Effects Of Geolocation Tracking Devices On Behavior, Reproductive Success, and Return Rate of <i>Aethia</i> Auklets: An Evaluation of Tag Mass Guidelines
Bibliographic record
Abstract
The use of tracking devices (tags) to investigate seabird movements and habitat use has grown rapidly over the last 30 years, but often tracking data are reported without assessment of the effects of tags. The extra mass and bulk may risk altering behavior, and effects likely vary depending on the size, anatomy, and foraging strategy of different species. A guideline that tags should not exceed 3% body mass is widely accepted by seabird researchers, but this guideline was developed for albatrosses and petrels. A review of tracking studies showed that alcids are more likely to be affected by tags than other groups. We found some evidence of a negative effect of tags on Parakeet Auklets' (Aethia psittacula; mean mass 266 g, tag 0.8–1.1% of body mass) reproductive success but not return rate or chick growth. Tagged Whiskered Auklets (A. pygmaea; mean mass 112 g, tag 1.8% of body mass) showed minor decreases in chick growth, and a 74% lower adult return rate during 2014–2015, despite no significant difference from control returns in 2013–2014. Our study demonstrated negative effects in alcids of tags well below the 3% guideline, confirming that limits for one group should not be uncritically applied to all seabirds. Mass of tags deployed should be kept to a minimum, but other factors (e.g., wing-loading, flight energetics, foraging strategy) may be equally important. To ensure the biological relevance of collected data, we strongly recommend that inclusion of tag effect experiments be considered essential in the design and approval of tracking studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 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 | 0.001 |
| 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 teacher head, 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".