Impacts acoustiques du trafic maritime sur les invertébrés marins benthiques vagiles des zones côtières subarctiques
Bibliographic record
Abstract
Anthropophony is emerging as a major factor in behavioral change among marine fauna, including invertebrates. Among other factors, heavy shipping traffic profoundly alters the behavior of many species, threatening their ecological roles. This doctoral project aims to assess the effect of marine noise through three components focusing on two benthic invertebrates: Buccinum undatum and Cancer irroratus, studied in situ and in the laboratory under prolonged exposure. This doctoral work has highlighted the importance of seasonal cycles in the spatial behavior of B. undatum, thanks to multi-year monitoring using acoustic telemetry, which revealed restricted mobility limiting dispersion and connectivity between populations, thereby increasing vulnerability to local overfishing. Based on these observations, we demonstrated that ship noise significantly reduces the locomotor capacity and dispersal potential of this species, both through in situ experiments in Miquelon Bay and under controlled laboratory conditions. With regard to C. irroratus, we showed, using a protocol that integrated its circadian and seasonal rhythms, that crab activity is also affected by marine noise, but in a seasonally modulated way, with a significant impact only at night in the spring. This work demonstrates that chronic exposure to marine noise disrupts the locomotor behavior of these invertebrates, compromising their dispersal, reducing population connectivity, and potentially altering community structure over the long term.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".