Phylogenetic signal found in fish–community response to an acoustic common carp deterrent
Bibliographic record
Abstract
Abstract Non‐structural deterrents may limit invasive fish dispersal and range expansion without altering waterflow or navigation. Despite extensive research in laboratory and artificial environments, few studies have been conducted in situ and, of those, few have evaluated the full community response of fishes interacting with the deterrent. We deployed acoustic deterrents within a physical trap‐and‐sort fishway at Cootes Paradise, Ontario, Canada, to determine the avoidance responses of a community of fishes attempting to disperse into the wetland. To test the effectiveness of an acoustic deterrent, the catch rates of fishes entering Cootes Paradise were compared when the deterrent was off (control) and on (treatment). Community diversity was fit to candidate generalised linear models, and common carp catch abundance was fit to candidate generalised additive models, both of which were compared with backwards selection. The presence of a phylogenetic signal in fish responses was assessed with Pagel's λ and Blomberg's K indices of trait evolution. Over 11,500 fishes, representing 16 species and 12 families, were captured. The acoustic deterrent did not alter the Shannon diversity of fishes challenging the fishway, but a significant phylogenetic signal in species‐specific avoidance responses was observed. There was a modest decrease in the catch rates of common carp (ambient trials = 1.03 fish/hr, deterrent trials = 0.84 fish/hr), a species of major management concern. Fish avoidance responses to acoustic deterrents were widely variable, and species specific. The avoidance response of common carp, the target species, was weak, probably due to a complex acoustic environment surrounding the fishway. Group size did not alter deterrent efficacy, but precipitation, water temperature, and turbidity did. Our study successfully quantified acoustic deterrent responses across an entire community of wetland fishes, including both native and invasive species. We are the first to demonstrate that there is a phylogenetic component to deterrent responses across species. We also identify environmental parameters that alter deterrent efficacy in the field, and describe important considerations for the deployment of non‐structural deterrents in the field.
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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".