Response of Migratory Sea Lampreys to Artificial Lighting in Portable Traps
Bibliographic record
Abstract
Abstract This study evaluated responses by migratory spawning-phase sea lampreys Petromyzon marinus to artificial trap lighting in the laboratory and field with the aim of improving trapping as a method of sea lamprey control in the Laurentian Great Lakes. We hypothesized that lighting would improve trap success by increasing the attraction to, entrance into, or retention within portable sea lamprey traps. The responses of migratory sea lampreys to nocturnal lighting were complex and situation dependent. In the laboratory, where two traps were placed side by side, more sea lampreys were caught in the lit trap than in the unlit trap (80% versus 20%), largely because of increased attraction to the lit trap (75% of trap funnel entries by sea lampreys were in lit traps). In the field, where two traps were set 9 m apart and located against a barrier to upstream movement, there was no consistent difference in the numbers of sea lampreys caught in lit versus unlit traps. We provide two hypotheses for the variability in response to trap lighting between the laboratory and field, but overall the inconsistency of sea lamprey response to trap lighting leads us to conclude that the benefits of implementing trap lighting for sea lamprey control are limited. Lighting traps may be beneficial in situations where lighting is implemented in conjunction with other trap modifications that attract sea lampreys to within close proximity of traps or when traps are operated in stream locations that already encounter high volumes of sea lampreys. Received November 2, 2011; accepted February 17, 2012
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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 | 0.000 |
| 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".