Otolith‐inferred patterns of marine migration frequency in <scp>Nunavik Arctic</scp> charr
Bibliographic record
Abstract
Abstract Alternative migratory tactics in salmonids reflect the large observed interindividual variation in spatial behaviour which may range from strict freshwater residency to uninterrupted anadromy. In Salvelinus, sea migrations are performed during the ice‐free period as freshwater overwintering is thought to be obligatory due to physiological constraints. As a result, individuals can either migrate the next spring or remain in freshwater, as anadromy is generally considered facultative. In Arctic charr (Salvelinus alpinus), skipped migrations are known to occur, but limited data are available regarding their frequencies within and among populations. Here, the authors used an otolith microchemistry approach relying on strontium (88Sr) to infer movements between freshwater and marine habitats, and annual oscillations in zinc (64Zn) to help with age identification. They determined the age‐at‐first‐migration and the occurrence of subsequent annual migrations in two Nunavik Arctic charr populations sampled in Deception Bay (Salluit) and river systems linked to Hopes Advance Bay (Aupaluk), northern Québec, Canada. The mode for age‐at‐first‐migration was 4+ for both populations, although it exhibited large variation (range: 0+ to 8+). Skipped migrations constituted a rare event, as 97.7% and 95.6% of the examined Arctic charr at Salluit (n = 43, mean age = 10.3 ± 2.0 years) and Aupaluk (n = 45, mean age = 6.0 ± 1.9 years), respectively, were found to have performed uninterrupted annual migrations after initiation of the behaviour. The consistency of the annual migrations suggests that the tactic is sufficiently fitness rewarding to be maintained under current environmental conditions. From a fisheries management perspective, these repeated migrations combined with low site fidelity in this species may lead to large interannual variations in abundance at the local scale, which may represent a challenge for monitoring Arctic charr demographics on a river‐by‐river basis.
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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 | 0.001 |
| 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".