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Effect of geographic isolation on genetic differentiation in<i>Dendroctonus pseudotsugae</i>(Coleoptera: Curculionidae)

2009· article· en· W2037091844 on OpenAlexaboutno aff
Enrico A. Ruíz, John E. Rinehart, Jane L. Hayes, Gerardo Zúñiga

Bibliographic record

VenueHereditas · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
FundersPacific Northwest Research StationConsejo Nacional de Ciencia y TecnologíaComisión Nacional Forestal
KeywordsCurculionidaeBiologyIsolation (microbiology)ZoologyBotanyEvolutionary biologyMicrobiology

Abstract

fetched live from OpenAlex

Genetic structure of phytophagous insects has been widely studied, however, relative influence of the effect of geographic isolation, the host plant or both has been subject of considerable debate. Several studies carried out on bark beetles in the genus Dendroctonus evaluated these factors; nonetheless, recent evidence has shown that genetic structuring is a more complex process. Our goal was to examine the effect of geographic isolation on genetic structure of the Douglas-fir beetle Dendroctonus pseudotsugae. We used mtDNA cytochrome oxidase I (COI) sequences and RAPD markers. One hundred-seventy-two individuals were obtained from 17 populations, for which we analyzed 60 haplotypes (among 172 sequences of COI gene, 550 bp long) and 232 RAPD markers (7 primers). Analyses of molecular variance (AMOVA and SAMOVA), F-statistics and linear regressions suggest that the genetic structure of D. pseudotsugae is strongly influenced by geographic distance. We found that D. pseudotsugae has high intra- and inter-population genetic variation compared with several other bark beetles. Genetic differences among populations based on COI and RAPD markers were correlated with geographic distance. The observed genetic differences between northern (Canada-USA) and southern (Mexico) populations on Pseudotsuga menziesii var. glauca confirm that these two sets of populations correspond to previously assigned subspecies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.286

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 head0.005
GPT teacher head0.209
Teacher spread0.204 · 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

Citations20
Published2009
Admission routes1
Has abstractyes

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