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Record W2072898950 · doi:10.1890/11-0455.1

The deadly effects of “nonlethal” predators

2011· article· en· W2072898950 on OpenAlexaff
Shannon J. McCauley, Locke Rowe, Marie‐Josée Fortin

Bibliographic record

VenueEcology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPredationPredatorDragonflyMetamorphosisLarvaBiologyEcologyPhenotypic plasticitySurvivorship curveZoology

Abstract

fetched live from OpenAlex

Nonconsumptive predator effects are widespread and include plasticity as well as general stress responses. Caged predators are often used to estimate nonconsumptive effects, and numerous studies have focused on the larval stages of animals with complex life cycles. However, few of these studies test whether nonconsumptive predator effects, including stress responses, are exclusively sublethal. Nor have they assessed whether these effects extend beyond the larval stage, affecting success during stressful life-history transitions such as metamorphosis. We conducted experiments with larvae of a dragonfly (Leucorrhinia intacta) that exhibits predator-induced plasticity to assess whether the mere presence of predators affects larval survivorship, metamorphosis, and adult body size. Larvae exposed to caged predators with no ability to attack them had higher levels of mortality. In the second experiment, larvae reared with caged predators had higher rates of metamorphic failure, but there was no effect on adult body size. Our results suggest that stress responses induced by exposure to predator cues increase the vulnerability of prey to other mortality factors, and that mere exposure to predators can result in significant increases in mortality.

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 head0.011
GPT teacher head0.199
Teacher spread0.188 · 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

Citations178
Published2011
Admission routes1
Has abstractyes

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