Impacts of parasites on marine survival of Atlantic salmon: a meta‐analysis
Bibliographic record
Abstract
Abstract Parasites can, in theory, have large impacts on the survival of fish populations. One method to evaluate such impacts on anadromous species is to apply manipulative field experiments in which parallel groups of antiparasitically treated and non‐treated fish are simultaneously released and then subsequently recaptured as returning adults. A systematic review and meta‐analysis on all such Norwegian studies on Salmo salar provided a data set for the time period 1996 to 2011 on 118 release groups comprising 657 624 fish released and 3989 recaptured. The overall risk ratio ( RR ) was estimated to be 1.18 (95% CI : 1.07–1.30). The effect varied strongly between groups, (Higgins I 2 = 40.1%). Over 70% of this heterogeneity could be explained by the release location, time period and baseline survival. The most important predictor variable was baseline survival. In groups with low recapture in the control group (low baseline survival), the effect of treatment was high ( RR = 1.7), while in groups with high recapture in the control group (high baseline survival), there was no effect of treatment ( RR ~ 1.00). The most prevalent parasite in the region affected by the drugs administered was Lepeophtheirus salmonis . Hence, the meta‐analysis supports the hypothesis that L. salmonis contributes to the mortality of S. salar during outward migration. However, the effect of treatment was not consistent, but was evidently strongly modulated by other risk factors. The results suggest that the population‐level effects of parasites cannot be estimated independently of other factors affecting the marine survival of S. salar .
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.057 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".