Parasite scars: the impact of salmon lice injury on sea trout populations
Bibliographic record
Abstract
Spillback effects of the parasitic salmon louse from fish farms to wild fish are a critical environmental concern for countries with wild salmon. The ectoparasitic louse causes significant physical and physiological damage to wild salmonids that probably have long-term impacts on individuals and population dynamics. However, empirical links between injuries and abundance of lice have not been established in the wild. This study establishes a strong association between dorsal fin injuries in wild sea trout ( Salmo trutta ) and infestation with salmon lice at a marine site in Norway. We further assessed the prevalence of such injuries on sea trout returning to spawning grounds from snorkelling observations in 16 rivers in Hardangerfjord, western Norway, from 2007 to 2021. The prevalence of injuries decreased with distance from the fjord outlet, from approximately 70% in middle and outer parts to approximately 10% in the inner parts. Additionally, a negative correlation was found between sea trout population size and the proportion of the population with dorsal fin damage. The results demonstrate that salmon lice inflict high levels of injury on significant portions of sea trout populations in areas with intensive fish farming, leading to poorer population status in affected 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".