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Evidence that tufted puffins <i>Fratercula cirrhata</i> use colony overflights to reduce kleptoparasitism risk

2009· article· en· W2029821234 on OpenAlexafffundabout
Gwylim S. Blackburn, J. Mark Hipfner, Ronald C. Ydenberg

Bibliographic record

VenueJournal of Avian Biology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of British Columbia
FundersSimon Fraser University
KeywordsKleptoparasitismBiologyForagingPredationEcologyFisheryZoology

Abstract

fetched live from OpenAlex

Predation, foraging and mating costs are critical factors shaping life histories. Among colonial seabirds, colony overflights may enhance foraging or mating success, or diminish the risk of predation and kleptoparasitism. The latter possibility is difficult to test because low predation or kleptoparasitism rates could be due either to low danger or to effective counter‐tactics by prey. Tufted puffins Fratercula cirrhata breeding at a large colony in British Columbia, Canada, deliver several loads of fish each day to their nestlings and are targets for kleptoparasitism by glaucous‐winged gulls Larus glaucescens . In the present study, we documented the ecological conditions under which overflights occurred in order to assess when overflights were made and to statistically isolate the effect of overflights on kleptoparasitism risk at this site. Load‐carrying puffins engaged in overflights under ecological conditions associated with relatively high rates of kleptoparasitism. Further, when ecological factors determining risk were statistically controlled, overflights were correlated with marginally lower chances of kleptoparasitism than when the risk factors were ignored. The results suggest that breeding puffins at this site use overflights for kleptoparasite avoidance. This tactic is used sparingly, suggesting it is costly. Costs of overflight behaviour might contribute to the impact of kleptoparasitism on the breeding success of tufted puffins.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.039
GPT teacher head0.292
Teacher spread0.252 · 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.

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

Citations4
Published2009
Admission routes3
Has abstractyes

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