Population dynamics in a long‐lived seabird: I. Impact of breeding activity on survival and breeding probability in unbanded king penguins
Bibliographic record
Abstract
Understanding the trade-off between current reproductive effort, future survival and future breeding attempts is crucial for demographic analyses and life history studies. We investigated this trade-off in a population of king penguins (Aptenodytes patagonicus) marked individually with transponders using multistate capture-recapture models. This colonial seabird species has a low annual proportion of non-breeders (13%), despite a breeding cycle which lasts over 1 year. To draw inferences about the consequences of non-breeding, we tested for an effect of reproductive activity on survival and on the probability of subsequent breeding. We found that birds non-breeding in year t show the same survival rate as breeders (two-states analysis: breeding and non-breeding). However, breeders had a lower probability of breeding again the following year. This negative phenotypic correlation suggests the existence of reproductive costs affecting future breeding probability, but it might also be strengthened by late arrival for courtship in year t. A three-state analysis including breeding success revealed that failed breeders in year t have a lower probability to reproduce successfully in year t + 1 than non-breeders in year t, providing some evidence for the existence of reproductive costs. Moreover, successful breeders showed higher survival probability. This positive phenotypic correlation between current reproduction and subsequent survival supports the hypothesis of an heterogeneity in individual quality. Males breeding in year t had a lower probability to breed again in year t + 1 than females, suggesting higher reproductive costs for this sex. Such additional costs might be due to higher male parental investment in the final phase of chick-rearing, which also delays the arrival of males in year t + 1, and decreases their breeding probability. Our study is the first to explore the breeding biology and the demography of penguins without the disturbance of flipper-bands.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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) | 0.000 | 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 teacher head, 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".