Sea lice in the North Pacific: from sub-lethal effects on wild salmon to parasite management and policy
Bibliographic record
Abstract
Since wild-capture fisheries production plateaued in the early 1990s, the world's dependence on aquaculture has grown steadily.This 'blue revolution' may have helped the conservation of some wild aquatic species by decreasing fishing pressure, but for others it has depleted their populations through habitat degradation, harvest for feed, and the spread of infectious disease.This thesis examines how parasites from aquaculture facilities can indirectly influence wild host survival and assesses how improvements to policy could limit these effects.I explore these topics in British Columbia, Canada, where wild Pacific salmon (Oncorhynchus spp.) are commonly infested with parasitic sea lice (Lepeophtheirus salmonis and Caligus clemensi) from open-net salmon farms.In Chapter 2, I use a field experiment to demonstrate that heavy sea louse infestation is associated with decreased competitive foraging ability for juvenile sockeye salmon (O.nerka).In Chapter 3, I show that this louse-associated reduction in competitive ability leads to decreased foraging success for juvenile sockeye in the wild.In Chapter 4, I analyse the otoliths (i.e., ear stones) of juvenile sockeye to reveal that highly infested fish grow more slowly than uninfested individuals.Each of these responsescompetitive ability, foraging success, and growthhas major implications for salmon survival.In Chapter 5, I then investigate the ways in which parasite control policy could be improved on salmon farms to limit transfer of sea lice to wild salmon.I demonstrate that there is considerable underestimation bias in selfreported sea lice counts from industry, which determine when delousing treatments are used to control sea lice outbreaks on farms.I also show that current parasite control policy is not resilient to changing environmental conditions and I assess the potential effectiveness of alternative policies.Ultimately, the sustainability and success of the blue revolution will depend on our understanding of the full impacts of disease on wildlife and our ability to limit them.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".