A review and risk analysis on potential impacts of riverine recreational activities on Atlantic Salmon (<i>Salmo salar</i>) in eastern Canada
Bibliographic record
Abstract
Atlantic salmon populations face a number of significant, human-driven threats such as overfishing and thermal stress from anthropogenically-accelerated climate change. A considerable body of research has been devoted to such large-scale threats as well as catch-and-release fishing, while the potential impacts of other recreational activities on Atlantic salmon while in rivers have been largely overlooked. Here, we undertook a systematic literature review of the effects that recreational activities (excluding direct impacts of catch-and-release angling) might have on the welfare and survival of Atlantic salmon in riverine systems at all relevant life history stages. Examples of relevant activities examined here include swimming, all-terrain vehicle (ATV) use, and underwater photography. We also performed a relative risk assessment of such activities based on the likelihoods of their occurrence and the severities of their potential impacts. For the most part, the impacts of non-angling recreational activities on Atlantic salmon are likely widespread but largely temporary. Redds, eggs, and juveniles were generally found to be more susceptible to most threats than smolts and adults. However, some activities have significant destructive potential such as ATV use in or around spawning habitats. Significant risks also remain concerning pathogen and invasive species transfer via angling gear, waders, canoes, and other equipment that may be moved across systems without proper cleaning. Although we focused primarily on risks to native Atlantic salmon populations in eastern Canada, the risk assessment framework developed here is broadly applicable and easily adaptable for management in other contexts and jurisdictions with populations of riverine Atlantic salmon and potentially other migratory salmonids too.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".