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Record W3206720261 · doi:10.3390/biology10101012

Skull Morphology, Bite Force, and Diet in Insectivorous Bats from Tropical Dry Forests in Colombia

2021· article· en· W3206720261 on OpenAlexaff
Leidy Azucena Ramírez‐Fráncel, Leidy Viviana García‐Herrera, Sergio Losada‐Prado, Gladys Reinoso‐Flórez, Burton K. Lim, Francisco Sánchez, Alfonso Sánchez‐Hernández, Giovany Guevara

Bibliographic record

VenueBiology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsRoyal Ontario Museum
FundersUniversidad del Tolima
KeywordsInsectivoreBiologyBite force quotientOmnivoreSkullPredationEcologyZoologyTrophic levelAnatomy

Abstract

fetched live from OpenAlex

In Neotropical bats, studies on bite force have focused mainly on differences in trophic ecology, and little is known about whether factors other than body size generate interspecific differences in bite force amongst insectivorous bats and, consequently, in their diets. We tested if bite force is related to skull morphology and also to diet in an assemblage of Neotropical insectivorous bats from tropical dry forests in the inter-Andean central valley in Colombia. It is predicted that the preference of prey types among insectivorous species is based on bite force and cranial characteristics. We also evaluated whether skull morphology varies depending on the species and sex. Cranial measurements and correlations between morphological variation and bite force were examined for 10 insectivorous bat species. We calculated the size-independent mechanical advantage for the mandibular (jaw) lever system. In all species, bite force increased with length of the skull and the jaw more than other cranial measurements. Obligate insectivorous species were morphologically different from the omnivorous Noctilio albiventris, which feeds primarily on insects, but also consumes fish and fruits. Our results show that bite force and skull morphology are closely linked to diets in Neotropical insectivorous bats and, consequently, these traits are key to the interactions within the assemblage and with their prey.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.790

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 integrity0.0010.000
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 head0.017
GPT teacher head0.225
Teacher spread0.208 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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