Stable isotope evidence of diverse species-specific and individual wintering strategies in seabirds
Bibliographic record
Abstract
Although there is increasing evidence that climatic variations during the non-breeding season shape population dynamics of seabirds, most aspects of their winter distribution and ecology remain essentially unknown. We used stable isotope signatures in feathers to infer and compare the moulting (wintering) habitat of subantarctic petrels breeding at two distant localities (South Georgia and Kerguelen). Petrels showed species-specific wintering habitat preferences, with a similar pattern of latitudinal segregation for all but one taxon. At both localities, delta13C values indicated that blue petrels (Halobaena caerulea) moult in Antarctic waters, South Georgian diving petrels (Pelecanoides georgicus) in the vicinity of the archipelagos and/or in the Polar Frontal Zone and Antarctic prions (Pachyptila desolata) in warmer waters. In contrast, common diving petrels (Pelecanoides urinatrix) showed divergent strategies, with low and high intrapopulation variation at South Georgia and Kerguelen, respectively. Birds from Kerguelen dispersed over a much wider range of habitats, from coastal to oceanic waters and from Antarctica to the subtropics, whereas those from South Georgia wintered mainly in waters around the archipelago. This study is the first to show such striking between-population heterogeneity in individual wintering strategies, which could have important implications for likely demographic responses to environmental perturbation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".