Binary dietary responses of northern gannets Sula bassana indicate changing food web and oceanographic conditions
Bibliographic record
Abstract
Interactions between seabirds and their prey are shaped largely by the dynamics of the marine ecosystems in which they are embedded. Physical oceanographic processes can drive the distributions of ectothermic and planktonic prey and hence their availability to marine birds. Owing to the complex nature of these processes and interactions, the signal-to-noise ratios of avian indicators of prey conditions are variable, often low and further degraded (buffered) by seabird behaviour and life-history features. Cairns (1987, Biol Oceanogr 5:261–271) detailed seabird responses operating over a range of temporal scales to variation in food supplies, and suggested that interval relationships might be developed between avian responses and environmental variation. While this may be possible in some instances, it appears unrealistic in most instances to expect interval relationships between seabird responses and prey conditions that are often nonlinearly related. The present paper focuses on binary data (e.g. breeding success versus failure) derived from seabirds that can provide robust information about major shifts in prey and oceanographic conditions and that are particularly informative when accumulated over decadal and large ocean scales. Inter-annual and decadal variations in specific and nominally categorized (warm- versus cold-water) prey landings of northern gannets Sula bassana at a large oceanic colony in the NW Atlantic reflect shifts in pelagic food webs induced by changes in regional sea surface temperature. Binary patterns emphasize decadal shifts in food webs and yield predictive indication of systemic change.
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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".