Small‐scale dispersal and survival in a long‐lived seabird, the wandering albatross
Bibliographic record
Abstract
1. Dispersal is a fundamental but still poorly known process in population dynamics and several hypotheses have been proposed to explain its patterns. We studied natal and breeding dispersal and survival in a long-lived seabird, the wandering albatross (Diomedea exulans L.), and examined several hypotheses concerning dispersal patterns in birds. 2. We applied multi-state capture-recapture models to a 36-year data set (1969-2004) collected at three albatross colonies on Ile de Possession, Crozet Islands. Because the species has biennial reproduction, we introduced unobservable states in the model to account for the absence of individuals in those years. 3. Adults were highly faithful to their nesting colony but colony fidelity, as well as survival rate, differed slightly among colonies (fidelity ranged from 0.957 to 0.977). Breeding fidelity was highest in the colony where survival was lowest and individuals were not more likely to change colony following a failed breeding attempt than after a successful one. The colony that attracted most dispersers had the lowest density of nesting birds. 4. Philopatry (the probability that young return to breed at a birth site) was generally high but variable among colonies (ranging from 0.70 to 0.92), and survival of young differed little. Philopatry was highest in the largest colony, where the availability of potential mates was presumably greatest. However, among dispersing individuals, the colony that had the lowest density of nesting individuals, not the largest colony, attracted the most recruits. 5. Although size of the colony influenced the decision to stay or to leave in young, density was most influential in the selection of a new colony among both adult and young dispersers. Our results support the hypothesis that philopatry is the strategy favoured by most recruits and that conspecific attraction can explain variation in the level of philopatry among colonies but not settlement patterns among dispersing individuals.
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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".