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Record W2189148434 · doi:10.1093/czoolo/60.6.719

To forage or hide? Threat-sensitive foraging behaviour in wild, non-reproductive passerine birds

2014· article· en· W2189148434 on OpenAlexaff
Shaun Turney, Jean‐Guy J. Godin

Bibliographic record

VenueCurrent Zoology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsCarleton UniversityMcGill University
Fundersnot available
KeywordsPasserinePredationForagingBiologyEcologyPredatorForageHabitatAccipiterAposematismZoology

Abstract

fetched live from OpenAlex

Abstract Because antipredator behaviours are costly, the threat-sensitive predator avoidance hypothesis predicts that individual animals should express predator-avoidance behaviour proportionally to the perceived threat posed by the predator. Here, we experimentally tested this hypothesis by providing wild passerine birds supplemental food (on a raised feeding platform) at either 1 or 4 m from the edge of forest cover (potential refuge), in either the presence or absence of a nearby simulated predation threat (a sharp-shinned hawk Accipiter striatus model). Compared with the control treatment, we observed proportionally fewer bird visits to the food patch, and the birds took longer to re-emerge from forest refuge and return to feed at the food patch, after the hawk presentation than before it. The observed threat-sensitive latency-to-return response was stronger when the food patch was further away from the nearest refuge. Overall, our results are consistent with the predictions of the threat-sensitive predator avoidance hypothesis in that wild passerine birds (primarily black-capped chickadees Poecile atricapillus) exhibited more intense antipredator behavioural responses with increasing level of apparent threat. The birds were thus sensitive to their local perceived threat of predation and traded-off safety from predation (by refuging) and foraging gains in open habitat in a graded, threat-sensitive manner.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.314

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 communication0.0000.000
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 head0.031
GPT teacher head0.287
Teacher spread0.256 · 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

Citations18
Published2014
Admission routes1
Has abstractyes

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