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Record W2114420901 · doi:10.1073/pnas.0710603105

Cooperative capture of large prey solves scaling challenge faced by spider societies

2008· article· en· W2114420901 on OpenAlexaff
Eric C. Yip, Kimberly S. Powers, Leticia Avilés

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsUniversity of British Columbia
FundersUniversity of ArizonaWissenschaftskolleg zu BerlinNational Science Foundation
KeywordsSpiderPredationSocialityBiologyEcologyPer capitaForageBiomass (ecology)Range (aeronautics)ForagingDemography

Abstract

fetched live from OpenAlex

A decrease in the surface area per unit volume is a well known constraint setting limits to the size of organisms at both the cellular and whole-organismal levels. Similar constraints may apply to social groups as they grow in size. The communal three-dimensional webs that social spiders build function ecologically as single units that intercept prey through their surface and should thus be subject to this constraint. Accordingly, we show that web prey capture area per spider, and thus number of insects captured per capita, decreases with colony size in a neotropical social spider. Prey biomass intake per capita, however, peaks at intermediate colony sizes because the spiders forage cooperatively and larger colonies capture increasingly large insects. A peaked prey biomass intake function would explain not only why these spiders live in groups and cooperate but also why they disperse only at large colony sizes, thus addressing both sociality and colony size range in this social spider. These findings may also explain the conspicuous absence of social spiders from higher latitudes and higher elevations, areas that we have previously shown to harbor considerably fewer insects of the largest size classes than the lowland tropical rainforests where social spiders thrive. Our findings thus illustrate the relevance of scaling laws to the size and functioning of levels of organization above the individual.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.032
GPT teacher head0.300
Teacher spread0.268 · 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

Citations204
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicInsect and Arachnid Ecology and BehaviorFrench-language works237,207