Scalimetry and otolith chemistry confirm the occurrence of a migratory contingent of estuary-growth Atlantic salmon (<i>Salmo salar</i>) in Ungava Bay (Nunavik, Quebec)
Bibliographic record
Abstract
Abstract Salmon populations exhibit a variety of migratory behaviours, generally residing in fresh water or migrating to the sea. It is important for the management and conservation of salmon populations that migratory behaviour is well understood, particularly in the context of climate change and exploitation. Scalimetry of Atlantic salmon (Salmo salar) at the northern edge of its North American range has revealed unusual migratory patterns. In the Ungava Bay region, some salmon described as estuary-growth spend summers in estuaries and winters in fresh water, whereas others from the same river exhibit typical marine anadromy or fresh-water residency. This study aimed to confirm and estimate the occurrence of estuary-growth Atlantic salmon using scalimetry and otolith chemistry. We compared scalimetry and otolith chemical transects of 86 salmon, 21 collected from the Koksoak River hydrographic network in Nunavik and 65 salmons from 12 hydrographic networks in southern Quebec. Otolith concentrations of Zn, Mg, Sr, and Ba detected the age and migrations of individual Atlantic salmon throughout their lifetime. The life history inferred by both methods matched very well (98.8% matching), confirming the effectiveness and reliability of scalimetry. This information strengthens the relevance of using this non-lethal and accessible method to monitor this iconic species. Additionally, our study confirmed the occurrence of salmon making estuarine migrations in the Ungava Bay region. This atypical migratory behaviour accounted for 22% and 74% of the Atlantic salmon sampled in the aux Mélèzes River in 2018 and the du Gué River in 2019, respectively.
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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".