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Record W4409016118 · doi:10.1093/jeb/voaf038

Behavioural mimicry among poison frogs diverges during close-range encounters with predators

2025· article· en· W4409016118 on OpenAlexaff
James B. Barnett, Brendan L. McEwen, Isaac Kinley, Hannah M. Anderson, Justin Yeager

Bibliographic record

VenueJournal of Evolutionary Biology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsBaycrest HospitalMcMaster University
Fundersnot available
KeywordsBatesian mimicryAposematismMimicryPredationBiologyPredatorCrypsisCamouflageEcologyArboreal locomotionZoologyEvolutionary biologyHabitat

Abstract

fetched live from OpenAlex

Aposematic species signal their unpalatability to potential predators with recognizable, and frequently conspicuous, colour patterns. These visual signals are often also associated with bold behaviour and a reduced propensity to escape from approaching predators. Bold behaviours may act as an aversive signal and allow defended prey to avoid the energetic/opportunity costs that arise from fleeing predators. For Batesian mimics, non-defended species which replicate the colours of defended models, behavioural mimicry may also improve mimic fidelity and reduce energetic/opportunity costs. However, as predators may test the honesty of aposematic signals through sampling behaviour, Batesian mimics can be at high risk during close-range interactions with predators. This raises the question of whether/when Batesian mimics should deviate from behavioural mimicry and initiate more extensive escape behaviour. Here, we exposed the chemically defended poison frog Ameerega bilinguis and its (non-toxic) Batesian mimic Allobates zaparo to a simulated predator encounter. We predicted Al. zaparo would escape to a greater distance and in a more erratic manner than Am. bilinguis. Yet, contrary to our predictions, Al. zaparo did not flee far from predators. It was, however, more likely to initiate escape prior to physical contact from the predator. We suggest that bold behaviour coupled with pre-emptive movement allows Al. zaparo to retain the benefits of behavioural mimicry while reducing the likelihood that predators will test signal honesty. Our data highlight that when examining the evolution of mimicry, we must consider both morphological and behavioural traits, as well as how risk to the prey may change how they behave throughout the predation sequence.

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 score0.011
Threshold uncertainty score0.604

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.211
Teacher spread0.206 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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