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Record W2116448292 · doi:10.1139/z06-124

Intraspecific and interspecific variation in use of forest-edge habitat by snakes

2006· article· en· W2116448292 on OpenAlexvenueaboutno aff
Gerardo L.F. Carfagno, Patrick J. Weatherhead

Bibliographic record

VenueCanadian Journal of Zoology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceNature ConservancyIllinois Department of Natural Resources
KeywordsPredationIntraspecific competitionHabitatEcologyBiologyNest (protein structural motif)Interspecific competitionHabitat fragmentationFragmentation (computing)ForagingForest fragmentation

Abstract

fetched live from OpenAlex

Variation in use of edge habitat among populations and species of snakes should reflect underlying causes (e.g., thermal ecology, prey availability) and consequences (e.g., predation on birds' nests) of habitat selection. We compared the habitat use of ratsnakes, Elaphe obsoleta (Say in James, 1823), in Illinois and Ontario and compared habitat use by ratsnakes and racers, Coluber constrictor (L., 1758), in Illinois. Ratsnakes in Illinois used upland forest more and forest edges less than ratsnakes in Ontario. Female ratsnakes in Illinois used edges less than males, regardless of their reproductive status. Relative to ratsnakes, racers preferred forest edges and avoided forest interior. Female racers used edges more than males, especially while gravid. These results, and most of the seasonal patterns in habitat use, were broadly consistent with variation expected from differences in thermoregulatory needs, although other factors potentially influencing habitat use cannot be ruled out. Although it has been proposed that some forest fragmentation is likely to be beneficial for ratsnakes in Canada, such fragmentation may be detrimental to ratsnakes in Illinois but beneficial to racers. Thus, relative to forest-interior species, edge-nesting birds should be more vulnerable to predation by ratsnakes in Ontario, and fragmentation should increase the vulnerability of forest birds to nest predation by racers.

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 score0.409
Threshold uncertainty score0.988

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)0.0010.000

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 head0.011
GPT teacher head0.191
Teacher spread0.181 · 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

Citations63
Published2006
Admission routes2
Has abstractyes

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