Application of a putative alarm cue hastens the arrival of invasive sea lamprey (<i>Petromyzon marinus</i>) at a trapping location
Bibliographic record
Abstract
The sea lamprey Petromyzon marinus is an invasive pest in the Laurentian Great Lakes basin, threatening the persistence of important commercial and recreational fisheries. There is substantial interest in developing effective trapping practices via the application of behavior-modifying semiochemicals (odors). Here we report on the effectiveness of utilizing repellent and attractant odors in a push–pull configuration, commonly employed to tackle invertebrate pests, to improve trapping efficacy at permanent barriers to sea lamprey migration. When a half-stream channel was activated by a naturally derived repellent odor (a putative alarm cue), we found that sea lamprey located a trap entrance significantly faster than when no odor was present as a result of their redistribution within the stream. The presence of a partial sex pheromone, acting as an attractant within the trap, was not found to further decrease the time to when sea lamprey located a trap entrance relative to when the alarm cue alone was applied. Neither the application of alarm cue singly nor alarm cue and partial sex pheromone in combination was found to improve the numbers of sea lamprey captured in the trap versus when no odor was present — likely because nominal capture rate during control trials was unusually high during the study period. Behavioural guidance using these odors has the potential to both improve control of invasive non-native sea lamprey in the Great Lakes as well as improving the efficiency of fish passage devices used in the restoration of threatened lamprey species elsewhere.
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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".