Group size influences light‐emitting diode light colour and substrate preference of David's Schizothoracin (<i>Schizothorax davidi</i>): Relevance for design of fish passage facilities
Bibliographic record
Abstract
Abstract Fish passage structures have been constructed to facilitate fish movement past barriers, though the effectiveness of passage structures is highly variable. Designing fish passage structures that consider the behavioural preferences of fish under different environmental conditions (e.g., light colour, substrate type) has the potential to improve fish passage success. Similarly, whether a fish encounters a passage facility alone or in a group may influence fish behaviour. In this case, we assessed the preference of different group sizes (n = 1, 6 and 12, respectively) of David's Schizothoracin Schizothorax davidi under four different light‐emitting diode colours and eight different substrate types in the aquaria of the Houziyan Reproduction Station. We found that singletons preferred to visit the white light, cement and fine pebble, while the fish in groups preferred to visit the blue light, fine pebble and cobble. In addition, the total percentage of mobility frequency (18.3 ± 1.8%), movement velocity (20.4 ± 15.9 cm/s) and distance moved (15.8 ± 1.8 m) of singletons in blue light were much lower than that in the others. The movement velocity (3.3 ± 0.6 cm/s) of singletons on cobble was less, but the percentage of total mobility time (162.9 ± 16.0%) and distance moved (153.4 ± 19.6 m) on the cobble were much greater. Our research yielded novel insights for improving passage efficiency for this species. Findings from this study suggest there should be greater consideration of light colour and substrate type when designing fish passage facilities. Because fish almost always experience dynamic hydraulic conditions near and in fishways, additional research is needed to understand the generality of these findings in systems under lotic characteristics.
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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".