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Day roost characteristics of northern long-eared bats (Myotis septentrionalis) in relation to female reproductive status

2008· article· en· W2141970399 on OpenAlexaffvenue
Colin J. Garroway, Hugh G. Broders

Bibliographic record

VenueEcoscience · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsBiologyEcologyDeciduousTorporPopulationReproductionTemperate rainforestDiameter at breast heightDemographyThermoregulationEcosystem

Abstract

fetched live from OpenAlex

(Uploaded by Plazi for the Bat Literature Project) In summer, females of most temperate bat species aggregate at maternity roosts, during which time females gestate, give birth, and wean offspring. These activities make the presence of suitable roosts critical for population persistence. Many studies have identified important roost tree characteristics by comparing roost trees to random trees. However, if bats select trees that facilitate either torpor use or maintenance of normothermic body temperatures relative to the energetic demands of reproduction, then it follows that roost tree characteristics may vary similarly. We compared variation in roost tree and site selection by lactating northern long-eared bats to the pre- and post-lactation periods. Scores from 2 principal components were the best predictors of the variation in roost selection. Relative to pre- and post-lactation periods lactating bat roost sites had a high and relatively open dominant canopy with low tree density (both coniferous and deciduous) and roost sites were situated high in tall trees. Our result demonstrates that when managing for bat roost trees, within-season variation in roost tree use should be considered.

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)0.001
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 score0.012
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.026
GPT teacher head0.224
Teacher spread0.198 · 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

Citations43
Published2008
Admission routes2
Has abstractyes

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