Spatiotemporal variation in Arctic char (<i>Salvelinus alpinus</i>) foraging ecology along western Hudson Bay, Nunavut, Canada
Bibliographic record
Abstract
Climate-induced alterations to Arctic sea ice dynamics are influencing resource availability and distribution, and in turn, restructuring Arctic marine food webs, which can be monitored by studying the foraging ecology of opportunistic predators such as anadromous Arctic char ( Salvelinus alpinus). Despite its subsistence and economic importance, Arctic char foraging ecology across their range, particularly in relation to sea ice dynamics, remains understudied. Here, we investigate the foraging ecology of Arctic char near the communities of Rankin Inlet and Naujaat along western Hudson Bay, using stomach contents, stable isotopes (δ13C and δ15N), and highly branched isoprenoids. Spatiotemporal variation in diet was observed in relation to sea ice dynamics, whereby Arctic char in Rankin Inlet consumed more fish and phytoplankton-based carbon, occupied a higher trophic position, and displayed a similar isotopic niche breadth compared to Naujaat. The plastic foraging ecology observed highlights the species' adaptability to inter-annual variability, although long-term resilience in response to climate-driven changes remains unknown.
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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 | 0.000 |
| 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".