Behavioural guidance of Chinook salmon smolts: the variable effects of LED spectral wavelength and strobing frequency
Bibliographic record
Abstract
Exploiting species-specific behavioural responses of fish to light is an increasingly promising technique to reduce the entrainment or impingement of fish that results from the diversion of water for human activities, such as hydropower or irrigation. Whilst there is some evidence that white light can be an effective deterrent for Chinook salmon smolts, the results have been mixed. There is a need to test the response of fish to different spectra and strobing frequencies to improve deterrent performance. We tested the movement and spatial response of groups of four fish to combinations of light-emitting diode (LED) spectra (red, green, blue and white light) during the day and night, and strobing frequencies (constant and 2Hz) during the day, using innovative LED technology intended as a behavioural guidance device for use in the field. Whilst strobing did not alter fish behaviour when compared to constant light, the red light had a repulsive effect during the day, with fish under this treatment spending significantly less time in the half of the arena closest to the behavioural guidance device compared to both the control and blue light. Importantly, this effect disappeared at night, where there were no differences in movement and space use found between spectra. There was some evidence of a potential attractive response of fish to the blue and green light during the day. Under these light treatments, fish spent the highest amount of time closest to the behavioural guidance device. Further tests manipulating the light intensity in the different spectra are needed to verify the mechanistic determinants of the observed behaviours. Results are discussed in reference to the known spectral sensitivities of the cone and rod photopigments in these fish, and further experiments are suggested to better relate the work to mitigating the effects on fish of infrastructure used for hydropower and irrigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".