Assessing the impacts of anthropogenic sounds on early stages of benthic invertebrates: The “<scp><i>Larvosonic</i></scp> system”
Bibliographic record
Abstract
Abstract Noise produced by human activities has increased in the oceans over the last decades. Whereas most studies have focused on the impact of anthropogenic noise on marine mammals and fishes, those focusing on marine invertebrates are rarer and more recent, especially when considering peri‐metamorphic benthic stages, highly sensitive to anthropogenic perturbations. A careful review of the literature reveals a simplistic characterization of the acoustics within the containers used to quantify larval and juvenile responses to noise, thus weakening the conclusions of such works. To address this problem, we developed the Larvosonic system, a laboratory tank equipped with acoustic assets to assess the impacts of noise on young stages of marine invertebrates. We first provide a careful analysis of the tank sound field using different sound types, and we assess the effects of expanded polystyrene units on the sounds emitted by a professional audio system in order to dampen reverberation and resonance. Then, we apply this acoustic calibration to the effects of both pile driving and drilling noises on postlarvae of the scallop bivalve Pecten maximus. Acoustic recordings highlight that diffuser and bass trap components constitute effective underwater sound absorbents, reducing the reflection of the whole frequency bandwidth. Scallop experiments reveal that both type and level of the tested noise influenced postlarval growth, with interactive effects between trophic environment and noise level/spectra. The Larvosonic system thus constitutes an efficient tool for bioacoustics research on bentho‐planktonic invertebrate species.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".