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Record W2015542860 · doi:10.1139/z09-010

Ambient temperature is more important than food availability in explaining reproductive timing of the bat Sturnira lilium (Mammalia: Chiroptera) in a montane Atlantic Forest

2009· article· en· W2015542860 on OpenAlexvenueno aff
Marco A. R. Mello, Elisabeth K. V. Kalko, W.R. Silva

Bibliographic record

VenueCanadian Journal of Zoology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
FundersUniversität UlmUniversidade Estadual de Campinas
KeywordsBiologyReproductionEcologyFrugivoreMontane ecologyReproductive successZoologyHabitatPopulation

Abstract

fetched live from OpenAlex

Reproduction of bats is determined by a suite of endogenous and exogenous factors. Among exogenous influences, special attention has been given to the influence of food availability. However, in highland forests, severe decreases in temperature during the cold and dry season may also play an important role. In the present study we tested the influence of ambient temperature and food availability on the timing of reproduction in the frugivorous bat Sturnira lilium (E. Geoffroy, 1810). We conducted a 15-month mist-netting sampling in a mountain area of the Brazilian Atlantic Forest during which time we assessed the bats’ diet through fecal samples, monitored fruit production of the main food plants, and recorded variations in ambient temperature. Sturnira lilium fed almost exclusively on Solanaceae. Similarly to the lowlands, reproduction was bimodal, but reproductive season tended to be shorter in the highlands and peaked in the warmer months of the year. Overall, 44% to 53% of the reproductive pattern was explained by variations in ambient temperature, while the relationship with food availability was nonsignificant. We conclude that variations in ambient temperature in tropical mountains may be a stronger selection pressure than food availability in determining reproductive timing of bats.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.708

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 integrity0.0000.001
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 head0.208
Teacher spread0.191 · 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

Citations45
Published2009
Admission routes1
Has abstractyes

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