Seabird density and predation on Arctic cod (Boreogadus saida) in Allen Bay in 2010
Bibliographic record
Abstract
Seabirds feed heavily on Arctic cod Boreogadus saida during the summer in the Canadian Arctic but little is known of the interactions among birds while foraging and the factors that drive feeding behaviour. The objective of this study was to describe the relationship between seabirds and Arctic cod in a productive feeding area distant from breeding colonies. Transect surveys were completed using standardized count protocols to determine the density of seabirds in Allen Bay, Cornwallis Island, Nunavut. Shore-based observation sites determined seabird foraging behaviour associated with the presence of schools and environmental variables. The density of birds (156 bird/km**2) was high compared to that of other locations in the Canadian Arctic. Several bird species were more active early in the morning and with winds from the south, possibly due to an increase in Arctic cod feeding on zooplankton at the surface. Northern fulmars Fulmarus glacialis and black-legged kittiwakes Rissa tridactyla captured Arctic cod directly from the water; however, they lost nearly 25% of captures to glaucous gulls Larus hyperboreus and parasitic jaegers Stercorarius parasiticus. These kleptoparasitic seabirds benefited the most in Allen Bay obtaining as much as 8 times more Arctic cod than species capturing cod directly. Northern fulmars captured 3 times more Arctic cod from schools, and black-legged kittiwakes captured similar proportions of schooling and non-schooling cod. We conclude that non-schooling Arctic cod are as important as schooling cod as an energy source for seabirds in nearshore areas, such as Allen Bay, during the summer.
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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".