Salmon Louse Infestation Impairs the Long‐Term Survival of Sea‐Run Brown Trout
Bibliographic record
Abstract
Anadromous salmonids, including sea-run brown trout, are exposed to ectoparasitic salmon lice during their sea migrations. The development of intensive aquaculture in coastal areas has promoted louse epidemics by substantially increasing the number of hosts available to the parasite. We employed a mark-recapture study involving large-scale traps to capture and PIT-tag 676 wild sea-trout during their early marine migration in spring 2020 and 2021. Each trout was examined for lice, tagged with passive integrated transponders (PIT), and monitored for subsequent survival using a PIT antenna system installed at the river Yndesdalsvassdraget. Using a Cormack-Jolly-Seber capture recapture model of individual re-detections the subsequent years, we found a significant negative correlation between lice per gram of fish weight and the survival probability. Increasing lice load from 0 to 1 louse per gram fish reduced the survival probability by approximately 73% in 2020 and 58% in 2021. This is among the first field studies to demonstrate a statistically significant association between individual survival of brown trout and their parasite loads in the wild. Our findings demonstrate the critical need for robust marine spatial planning and lice management in coastal fisheries. Effective control of lice loads is essential to mitigate their deleterious effects on brown trout, ensuring sustainable fish populations and maintaining ecological balance in regions affected by aquaculture.
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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 | 0.000 |
| 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) | 0.001 | 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".