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Record W2330687458 · doi:10.1139/cjz-2012-0239

Acoustics of the mountain pine beetle (<i>Dendroctonus ponderosae</i>) (Curculionidae, Scolytinae): sonic, ultrasonic, and vibration characteristics

2013· article· en· W2330687458 on OpenAlexafffundvenue
Alan J. Fleming, Amanda A. Lindeman, Allan L. Carroll, Jayne E. Yack

Bibliographic record

VenueCanadian Journal of Zoology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsUniversity of British ColumbiaCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Economic Development and Innovation
KeywordsDendroctonusCurculionidaeMountain pine beetleBark beetleBiologyAcousticsDoppler effectEcologyPhysics

Abstract

fetched live from OpenAlex

Acoustic signaling is widespread in bark beetles (Scolytinae), although little is known about the physical characteristics of signals, how they are transmitted, and how they differ among behavioural contexts. Signals were studied in the male mountain pine beetle (Dendroctonus ponderosae Hopkins, 1902) during stress, male–female, and male–male interactions. Sounds are broadband with significant energy in the ultrasound (peaks between 15 and 26 kHz) and low amplitude (55 and 47 dB SPL at 2 and 4 cm, respectively), indicating that signaling functions at close range. Signal trains vary among contexts primarily in the proportions of chirp types. Chirps were categorized as being simple or interrupted, with the former having significantly lower tooth strike rates and shorter chirp durations. Stress chirps are predominantly simple with characteristics resembling other insect disturbance signals. Male–female interactions begin with the male producing predominantly interrupted chirps prior to gallery entrance, followed by simple chirps. Male–male (rivalry) chirps are predominantly simple, with evidence of antiphonal calling. Substrate-borne vibrations were detectable with a laser-doppler vibrometer at short distances (1–3 cm), suggesting that sensory organs could be tuned to either air or substrate-borne vibrations. These results have important implications for future research on the function and reception of acoustic signals in bark beetles.

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 score0.074
Threshold uncertainty score0.999

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)0.0020.000

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 head0.005
GPT teacher head0.180
Teacher spread0.176 · 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

Citations46
Published2013
Admission routes3
Has abstractyes

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