Clonal structure and hybrid susceptibility to a smut pathogen in microscale hybrid zones of northern wetland <i>Carex</i> (Cyperaceae)
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".