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Contrasted thermal preferences translate into divergences in habitat use and realized performance in two sympatric snakes

2011· article· en· W2118601786 on OpenAlexaff
Hervé Lelièvre, Gabriel Blouin‐Demers, David Pinaud, Hélène Lisse, Xavier Bonnet, Olivier Lourdais

Bibliographic record

VenueJournal of Zoology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEctothermSympatric speciationBiologyThermoregulationEcologyHabitatTemperate climateForagingNatrixZoology

Abstract

fetched live from OpenAlex

Temperature influences ectotherm fitness by affecting physiological performance. Terrestrial reptiles behaviourally regulate their body temperature by selecting particular microhabitats or activity periods. In temperate climates, thermal constraints make precise thermoregulation costly. Theoretical models of thermoregulation predict that species in cool environments should exhibit lower optimal temperature for performance and lower thermal preferences to minimize thermoregulatory costs. Empirical data in support of this prediction remain equivocal because several species maintain high and constant body temperatures, even in cool environments. We studied two largely sympatric colubrid snakes, Hierophis viridiflavus and Zamenis longissimus that share numerous morphological and ecological similarities, but differ markedly in thermal preference. Our objective was to quantify their thermoregulatory strategies in the field to determine how thermal preferences translate in habitat use and performance gain. The thermophilic species, H. viridiflavus, selected open microhabitats, whereas Z. longissimus, which prefers cooler temperatures, used a greater diversity of microhabitats. The two species differed markedly in their exposure levels. Hierophis viridiflavus was constrained to shuttle between sun and shade to maintain preferred body temperatures rendering it very exposed, while covered microhabitats were usually thermally compatible with the requirements of Z. longissimus. High exposure was apparently counterbalanced by higher locomotor performances in H. viridiflavus. The divergence in thermal ecology between Z. longissimus and H. viridiflavus likely reflects different trade-offs between energy gain and predator avoidance.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.434

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)0.0000.000

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 head0.244
Teacher spread0.219 · 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

Citations50
Published2011
Admission routes1
Has abstractyes

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