Relating Demographic Performance to Breeding-Site Location in the King Penguin
Bibliographic record
Abstract
In colonial species, it is often assumed that locations in the center of the colony are of highest quality and provide highest breeding success. We tested this prediction, known as the “central-periphery model,” in a King Penguin colony in the subantarctic Crozet Archipelago. Breeding activity and survival of 150 penguins, ftted with transponder tags, were monitored over an entire breeding season. Among these 150 bird s, 50 bred on t he slope at the upper periphery of the colony, where the rates of predation and parasitism by ticks were high. fifty birds bred in the center of the colony, where rates of predation and tick parasitism were low, and 50 bred at the lower end of the colony, where the rate of tick parasitism was low but predation and fooding were important risks. We predicted that the center of the colony should provide the safest breeding place and consequently be characterized by the highest breeding success and be used by the highest-quality individuals. Yet we found that penguins breeding in the center of the colony had the same breeding success as those at both peripheral locations. In addition, penguins breeding on the upper slope had a higher survival rate than penguins breeding at the center or bottom of the slope and were likely of higher quality. Our study does not support the central-periphery model and emphasizes the complexity behind the relationships among breeding site, breeding success, and individual quality.
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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 | 0.002 |
| 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".