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Record W3045645222 · doi:10.1093/icb/icaa097

What Does an Insect Hear? Reassessing the Role of Hearing in Predator Avoidance with Insights from Vertebrate Prey

2020· article· en· W3045645222 on OpenAlexaff
Jayne E. Yack, Brianna H. Raven, Michelle B. Léveillée, Mairelys Naranjo

Bibliographic record

VenueIntegrative and Comparative Biology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsCarleton University
FundersCompany of BiologistsSociety for Integrative and Comparative Biology (SICB)
KeywordsPredationPredatorHuman echolocationBiologyVertebrateAposematismEcologyInsectInvertebrateNeuroscience

Abstract

fetched live from OpenAlex

Insects have a diversity of hearing organs known to function in a variety of contexts, including reproduction, locating food, and defense. While the role of hearing in predator avoidance has been extensively researched over the past several decades, this research has focused on the detection of one type of predator-echolocating bats. Here we reassess the role of hearing in antipredator defense by considering how insects use their ears to detect and avoid the wide range of predators that consume them. To identify the types of sounds that could be relevant to insect prey, we first review the topic of hearing-mediated predator avoidance in vertebrates. Sounds used by vertebrate prey to assess predation risk include incidental sound cues (e.g., flight sounds, rustling vegetation, and splashing) produced by an approaching predator or another escaping prey, as well as communication signals produced by a predator (e.g., echolocation calls, songs) or nonpredator (e.g., alarm calls). We then review what is known, and what is not known, about such sounds made by the main predators and parasitoids of insects (i.e., birds, bats, terrestrial vertebrates, and invertebrates) and how insects respond to them. Three key insights emerged from our review. First, there is a lack of information on how both vertebrate and insect prey use passive sound cues produced by predators to avoid being captured. Second, while there are numerous examples of vertebrate prey eavesdropping on the calls and songs of predators and nonpredators to assess risk, there are currently no such examples for eared insect prey. Third, the hearing sensitivity of many insects, including those with ears considered to be dedicated to detecting bats or mates, overlaps with both sound cues and signals generated by nonbat predators. Sounds of particular relevance to insect prey include the flight sounds and calls of insectivorous birds, the flight sounds of insect predators and parasitoids, and rustling vegetation sounds of birds and terrestrial predators. We conclude that research on the role of insect hearing in predator avoidance has been disproportionally focused on bat-detection, and that acoustically-mediated responses to other predators may have been overlooked because the responses of prey may be subtle (e.g., ceasing activity, increasing vigilance). We recommend that researchers expand their testing of hearing-mediated risk assessment in insects by considering the wide range of sounds generated by predators, and the varied responses exhibited by prey to these sounds.

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 score0.317
Threshold uncertainty score0.972

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)0.0000.000

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 head0.061
GPT teacher head0.266
Teacher spread0.204 · 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

Citations23
Published2020
Admission routes1
Has abstractyes

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