Prevalence and recurrence of escaped farmed Atlantic salmon (Salmo salar) in eastern North American rivers
Bibliographic record
Abstract
Knowledge of the prevalence of escaped farmed fishes in the wild is an essential first step to assessing the risk resulting from interactions between farmed and wild fishes. This is especially important in eastern North America, where Atlantic salmon ( Salmo salar ) aquaculture occurs near wild Atlantic salmon rivers and where many wild salmon populations are severely depressed. Here, we review the literature on the incidence of escaped farmed salmon in eastern North American rivers, for which there has been no comprehensive compilation to date. Escaped farmed salmon have been found in 54 of 62 (87%) rivers investigated within a 300 km radius of the aquaculture industry since 1984, including 11 rivers that contain endangered salmon populations. Averaged among all investigations, the proportional representation of farmed salmon among adults entering the rivers from the sea was 9.2% (range 0% to 100%). Where data were sufficient to examine temporal trends, farmed salmon proportions varied considerably over time, suggesting that escape events are episodic in nature. We conclude that escaped farmed salmon are sufficiently prevalent in eastern North American rivers to pose a potentially serious risk to the persistence of wild salmon populations, especially in those rivers that are adjacent to existing aquaculture sites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| 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".