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Record W2074179467 · doi:10.1071/zo04080

Seasonal range variation of Tadarida australis (Chiroptera : Molossidae) in Western Australia: the impact of enthalpy

2005· article· en· W2074179467 on OpenAlexaff
R. D. Bullen, N. L. McKenzie

Bibliographic record

VenueAustralian Journal of Zoology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsDepartment of Environment and Conservation
Fundersnot available
KeywordsEnergeticsRange (aeronautics)Temperate climateZoogeographyLatitudeEcologyAbundance (ecology)Environmental scienceAtmospheric sciencesBiologyGeographyBiogeographyGeology

Abstract

fetched live from OpenAlex

The Australian bat Tadarida australis has a peculiar geographical niche that involves a continental-scale movement of over 10° of latitude in Western Australia. Its range expands northward by up to 1200 km for the winter and contracts southward for the summer. Its summer range limit correlates with an interaction of temperature and humidity, best summarised by atmospheric enthalpy. Its winter distribution is expanded northward within the enthalpy threshold, but appears to be further restricted in some areas by an unknown factor that may be biotic. We propose a potential competitor and a potential predator that may have strongly negative interactions in these regions. The 1% of records that are beyond the enthalpy envelope are from the change-over months and may be an artefact of year-to-year climatic variation. Three climatic thresholds enclose the enthalpy envelope: average annual rainfall >10 mm per month and <50 mm per month, and average overnight minimum temperature <20°C. Current literature relates migration of temperate-zone bats to resource availability as a consequence of changing season. We identify a tight correlation with atmospheric enthalpy that points to dissipation of flight muscle heat as a limiting factor.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.039
GPT teacher head0.288
Teacher spread0.249 · 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.

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

Citations29
Published2005
Admission routes1
Has abstractyes

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