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Record W2045327926 · doi:10.1139/z09-049

Behavioral response of migrating wood frogs to experimental timber harvest surrounding wetlands

2009· article· en· W2045327926 on OpenAlexvenueno aff
Tracy A. G. Rittenhouse, Raymond D. Semlitsch

Bibliographic record

VenueCanadian Journal of Zoology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsHabitatBiologyEcologyPredationWildlifeWildlife conservation

Abstract

fetched live from OpenAlex

Behavioral responses to ecological disturbances such as timber harvest, fire, or drought provide insight into wildlife habitat requirements. To determine the behavioral response of adult wood frogs ( Lithobates sylvatica (LeConte, 1825)) to timber harvest in oak–hickory forest, we conducted experimental timber harvest surrounding replicate breeding sites, monitored freely moving frogs using radiotelemetry, and tested the repeatability of behavioral responses with two experimental displacements. We found no evidence that wood frogs use recent oak–hickory clearcuts as habitat. Timber harvest was not a complete barrier to movement, as frogs surviving increased predation and desiccation risks reached drainages used as nonbreeding habitat. Frogs did not alter the direction of travel and traversed similar distances (i.e., total distance and net distance from breeding site) before and after timber harvest. However, rate of travel (i.e., maximum distance traversed in 1 day) increased following timber harvest and frogs displaced to the center of clearcuts exited the timber harvest array in one rainy night. Notably, wood frogs following displacement exhibited site fidelity to nonbreeding habitat. We suggest that deleterious effects of timber harvest on amphibians may be minimized through the use of small stand sizes placed in locations that do not separate breeding and nonbreeding habitat.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.998
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.018
GPT teacher head0.261
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), 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

Citations37
Published2009
Admission routes1
Has abstractyes

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