Mountain pine beetle‐associated blue‐stain fungi are differentially adapted to boreal temperatures
Bibliographic record
Abstract
Summary Mountain pine beetles (MPB) are the most serious pest of lodgepole pine in Canada and are likely to invade boreal jack pine forests. MPB vector three blue‐stain fungi, Grosmannia clavigera, Ophiostoma montium and Leptographium longiclavatum, which contribute to beetle success. Fungal survival at extreme boreal temperatures will contribute to their success in jack pine. Growth, sporulation and survival of the three fungi at −20 to 37°C were tested in vitro. Overwintering survival of G. clavigera and O. montium was assessed in vivo. All species grew at 5–30°C, with optimal growth at 20–25°C. Grosmannia clavigera and L. longiclavatum survived at −20°C, but O. montium died. Growth of G. clavigera and L. longiclavatum was inhibited at 30°C, but O. montium grew well. Grosmannia clavigera and O. montium overwintered in living pines. These results suggest that G. clavigera and L. longiclavatum were adapted to cold boreal winters but not hot summers, with the converse true for O. montium. Temperature tolerance varied among G. clavigera isolates. British Columbian and Californian isolates grew faster at 25°C than Albertan isolates. Isolates from Alberta and Idaho/Montana grew optimally at 20°C, while British Columbian and Californian isolates grew optimally at 25°C.
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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 | 0.000 | 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) | 0.001 | 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".