Relative abundance and potential dispersal range of intersterility groups of <i>Heterobasidion annosum</i> in pure and mixed forests
Bibliographic record
Abstract
In Europe the forest pathogen Heterobasidion annosum (Fr.) Bref. includes the S, P, and F intersterility groups (ISGs), each displaying a preferential specialization on Norway spruce (Picea abies (L.) Karst.), pine, and silver fir (Abies alba Mill.), respectively. In this paper, we present data about (i) H. annosum ISGs frequency in different forest types, (ii) the degree of host specificity of each ISG, (iii) the significance of the potential movement of airborne spores among forests, and (iv) the occurrence of SP chimeras in the northwestern Alps. Using woody spore traps, we sampled natural pure spruce and fir forests and a mixed spruce-fir forest. The ISG of 582 spores was determined by ISG-diagnostic taxon-specific competitive priming (TSCP) polymerase chain reaction (PCR) combined with PCR-mediated detection of ISG-specific introns in the ML5ML6 DNA region of the mitochondrial large ribosomal RNA (mt LrRNA). All three ISGs were found, and a strong correlation was observed between the F ISG and fir and the S ISG and spruce. In the mixed forest, no clear relationship between tree host species and host-specialized ISGs was found. In spite of a relative dominance of fir in the overstory of the mixed stand, the fir-associated F ISG represented only 11% of the total number of spores collected. This discrepancy was explained by the recent establishment of firs at this site. No SP nuclear-mitochondrial chimeras were found. This suggests limited gene flow between these ISGs.Key words: Heterobasidion annosum, host specificity, ISGs, gene flow, PCR, Alps.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".