Fitness-related Consequences of Relaying in an Arctic Seabird: Survival of Offspring to Recruitment Age
Bibliographic record
Abstract
Seasonal declines in rates of renesting following clutch loss are common features of avian breeding, and are generally thought to reflect underlying seasonal declines in food availability that lower survival prospects for late-season offspring. However, in Thick-billed Murres (Uria lomvia), long-lived Arctic seabirds that lays a single-egg clutch, previous research has shown that early laying females will continue to relay until late in the laying period. Moreover, hatching success is similar between first and replacement attempts, as are nestling growth and survival, when parental quality is controlled. I compared survival between departure from the breeding site and recruitment age (4–5 years) for Thick-billed Murres that hatched from first and replacement eggs, but that were raised by parents that laid their first eggs early in the season. Replacement-egg offspring hatched and departed the colony about three weeks later than did first-egg offspring, but despite that, they were no less likely to survive to recruitment age. That result indicates that the potential fitness payoff from a replacement egg is similar to that from a first egg for the more capable members of the population. I suggest that an adequate and predictable late-season food supply ultimately underlies the considerable relaying capacity exhibited by Thick-billed Murres.
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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".