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Record W4321327454 · doi:10.1002/ecy.4007

Auditory predator cues decrease herbivore survival and plant damage

2023· article· en· W4321327454 on OpenAlexaff
Zachary A. Lee, Caroline B. Cohen, A. Baranowski, Kristen N. Berry, Maxwell R. McGuire, Tyler S. Pelletier, Brendan P. Peck, Jacqueline Blundell, Evan L. Preisser

Bibliographic record

VenueEcology · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPredationBiologyHerbivoreCaterpillarPredatorEcologyExiguaBiomass (ecology)LarvaSpodoptera

Abstract

fetched live from OpenAlex

The high fitness cost of predation selects prey capable of detecting risk cues and responding in ways that reduce their vulnerability. While the impacts of auditory predator cues have been extensively researched in vertebrate prey, much less is known about invertebrate species' responses and their potential to affect the wider food web. We exposed larvae of Spodoptera exigua, a slow-moving and vulnerable herbivore hunted by aerial predators, to recordings of wasp buzzing (risk cue), mosquito buzzing (no-risk cue), or a no-sound control in both laboratory and field settings. In the laboratory, wasp buzzing (but not mosquito buzzing) reduced survival relative to the control; there was, however, no effect on time to or weight at pupation in survivors. In the field, wasp buzzing reduced caterpillar herbivory and increased plant biomass relative to the control treatment. In contrast, mosquito buzzing reduced herbivory less than wasp buzzing and had no effect on plant biomass. The fact that wasp cues evoked strong responses in both experiments, while mosquito buzzing generally did not, indicates that caterpillars were responding to predation risk rather than sound per se. Such auditory cues may have an important but largely unappreciated impacts on terrestrial invertebrate herbivores and their host plants.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 head0.036
GPT teacher head0.217
Teacher spread0.181 · 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 designBench or experimental
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

Citations3
Published2023
Admission routes1
Has abstractyes

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