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Record W2119394914 · doi:10.1139/z05-141

Population genetic structure of tailed frogs (<i>Ascaphus truei</i>) in clearcut and old-growth stream habitats in south coastal British Columbia

2005· article· en· W2119394914 on OpenAlexvenueaboutno aff
Tanya Rhoda Wahbe, Carol Ritland, Fred L. Bunnell, Kermit Ritland

Bibliographic record

VenueCanadian Journal of Zoology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyBiological dispersalLoggingEcologyPopulationHabitatGene flowGenetic diversityGenetic structurePopulation bottleneckSTREAMSIsolation by distanceOld-growth forestMicrosatelliteDemography

Abstract

fetched live from OpenAlex

Ascaphus truei Stejneger, 1899 relies on cool, fast-flowing, forested mountain streams, which receive little protection from logging activities. During recovery of post-logging habitats, local extirpation of Ascaphus is a concern because their recolonization may be slow. In British Columbia, Oregon, and California, coastal Ascaphus populations are designated as "at risk". To infer fragmentation impacts from patterns of genetic structure, we used RAPD molecular markers and compared population genetic structures of Ascaphus larvae in an old growth with an adjacent clearcut stream located in coastal British Columbia. In the clearcut, larvae were less genetically diverse than in the old growth and exhibited no relationship between physical distance and genetic relatedness, whereas in the old growth, genetic similarity decreased with physical distance. Patterns of gene flow between the clearcut and old-growth streams were significantly different. The clearcut population went through a bottleneck/founding event, but also exhibited greater dispersal. The frogs were perhaps searching for new habitat (which would lower isolation by distance) and suffering mortality (which would decrease diversity). Most problems in conservation will require genetic and ecological data, and future research should aim to incorporate methodologies from both fields.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.004
GPT teacher head0.181
Teacher spread0.177 · 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

Citations9
Published2005
Admission routes2
Has abstractyes

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