Comparison between the marine soundscape of recreational boat mooring areas with that of a pristine area in the Mediterranean: Evidence that such acoustic hot-spots are detrimental to ecologically sensitive habitats
Bibliographic record
Abstract
We investigated the potential to use passive acoustics to access the impact of recreational boat mooring areas on ecologically sensitive habitats in the Western Mediterranean. One important consequence of the tourist industry in the region is that it targets the most pristine and ecologically sensitive habitats. Underwater sounds were recorded in mooring areas in Ibiza, Formentera and Tabarca harbors during high use and low use seasons and compared to recordings in the Tabarca Marine Protected area. At each location, we recorded sounds during 20 min at three different sites, for three random sampling times during the day. The percent of time occupied by selected biological (drums and croaks) and anthropogenic sounds (boat and mooring chain noises), and call rates of selected fish sounds were measured and compared among sites and seasons. Biological sounds contributed significantly less to the soundscape in mooring areas during the tourist season, and to the reserve in both seasons. Our study demonstrates the critical need for research on the impact of acoustic noise “hot spots” such as recreational mooring areas on marine and freshwater soundscapes.
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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 | 0.001 | 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".