Migratory hosts can maintain the high‐dose/refuge effect in a structured host‐parasite system: The case of sea lice and salmon
Bibliographic record
Abstract
Migration can reduce parasite burdens in migratory hosts, but it connects populations and can drive disease dynamics in domestic species. Farmed salmon are infested by sea louse parasites, often carried by migratory wild salmonids, resulting in a costly problem for industry and risk to wild populations when farms amplify louse numbers. Chemical treatment can control lice, but resistance has evolved in many salmon-farming regions. Resistance has, however, been slow to evolve in the north-east Pacific Ocean, where large wild-salmon populations harbour large sea louse populations. Using a mathematical model of host-macroparasite dynamics, we explored the roles of domestic, wild oceanic and connective migratory host populations in maintaining treatment susceptibility in associated sea lice. Our results show that a large wild salmon population, unexposed to direct infestation by lice from farms; high levels of on-farm treatment; and a healthy migratory host population are all critical to slowing or stopping the evolution of treatment resistance. Our results reproduce the "high-dose/refuge effect," from the agricultural literature, with the added requirement of a migratory host population to maintain treatment susceptibility. This work highlights the role that migratory hosts may play in shared wildlife/livestock disease, where evolution can occur in ecological time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".