Animal-Borne Acoustic Transceivers Reveal Patterns of at-Sea Associations in an Upper-Trophic Level Predator
Bibliographic record
Abstract
Satellite telemetry data have substantially increased our understanding of habitat use and foraging behaviour of upper-trophic marine predators, but fall short of providing an understanding of their social behaviour. We sought to determine whether novel acoustic and archival GPS data could be used to examine at-sea associations among grey seals (Halichoerus grypus) during the fall foraging period. Fifteen grey seals from Sable Island, Canada were deployed with Vemco Mobile Transceivers and Satellite-GPS transmitters in October 2009, 13 of which were recaptured and units retrieved 79 ± 2.3 days later during the following breeding season, December 2009-January 2010. An association between two individuals was defined as a cluster of acoustic detections where the time between detections was <30 min. Bathymetry, travel rate, and behavioural state (slow and fast movement) were determined for each GPS archival point (3.7 ± 0.1 locations recorded per hour). Behavioural state was estimated using a hidden Markov model. All seals had been involved in associations with other instrumented seals while at sea, with a total of 1,872 acoustic detections recorded in 201 associations. The median number of detections per association was 3 (range: 1-151) and the median duration of an association was 0.17 h (range: <0.1-11.3 h). Linear mixed-effects models showed that associations occurred when seals were exhibiting slow movement (0.24 ± 0.01 ms(-1)) on shallow (53.4 ± 3.7 m) offshore banks where dominant prey is known to occur. These results suggest the occurrence of short-term associations among multiple individuals at foraging grounds and provide new insights into the foraging ecology of this upper-trophic marine predator.
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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 | 0.000 | 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".