Behavioral reactions of free-ranging harbor porpoises Phocoena phocoena encountering standard nylon and BaSO4 mesh gillnets and warning sound
Bibliographic record
Abstract
MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 313:285-294 (2006) - doi:10.3354/meps313285 Behavioral reactions of free-ranging harbor porpoises Phocoena phocoena encountering standard nylon and BaSO4 mesh gillnets and warning sound Sven Koschinski1,*, Boris M. Culik1, Edward A. Trippel2, L. Ginzkey3 1Leibniz Institute of Marine Sciences at Kiel University (IFM-GEOMAR), Düsternbrooker Weg 20, 24105 Kiel, Germany 2Fisheries and Oceans Canada, Biological Station, St. Andrews, New Brunswick E5B 2L9, Canada 3Federal Armed Forces Underwater Acoustics and Marine Geophysics Research Institute (FWG), Klausdorfer Weg 224, 24148 Kiel, Germany *Email: sven.koschinski@meereszoologie.de ABSTRACT: Field tests suggest that high-density nets can reduce harbor porpoise Phocoena phocoena by-catch in demersal gillnet fisheries. However, it is not clear whether acoustic reflectivity or twine stiffness are responsible for this. We conducted sonar tests in a tank in the frequency range of 110 to 190 kHz and found that the target strength of the high-density BaSO4 net was 7.2 dB higher at 150 kHz than that of the standard nylon net. In a fjord on Vancouver Island, Canada, we investigated porpoise surfacing and echolocation behavior as they encountered 2 surface gillnets (45 × 9 m, 165 mm mesh size) made of (1) standard 100% nylon and (2) a mix of BaSO4 and nylon. The distribution of click intervals shifted to longer intervals when the BaSO4 net was used (median = 51 ms vs. 45.2 ms for the standard net; Kolmogorov-Smirnov test, p < 0.001), indicating a greater target distance. We estimated that porpoises are able to detect BaSO4 nets 4.4 m in advance of standard nylon nets. However, an unexpected low percentage of echolocating porpoise groups within 50 m of the center of nets (standard 30.6%, BaSO4 19.3%) indicates that additional measures may be necessary to reduce by-catch. A subsequent experiment showed that transmission of 2.5 kHz tones as a warning sound increased biosonar use by a factor of 4 compared to controls (16.7% for controls vs. 71.4% for groups during ensonification; chi2-test, p < 0.001). The combination of reflective nets and warning sounds may be a promising mitigative tool. KEY WORDS: Harbor porpoise · Phocoena phocoena · Barium sulfate · Reflective gillnet · By-catch mitigation Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 313. Online publication date: May 11, 2006 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2006 Inter-Research.
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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 | 0.000 | 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".