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Record W2900696512

Winter Ecology and Ecophysiology of Prairie-Living Big Brown Bats (Eptesicus Fuscus)

2017· dissertation· en· W2900696512 on OpenAlexfundno aff
Brandon Jeremiah Baerwald

Bibliographic record

VenueoURspace (University of Regina) · 2017
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
FundersAlberta Conservation AssociationWildlife Conservation Society
KeywordsEptesicus fuscusEcophysiologyEcologyBiologyGeographyBotany
DOInot available

Abstract

fetched live from OpenAlex

Hibernation allows animals to survive lengthy periods of energetic deficit, but is not without costs. Hypometabolism, low body-temperature, and inactivity are associated with a variety of costs such as immuno-incompetence, dehydration, and build up of harmful metabolites. Additionally, conditions within hibernacula have a profound influence on hibernation patterns and survival. Periodic arousals and site selection are thought to mitigate these costs, and often involve timing arousals to foraging opportunities and overwintering in locations with stable temperatures and high humidity. I studied prairie-living big brown bats (Eptesicus fuscus) that overwinter in rock crevices and take flight outside of the hibernacula despite a lack of foraging opportunity. My goal was to describe their winter ecology and behaviour, and investigate reasons for winter flight. I found that E. fuscus in my study area use relatively dry hibernacula compared to known cavernous sites and show fidelity to sites between and within years. I found that temperature and wind are important predictors of winter flight, and that arousals remain under diurnal influence. My data suggest that individuals from this particular population spend the majority of their winter energy-stores during steady-state torpor and have mechanisms to decrease evaporative water loss during hibernation. I found typical levels of dehydration as winter progressed and my data indicate no use by bats of a supplemental water source. My research elucidates novel behaviours and traits of this population of E. fuscus, and reduces the paucity of knowledge about winter bat-ecology in the prairies.

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 score0.482
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.201
Teacher spread0.188 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

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