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Record W2006292272 · doi:10.1636/st08-84.1

Predatory interactions between Centruroides scorpions and the tarantula Brachypelma vagans

2011· article· en· W2006292272 on OpenAlexaff
Ariane Dor, Sophie Calmé, Yann Hénaut

Bibliographic record

VenueJournal of Arachnology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBiologyPredationZoologyEcology

Abstract

fetched live from OpenAlex

In the Yucatan Peninsula, the tarantula Brachypelma vagans Ausserer 1875 is commonly associated with human settlements, as are the scorpions Centruroides gracilis Latreille 1804 and C. ochraceus Pocock 1898. Nonetheless, scorpions are virtually absent from villages showing a high density of tarantulas. Predatory interactions between these predators could explain the lack of local overlap. To test this hypothesis, we observed the behavioral interactions between B. vagans and C. gracilis or C. ochraceus in experimentally controlled conditions, and we compared these interactions to interactions between the tarantula and two prey species: cricket and cockroach. For observations, a pre-adult tarantula was placed in an experimental arena in which we introduced either a scorpion or an insect. In all, 115 trials were performed. We recorded time elapsed and behavioral responses: avoidance, attack, escape, capture, and attack success. Tarantulas preyed on all prey with the same attack success (63.8% ± 0.8%), but they attacked and captured cockroaches quicker and more often than the other prey (87% vs. 50%, and 57% vs. 30%, respectively). Scorpions attacked tarantulas in 25.5% of occasions, but they were never successful, and were killed in 9% of occasions. We conclude that tarantulas are potential predators of scorpions. Moreover, in villages where tarantulas are abundant they might prevent the presence of scorpions. Thus the presence of this non-aggressive tarantula may be beneficial from the human perspective.

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 score0.529
Threshold uncertainty score0.426

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 head0.021
GPT teacher head0.206
Teacher spread0.185 · 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

Citations15
Published2011
Admission routes1
Has abstractyes

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