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Record W2754370211 · doi:10.1676/16-084.1

Effects Of Geolocation Tracking Devices On Behavior, Reproductive Success, and Return Rate of <i>Aethia</i> Auklets: An Evaluation of Tag Mass Guidelines

2017· article· en· W2754370211 on OpenAlexaff
Carley R. Schacter, Ian L. Jones

Bibliographic record

VenueThe Wilson Journal of Ornithology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSeabirdForagingGeolocationReproductive successTracking (education)BiologyEcologyCharadriiformesHabitatZoologyMedicineComputer sciencePsychologyPredationEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.334

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.355
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2017
Admission routes1
Has abstractyes

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