Trophic ecologies and dietary niches of Arctic charr (Salvelinus alpinus) and three coastal forage fishes in Frobisher Bay, Nunavut
Bibliographic record
Abstract
Abstract Here, the trophic ecology of four mid-trophic level fishes is described for an Arctic coastal marine habitat near Iqaluit, Nunavut. Arctic charr (Salvelinus alpinus), Arctic cod (Boreogadus saida), Fish Doctor (Gymnelus viridis), and sculpins (Cottidae) diet and feeding strategies were estimated using gut content; dietary niches were compared using stable isotopes (δ13C, δ15N); and relationships between diet indices and metrics of fish condition, including calorie content, were assessed. While the four taxa differed in foraging strategy, targeted prey, and the strength of associations with benthic and pelagic food web pathways, niche overlap occurred among the benthic and pelagic taxa. Pelagic Arctic charr and Arctic cod specialized in hyperbenthic amphipods and copepods, respectively, with evidence that selectivity was flexible. Fish Doctor and sculpins were benthic generalists with evidence for inter-individual and population-level specialization. Arctic charr occupied a central isotopic niche, resulting in a high probability of dietary niche overlap with the other three taxa. Fish Doctor and sculpins were likely to overlap with each other, and both had a low probability of overlap with Arctic cod. Isotopic diet indicators did not significantly explain variation in fish condition or calorie content. Findings reiterate the complex trophic ecologies that allow Arctic fish to divide resources and respond to changes in prey availability.
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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 | 0.001 | 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".