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Record W2035116902 · doi:10.1139/z06-120

The adaptive utility of Richardson’s ground squirrel (Spermophilus richardsonii) short-range ultrasonic alarm signals

2006· article· en· W2035116902 on OpenAlexaffvenue
David R. Wilson, James F. Hare

Bibliographic record

VenueCanadian Journal of Zoology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAlarm signalBiologyALARMStimulus (psychology)Ultrasonic sensorVigilance (psychology)PredationGround squirrelEcologyHome rangeAnimal communicationZoologyAcousticsCommunicationSquirrel monkeyCognitive psychologyNeuroscienceHabitatPhysicsPsychology

Abstract

fetched live from OpenAlex

Richardson’s ground squirrels ( Spermophilus richardsonii (Sabine, 1822)) produce audible (ca. 8 kHz) and (or) ultrasonic (ca. 48 kHz) alarm vocalizations that warn conspecifics of impending danger. Audible calls have a larger active space than ultrasonic calls because they travel farther, are louder, and contain frequencies to which conspecific and allospecific recipients are more sensitive. In our first experiment, we presented an alarming stimulus to 103 squirrels to examine the effect of threat proximity on signal type. The ratio of ultrasonic to audible alarm calls increased with increasing distance from the stimulus. We conclude that the size of the active space influences signalling strategy and that squirrels emitting ultrasonic calls can signal conspecifics to the exclusion of distant predators. As recipients of ultrasonic calls must be close to the signaler, one context in which ultrasonic calling may be most adaptive is during natal emergence when juveniles are particularly abundant, highly vulnerable to predation, and clustered in space. In our second experiment, we broadcast ultrasonic alarm signals to emerging juveniles and found that they, like older individuals, responded to calls by increasing vigilance. We discuss the adaptive utility of multiple signalling strategies in light of our findings.

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)0.001
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 score0.246
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.223
Teacher spread0.197 · 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

Citations47
Published2006
Admission routes2
Has abstractyes

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