Marine migration, thermal habitat use and feeding habits of Arctic charr ( <i>Salvelinus alpinus</i> ) in SW Greenland
Bibliographic record
Abstract
Climate change is altering northern coastal aquatic habitats, especially in fjords. Data on current ecosystem structure and biodiversity in many northern fjord and coastal ecosystems, especially for Greenland, are lacking. We used acoustic telemetry combined with stable isotope analyses in a southwest Greenland fjord to investigate marine migrations, marine, and freshwater thermal habitat use, and the marine feeding habits of 80 acoustically tagged Arctic charr over one year. During summer, most Arctic charr occupied the inner fjord. Models of Arctic charr thermal habitat use suggested higher experienced water temperatures in the inner compared to outer fjord (estimated 1.59 °C difference) during tagged charr mean 70-day (SD = 14 days) residencies. During February and March, non-migratory individuals used warmer waters (+0.56 °C higher) than fish that ultimately migrated to sea, suggesting that over-wintering habitat use patterns influenced migration tactics. Stable isotope mixing model analysis indicated that Arctic charr fed mainly on capelin, marine gammarids, and sandlance. The results provide a contemporary baseline for assessing predictions of potential changes in the ecology of Arctic charr in SW Greenland fjords.
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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) | 0.000 | 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".