Atlantic salmon in the Canadian Arctic: potential dispersal, establishment, and interaction with Arctic char
Bibliographic record
Abstract
Abstract As the Arctic rapidly warms, sub-Arctic species such as the Atlantic salmon (Salmo salar) are expected to shift their distributions into the Arctic, potentially facilitating interaction with native Arctic species. Here, the possible dispersal and establishment of Atlantic salmon are considered in Canadian Arctic fresh waters containing Arctic char (Salvelinus alpinus), an important subsistence fish species. Available information about Atlantic salmon harvests in the Canadian Arctic was summarized to assess dispersal potential. Review and synthesis of published data were used to assess the suitability of the Canadian Arctic for Atlantic salmon colonization and the interaction potential of Atlantic salmon and Arctic char in Canadian Arctic fresh waters. Establishment of Atlantic salmon in Canadian Arctic thermal habitat was deemed possible, especially with rising freshwater temperatures. Overlap in habitat preferences and life cycles of Atlantic salmon and Arctic char, along with data on resource partitioning in sympatry, implied a possibility for interaction at multiple freshwater life stages. However, many data gaps were identified that inhibit further discussion and analysis. These considerations highlight the need for further study of these two culturally, ecologically, and economically important fish species, to address growing concerns and inform future management efforts.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 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".