Diving of Great Shearwaters (Puffinus gravis) in Cold and Warm Water Regions of the South Atlantic Ocean
Bibliographic record
Abstract
BACKGROUND: Among the most widespread seabirds in the world, shearwaters of the genus Puffinus are also some of the deepest diving members of the Procellariiformes. Maximum diving depths are known for several Puffinus species, but dive depths or diving behaviour have never been recorded for great shearwaters (P. gravis), the largest member of this genus. This study reports the first high sampling rate (2 s) of depth and diving behaviour for Puffinus shearwaters. METHODOLOGY/PRINCIPAL FINDINGS: Time-depth recorders (TDRs) were deployed on two female great shearwaters nesting on Inaccessible Island in the South Atlantic Ocean, recording 10 consecutive days of diving activity. Remote sensing imagery and movement patterns of 8 males tracked by satellite telemetry over the same period were used to identify probable foraging areas used by TDR-equipped females. The deepest and longest dive was to 18.9 m and lasted 40 s, but most (>50%) dives were <2 m deep. Diving was most frequent near dawn and dusk, with <0.5% of dives occurring at night. The two individuals foraged in contrasting oceanographic conditions, one in cold (8 to 10°C) water of the Sub-Antarctic Front, likely 1000 km south of the breeding colony, and the other in warmer (10 to 16°C) water of the Sub-tropical Frontal Zone, at the same latitude as the colony, possibly on the Patagonian Shelf, 4000 km away. The cold water bird spent fewer days commuting, conducted four times as many dives as the warm water bird, dived deeper on average, and had a greater proportion of bottom time during dives. CONCLUSIONS/SIGNIFICANCE: General patterns of diving activity were consistent with those of other shearwaters foraging in cold and warm water habitats. Great shearwaters are likely adapted to forage in a wide range of oceanographic conditions, foraging mostly with shallow dives but capable of deep diving.
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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 | 0.000 |
| 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".