Across the North Pacific, dietary-induced stress of breeding rhinoceros auklets increases with high summer Pacific Decadal Oscillation index
Bibliographic record
Abstract
Multi-colony studies of breeding seabirds may provide insights into the mechanistic links between large-scale climate variability and local changes in prey availability. In the North Pacific, the Pacific Decadal Oscillation (PDO) is a dominant climate index characterized by contrasting patterns in sea surface temperature between the western and eastern North Pacific. To examine how inter-annual variability in the PDO affects rhinoceros auklets Cerorhinca monocerata across the North Pacific, we measured inter-annual changes in nutritional stress (as reflected in plasma levels of corticosterone) of adults breeding on 5 colonies (2 and 3 colonies from the western and eastern Pacific, respectively). We also examined concurrent changes in mass and energy content of food loads delivered to chicks. We found that higher summer PDO values were associated with increased corticosterone levels and lower mass and energy contents of the food loads in both the western and eastern North Pacific colonies. Results indicated that oceanographic conditions during higher PDO values induced local changes in forage fish communities, leading to reduced prey availability, which, in turn, increased the nutritional stress of breeding birds. We conclude that the higher summer PDO index in recent years was associated with food-poor conditions for breeding rhinoceros auklets across their reproductive range, and prolonged periods of high summer PDO may be detrimental to the populations of this seabird species. Our results highlight the complexity of the mechanisms of how large-scale climate variability affects seabirds with a large geographical distribution.
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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 | 0.000 | 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".