Assessing the potential for Atlantic salmon (<i>Salmo salar</i>) colonization of Nunavik’s Arctic and subarctic rivers by 2070–2100
Bibliographic record
Abstract
In Nunavik, Québec, Canada, Atlantic salmon ( Salmo salar) populations reach their northern limit in four rivers of southern Ungava Bay. With projected river warming from climate change, this study assesses the potential for Atlantic salmon to colonize new rivers in Nunavik by modelling water temperatures and evaluating river accessibility. Migration barriers were identified with a literature review, topographic data, and satellite imagery. Water temperatures were modelled with a generalized additive model using ERA5-Land air temperature, observed daily mean temperatures, and water surface temperature estimated from Landsat imagery. Our projections indicate an average increase of the rivers mean summer temperatures of 1.2–2.7 °C by the end of the century, enhancing thermal conditions in current salmon rivers with more days with optimal growth temperatures (16–20 °C) while still having limited days with thermal stress (>22 °C). By 2100, other Ungava Bay rivers may be colonized, as most are accessible and expected to reach more suitable temperatures. However, Nunavik’s northernmost rivers would remain too cold and colonization of the Hudson Bay watershed appears less likely due to the inaccessibility of most rivers and their distance from established anadromous populations.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".