Consistent variation in individual migration strategies of brown skuas
Bibliographic record
Abstract
Seabirds show remarkable variability in migration strategies among individuals and populations. In this study, we analysed 47 migrations of 28 brown skuas Catharacta antarctica lonnbergi breeding on King George Island in the Maritime Antarctic. Brown skuas from this population used a large area during the non-breeding period north of 55S, including parts of the Patagonian Shelf, Argentine Basin and South Brazil Shelf, areas which are characterised by high levels of marine productivity. However, individual birds utilised only a subset of these areas, adopting 1 of 4 distinct migration strategies to which they were highly faithful between years, and showed high repeatability in departure and arrival dates at the breeding ground. Although they spent the majority of the non-breeding season within a particular region, almost all individuals used the same area in the late winter, exploiting its seasonal peak in productivity. Overall, these results indicate consistent individual variation in migration strategies that may reflect a combination of genetic control and individual experience, but with considerable flexibility to shift distribution in response to prevailing environmental conditions.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".