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Pros and cons of group living in the forest tent caterpillar: separating the roles of silk and of grouping

2007· article· en· W2125657085 on OpenAlexaff
Emma Despland, Alice Le Huu

Bibliographic record

VenueEntomologia Experimentalis et Applicata · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsConcordia University
Fundersnot available
KeywordsBiologyIntraspecific competitionCaterpillarEcologyForagingCompetition (biology)InstarLarvaContext (archaeology)Interspecific competitionLepidoptera genitaliaZoology

Abstract

fetched live from OpenAlex

Abstract Group living can incur both benefits and costs, mediated by different mechanisms. In many gregarious caterpillars, collective use of a network of silk trails is thought to improve foraging. Grouping, i.e., close contact with conspecifics, has been postulated to have both positive (thermoregulation and predator defense) and negative (competition and pathogen transmission) effects. The present experiment distinguishes between silk produced by group members and grouping per se in their effects on growth and development of both early and late larval stadia of the forest tent caterpillar [ Malacosoma disstria Hübner (Lepidoptera: Lasiocampidae)] in a laboratory context. For both developmental stadia tested, pre‐established silk trails decreased latency to food finding and hence increased food consumption and growth rate. For younger larvae, pre‐established silk also decreased investment in silk production. Grouping young caterpillars accelerated development at the expense of growth, possibly as a mechanism to avoid intraspecific competition in later larval stadia. In older caterpillars, grouping decreased meal duration, suggesting that competition can indeed occur towards the end of larval development, even in the presence of surplus food. This led to a decrease in growth without any effect on instar duration. The benefits of exogenous silk thus decreased during larval development, whereas the costs associated with crowding increased. Ontogenetic shifts in grouping are common in many taxa: the present study is among the first to provide empirical evidence for an adaptive explanation of observed ontogenetic changes in aggregative behavior.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.014
GPT teacher head0.301
Teacher spread0.287 · 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 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

Citations55
Published2007
Admission routes1
Has abstractyes

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