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Influence of body size and level of cooperation on the prey capture efficiency of two sympatric social spiders exhibiting an included niche pattern

2011· article· en· W1876623234 on OpenAlexafffund
Jennifer Guevara, Leticia Avilés

Bibliographic record

VenueFunctional Ecology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologySympatric speciationForagingPredationEcologyNicheRange (aeronautics)ForageNiche differentiationOptimal foraging theory

Abstract

fetched live from OpenAlex

1. Body size and other morphological traits play key roles in an animal’s performance and thus their ability to locate, capture and handle different resources. For species that live and forage in groups, group-level characteristics, such as foraging group size and level of cooperation, may also influence performance and further shape resource use. 2. We explored the simultaneous role of individual (body size) and social traits on performance (i.e. prey capture efficiency) in two sympatric social spiders in Ecuador. 3. Given a fivefold difference in body size, the large species captured on average significantly larger insects than the small species. However, because the large species captured both small and large insects, its prey size range included that of the small species, which is thus said to exhibit an included niche. 4. The small species compensated for its small body size by having greater density of individuals within the nests, faster reaction times, and greater participation of individuals of all age classes in prey capture. As a result, the smaller species had a steeper increase in the size of the insects it captured with increasing colony size than the larger species. As predicted by included niche theory, the small species was also more efficient within the shared range as it was less likely to miss or ignore small prey than the large species. 5. Our study contributes to our understanding of how social traits may jointly interact with individual-level traits to shape foraging performance and resource use in communities of social organisms, a problem little explored in the past.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.150

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.106
GPT teacher head0.237
Teacher spread0.131 · 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 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

Citations19
Published2011
Admission routes2
Has abstractyes

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