Wintering strategies of two king penguin populations of the Southern Indian Ocean
Bibliographic record
Abstract
The king penguin Aptenodytes patagonicus is an important model species of the Southern Ocean. While there is extensive knowledge on the foraging movement of this species during the summer in the early chick-provisioning period, little information is available for the winter period. To fill this gap, we tracked 13 individuals during the winter from 2 neighboring populations of the Southern Indian Ocean, namely the Kerguelen and the Crozet Archipelagos, and examined penguin locations with respect to remote sensing data. Tracked penguins from Kerguelen mostly headed east of the archipelago, while those from Crozet islands headed southwest. This resulted in contrasting latitudes used between the 2 wintering locations. The different directions taken possibly result from the distinct oceanic features around the 2 islands: at Kerguelen, extensive spring blooms transported east of the island might sustain prey well until the winter, offering favorable conditions for penguins. At Crozet, blooms are reduced in intensity and penguins might instead head south to benefit from the better foraging conditions near the sea ice. Such distinct foraging distributions relative to the 2 archipelagos are consistent with the at-sea distribution of other penguin species (e.g. Eudyptes spp.) breeding in the same localities. We highlight 2 distinct winter foraging strategies in neighboring king penguin populations, shaped by the contrasting oceanographic conditions surrounding their breeding sites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".