Using acoustic recording tags to investigate anthropogenic sound exposure and effects on behavior in endangered killer whales (Orcinus orca)
Bibliographic record
Abstract
Vessel traffic from commercial shipping, whale-watching, and other boating activity is common in the Salish Sea. Potential effects on local marine mammals include vessel disturbance and associated noise exposure. The Salish Sea also includes designated critical habitat for endangered Southern Resident killer whales (SRKWs) because it is an important summer foraging area for these whales. In both the U.S. and Canada, conservation efforts for SRKWs have identified risk factors or threats that may hinder population recovery. These risk factors include vessel and noise effects, and prey quality and availability. In this collaborative investigation, acoustic recording tags (DTAGs), equipped with hydrophones and other sensors, are temporally attached with suction cups. The tags allow us to collect data about what an individual killer whale experiences in its acoustic environment as well as its vocal and movement behavior subsurface. Specific research goals include: (1) quantifying noise levels that individual whales experience; (2) determining relationships between the noise levels and detailed vessel traffic variables obtained from precise geo-referenced data collected concurrently; (3) investigating whale acoustic and movement behavior during different activities, including foraging, to understand sound use and behavior in specific biological and environmental contexts; and (4) determining potential effects of vessels and associated noise on behavior. We have collected over 80 hours of tag data from 23 tags deployed over three field seasons. Noise levels recorded from killer whales are variable with maximum levels attributed to individual vessels passing in close proximity. Additional data obtained from the tags shed light on the (otherwise) dark and subsurface world of SRKWs, particularly on the importance of acoustics and specific movement patterns during foraging in SRKWs. This paper will describe the experimental approach taken, unique data obtained, and current scientific results. These data are critical for addressing our research goals related to multiple population risk factors of endangered SRKWs.
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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 | 0.001 |
| 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) | 0.000 | 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".