fully explained by sex or fledge date, highlighting the need for further research to understand which factors influence F. arctica dispersal.
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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 | 0.000 |
| 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".