Exploring individual quality: basal metabolic rate and reproductive performance in storm-petrels
Bibliographic record
Abstract
Despite evidence that some individuals achieve both superior reproductive performance and high survivorship, the factors underlying variation in individual quality are not well understood. The compensation and increased-intake hypotheses predict that basal metabolic rate (BMR) influences reproductive performance; if so, variation in BMR may be related to differences in individual quality. We evaluated whether BMR measured during the incubation period provides a proximate explanation for variation in individual quality by measuring the BMRs and reproductive performance of Leach's storm-petrels (Oceanodroma leucorhoa) breeding on Kent Island, New Brunswick, Canada, during 2000 and 2001. We statistically controlled for internal (body mass, breeding age, sex) and external (year, date, time of day) effects on BMR. We found that males with relatively low BMRs hatched their eggs earlier in the season and that their chicks' wing growth rates were faster compared to males with relatively high BMRs. Conversely, BMR was not related to egg volume, hatching date, or chick growth rate for females or to lifetime (≤23 years) hatching success for either sex. Thus, for males but not for females, our results support the compensation hypothesis. This hypothesis predicts that animals with low BMRs will achieve better reproductive performance than animals with high BMRs because they have lower self-maintenance costs and therefore can apportion more energy to reproduction. These results provide evidence that intraspecific variation in reproductive performance is related to BMR and suggest that BMR may influence individual quality in males.
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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".