Data from: Going the distance: Influence of distance between boat noise and nest site on the behavior of paternal smallmouth bass
Bibliographic record
Abstract
The effects of anthropogenic noise have garnered significant attention in marine ecosystems, but comparatively less is known about its impacts on freshwater ecosystems. For fish that provide parental care, the effects of acoustic disturbance could have fitness-level consequences if nest tending behavior is altered. This study explored the effects of motorboat noise on the parental behavior of nesting male smallmouth bass (Micropterus dolomieu; Lacépède, 1802), an important freshwater game fish in North America that provides sole paternal care to offspring. Specifically, we evaluated how boat noise proximity to a bass nest (ranging from 4.5 to 90 m) influenced paternal care behaviors. A total of 73 fish were exposed to a 3-min motorboat playback designed to simulate a boat sound that typically occurs in areas near littoral nesting sites. The fish were video recorded, and their behaviors were analyzed before, during, and after exposure to the playback. Residency time was the only behavioral metric to be adversely affected by noise playbacks but only when in close proximity to the speaker. Our results suggest that boat noise may have an impact on bass reproductive fitness in specific contexts where combustion motors are used near shore during the nesting period. The largely null findings may indicate a resilience to boat noise and/or habituation to the noise. In addition, boats displace water and create waves that represent another form of disturbance that could be experienced by fish but was not simulated here. Future research should integrate behavioral and physiological responses to boat noise and other aspects of boat disturbance to better understand the fitness impacts of boating activity on freshwater fish.
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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 | 0.002 |
| 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) | 0.014 | 0.003 |
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".