An evaluation of acoustic telemetry as a method to study the movements of Asteroidea (Asterias rubens)
Bibliographic record
Abstract
Abstract Background Acoustic telemetry is an important tool to study the movement of aquatic animals. However, studies have focussed on particular groups of easily tagged species. The development of effective tagging methods for ecologically important benthic species, such as sea stars, remains a challenge due to autotomy and their remarkable capacity to expel any foreign material. We tested three methods to surgically attach acoustic transmitters to the common sea star Asterias rubens; two methods attached the tag to the aboral side of the central body and the third attached the transmitter to the aboral side of an arm. Laboratory experiments evaluated each method in terms of survivability, tag retention, associated injuries, and changes in feeding behaviour and physical condition. Results Laboratory results were highly variable; however, all tagging methods caused significant injury to the epidermis and deeper tissue around the attachment site over periods greater than 4 weeks. Attaching a tag by horizontally piercing the central body (method HPC) had minimal effects in the short-term (2–3 weeks) and this method was used for a pilot tagging study in the field, where 10 sea stars were tagged and placed within an existing acoustic telemetry array. Although, the interpretation of field data was challenging due to the characteristic slow movement of sea stars, movements of a similar magnitude to previous studies were identified during the 2–4 weeks after sea stars were tagged and released. However, this apparent period of tagging success was followed by a reduction in movement that, when viewed in conjunction with laboratory results, potentially indicated a deterioration in the sea stars’ physical condition. Conclusions While acoustic telemetry continues to provide novel insights into the ecology of a wide variety of marine species, species-specific effects of tagging should be evaluated before starting field studies. If the autonomous study of benthic movement is to expand beyond hard-bodied macroinvertebrates current methodological and analytical challenges must be addressed.
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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 | 0.001 | 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) | 0.000 | 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".