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Record W3080995653 · doi:10.1371/journal.pone.0237594

Ontogenetic shift from aposematism and gregariousness to crypsis in a Romaleid grasshopper

2020· article· en· W3080995653 on OpenAlexafffund
Emma Despland

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsConcordia University
FundersFonds de recherche du Québec – Nature et technologies
KeywordsAposematismCrypsisGrasshopperChemical defenseBiologyNymphCamouflagePredationZoologyOntogenyEcologyPredatorHerbivore

Abstract

fetched live from OpenAlex

Traits of chemically-defended animals can change as an individual grows and matures, and both theoretical and empirical evidence favour a direction of change from crypsis to aposematism. This study examines the suite of traits involved in an unusual opposite shift from aposematism to crypsis in a neotropical toxic-plant-feeding Romaleid grasshopper, Chromacris psittacus (Gerstaecker, 1873). Field surveys, behavioural observations and a rearing experiment compare host plant choice, aggregation, locomotion and thermoregulation between life history stages. Results showed that both nymphs and adults fed exclusively on a narrow range of Solanaceae plants, suggesting that the shift in defensive syndrome is not due to a change in chemical defense. Instead, nymphal aposematism appears linked to aggregation in response to plant-based selection pressures. Slow nymphal development suggests a cost to feeding on toxic plant compounds, and grouping could mitigate this cost. Grouping also increases conspicuousness, and hence can favour warning colourating in chemically-defended insects. The role of diet breadth in aposematism is poorly understood, and these results suggest how constraints imposed by feeding on toxic plants can generate bottom-up selection pressures shaping the adaptive suites of traits of chemically-defended animals.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.103
GPT teacher head0.189
Teacher spread0.086 · 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

Citations8
Published2020
Admission routes2
Has abstractyes

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