The co-distribution of Arctic cod and its seabird predators across the marginal ice zone in Baffin Bay
Bibliographic record
Abstract
Arctic cod (Boreogadus saida) is the dominant pelagic fish in Arctic seas and a staple food of many arctic predators including several seabird species. Marginal ice zones are known as important feeding locations for seabirds. The hypothesis that thick-billed murre (Uria lomvia), northern fulmar (Fulmarus glacialis) and black-legged kittiwake (Rissa tridactyla) congregate in areas of high Arctic cod food resource and low ice concentration was tested at different spatial scales. Arctic cod biomass was estimated by hydroacoustics as a resource proxy, and seabirds were counted and sampled for stomach analysis along eight longitudinal transects across the marginal ice zone in southern Baffin Bay in June–July 2016. With increasing length, the epipelagic age-0 Arctic cod migrated from open waters to ice-covered areas. Subsequently, age-1 and age-2 Arctic cod tended to concentrate in a subsurface layer (40–100 m) within the epipelagic layer. Arctic cod 5.7–16.1 cm long (late age-0 to age-5) were the main fish prey of the three seabird species, which preferentially captured age-1 cod (6–11.5 cm). At large spatial scale (western versus eastern Baffin Bay), thick-billed murre, northern fulmar and their Arctic cod resource proxy were generally more abundant on the western ice-covered side of Baffin Bay. No clear spatial match was found, however, when comparing seabird abundances and their food-resource proxy in different ice concentrations across the marginal ice zone or at small scale (5 km). At medium scale (12.5 km), only murre density was influenced positively by its Arctic cod resource. A lack of schooling behavior and a successful strategy to avoid predation by hiding under the ice could explain the absence of any strong spatial match between Arctic cod and its seabird predators at these different scales.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".