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Record W2170748035 · doi:10.3732/ajb.89.4.642

Clonal structure and hybrid susceptibility to a smut pathogen in microscale hybrid zones of northern wetland <i>Carex</i> (Cyperaceae)

2002· article· en· W2170748035 on OpenAlexaffabout
Eliot J. B. McIntire, Marcia J. Waterway

Bibliographic record

VenueAmerican Journal of Botany · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiologySmutHybridCarexEcologyHybrid zoneBotanyGene flowGenetic variationGenetics

Abstract

fetched live from OpenAlex

Interspecific hybrid taxa, especially those with the potential for clonal spread, may play important roles in community dynamics and plant-pathogen interactions. This study combines the mapping of clonal structure for two rhizomatous sedges (Carex limosa, C. rariflora) and their nearly sterile interspecific hybrid with an investigation of the relationship between these taxa and a nonsystemic floral smut pathogen (Anthracoidea limosa) in six subarctic fens in Nouveau-Québec, Canada. We used allozyme polymorphisms in 14 of 18 putative loci to confirm hybrid identification and to distinguish among genotypes for mapping. The incidence of A. limosa was 5-20 times greater on hybrids than on parental taxa across all sites at two spatial scales (intensive extent = 10.5 m(2), extensive extent = entire fens). Spatial autocorrelation was detected in smut incidence; however, its statistical removal did not alter the strong association between hybrids and smut infection. Smut incidence on both C. limosa and hybrids was greater when they were growing in areas of high hybrid density. Our study provides evidence that disease can help maintain boundaries between species. We suggest explanations for hybrid susceptibility and provide evidence for a model in which hybrids act as a source for reinfection for all three taxa during subsequent years.

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 score0.190
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.202
Teacher spread0.191 · 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

Citations24
Published2002
Admission routes2
Has abstractyes

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