Evaluating the potential for sea lice to evolve freshwater tolerance as a consequence of freshwater treatments in salmon aquaculture
Bibliographic record
Abstract
Increasing usage of non-medicinal methods (NMMs) to control sea louse infestations on salmon farms has raised questions about whether sea lice may be able to evolve tolerance of NMMs. Of particular concern is the potential for sea lice to evolve freshwater tolerance as a result of freshwater treatments. Wild trout and some juvenile salmonids swim into freshwater to control infestations and regain ionic balance after disruption by sea lice; freshwater tolerance would compromise this potentially adaptive behavior. Here we evaluated the potential for freshwater tolerance to evolve in the sea louse Lepeophtheirus salmonis. When exposed to low-salinity water, parasitic stages of sea lice are able to osmoregulate through the host, while larval planktonic stages are not. Transcriptomic work suggests that sea lice mount a costly polygenic stress response when exposed to brackish water. The population structure of sea lice is panmictic in both the Pacific and Atlantic, making it conducive to rapid evolutionary responses. It is unknown how much heritable genetic variation these panmictic populations have for freshwater treatments. While usage of freshwater treatments on wellboats is increasing, it is unclear whether the freshwater itself is a strong selective force; during the freshwater exposure, sea lice can die from physical disruption during pumping and filtration on the wellboat. Future studies are advised to quantify the heritable variation in freshwater tolerance in sea louse populations, characterize mechanisms for freshwater tolerance in planktonic and attached sea lice, and assess the risk of freshwater tolerance evolution under different management strategies
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".