Deterring the Movement of an Invasive Fish: Individual Variation in Common Carp Responses to Acoustic and Stroboscopic Stimuli
Bibliographic record
Abstract
Abstract Biological invasions erode ecosystem functioning and occur more frequently in freshwater ecosystems than in terrestrial environments. Nonphysical deterrents may be used to limit invasive fish dispersal, without altering the streamflow or connectivity of a watershed. Little is currently known about how behavioral variation among individuals may affect the efficacy of a deterrent, although such variation has been shown to affect fish dispersal in other contexts, such as range expansion. Furthermore, deterrent effectiveness is rarely tested when fish are motivated to disperse. Across a control, CO2, and CO2 + deterrent treatment, we quantified the avoidance response of invasive Common Carp Cyprinus carpio to a combined acoustic‐stroboscopic deterrent. In the CO2 treatment, we motivated individuals to enter a novel environment by degrading the home chamber of a choice arena with a continuous infusion of CO2. In the CO2 + deterrent treatment we introduced acoustic and stroboscopic stimuli to delay the departure of the fish and evaluate the efficacy of the deterrent. Finally, we tested a subset of the fish multiple times to determine whether they consistently responded to the same concentration of CO2. We found that the acoustic and stroboscopic deterrent could detain the fish in an increasingly unfavorable environment. Common Carp took only 195 and 131 s, respectively, to swim between the chambers during the control and CO2 treatment but took an average of 596 s in the CO2 + deterrent treatment. High CO2 concentrations in the CO2 + deterrent treatment led to most fish eventually dispersing toward the deterrent stimuli. Avoidance behavior varied widely within the CO2 + deterrent treatment, and Common Carp expressed repeatable differences in the tank‐inflow CO2 concentrations that were observed during chamber departure. Such interindividual variation in deterrent avoidance indicates that some individuals within a given species are more likely to move past a deterrent than others.
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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 | 0.001 | 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".