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Record W4407329022 · doi:10.1242/jeb.249796

Buzzing boundaries: tiny caterpillars vibrate to defend leaf tip territories

2025· article· en· W4407329022 on OpenAlexafffund
Sarah M. Matheson, Leonardo M. Turchen, Emilie Mauduit, Jayne E. Yack

Bibliographic record

VenueJournal of Experimental Biology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaQueen's UniversityCarleton University
KeywordsMarketing buzzBiologyCONTESTCaterpillarTerritorialityLepidoptera genitaliaNest (protein structural motif)EcologyAdvertisingLaw

Abstract

fetched live from OpenAlex

Territorial displays include some of the most elaborate behaviours in the animal kingdom. In this study, we investigated the territorial behaviour and vibratory signalling of neonate warty birch caterpillars (Falcaria bilineata; Lepidoptera: Drepanidae), which reside solitarily on birch leaves and defend the leaf tip. Upon hatching, these tiny caterpillars - no larger than 2 mm - seek out and establish a small solitary territory (∼1 cm wide) at the leaf tip, where they lay silk mats, feed and advertise their presence by producing multicomponent vibratory signals - buzz scrapes and drums. When a conspecific neonate (intruder) is introduced to a leaf occupied by a resident, the resident increases its signalling rate up to four times that when undisturbed, and even more - up to 14 times - if the intruder enters the territory. Intruders rarely manage to take over the resident's defended space, with most confrontations (71%) ending in the resident maintaining control. Residents signal significantly more than intruders at all stages of the contest. If physical contact occurs, residents flee by dropping from the leaf by a silk thread. This results in territorial contests that involve no physical aggression, relying entirely on vibratory communication. These vibratory displays most likely function to establish spacing between conspecifics on a tree branch, but these complex signals may also function to exclude other members of the vibratory community by mimicking something dangerous, such as a jumping spider.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 head0.030
GPT teacher head0.270
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2025
Admission routes2
Has abstractyes

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