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Record W2000874477 · doi:10.2980/18-4-3413

Behavioural responses of wintering porcupines to their heterogeneous thermal environment

2011· article· en· W2000874477 on OpenAlexaffvenueabout
Géraldine Mabille, Dominique Berteaux, Donald W. Thomas, Daniel Fortin

Bibliographic record

VenueEcoscience · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversité LavalUniversité de SherbrookeUniversité du Québec à Rimouski
Fundersnot available
KeywordsPorcupineEctothermMicroclimateThermoregulationPredationEcologyOperative temperatureBiologyEnvironmental scienceGeographyThermalMeteorology

Abstract

fetched live from OpenAlex

Many species use behavioural thermoregulation to cope with changes in their thermal environment. Most studies to date, however, have focused either on ectotherms or on endotherms living in warm environments. Here we used heated taxidermic mounts to characterize microclimates available to North American porcupines during the cold Canadian winter. We then examined activity patterns and microhabitat use of wild individuals to test whether porcupines responded behaviourally to changes in thermal conditions. Dens offered good protection against the cold, and porcupines modified their use of dens as thermal conditions became more constraining. They reduced time spent outside of dens, increased the number of activity bouts in a day, and became more diurnal. When outside of dens, they fed more often, but did not change their use of microhabitats as thermal conditions became most constraining. Microhabitats other than dens were less predictable in the protection they offered against cold temperatures. This may be why porcupines based their behavioural thermoregulation strategy on modulating patterns of den use rather than on selecting warmer microclimates when outside of the den. We hypothesize that selection of microhabitats outside of the den was driven by food acquisition or predation risk.

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 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 score0.008
Threshold uncertainty score0.999

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.215
Teacher spread0.174 · 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

Citations6
Published2011
Admission routes3
Has abstractyes

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