Responses of Engelmann spruce to inoculation with <i>Leptographium abietinum</i>, a symbiotic fungus of the North American spruce beetle
Bibliographic record
Abstract
Symbiotic fungi associated with tree-killing bark beetles can alter host-tree physiology with consequences for tree survival, and symbiont genetic variation and environmental variability may impact these interactions. Here, we test whether multiple genetically distinct isolates of a symbiotic fungus (Leptographium abietinum (Peck) M.J. Wingf.) associated with North American spruce beetle (Dendroctonus rufipennis (Kirby, 1837)) vary in their ability to manifest defensive responses consistent with disease symptoms in seedlings of Engelmann spruce (Picea engelmannii Parry ex Engelm.), a primary host-tree species for the beetle–fungus complex in North America. Our experiments incorporate variation in both host-tree water availability and host defenses (phloem monoterpene concentration). Three central findings emerged: (i) isolates varied considerably in their effects on host trees — inoculation with L. abietinum isolates from Colorado caused significantly larger phloem lesions than isolates from Wyoming, though all isolates caused phloem oxidation; (ii) neither water availability nor spruce phloem monoterpene concentrations impacted lesion formation; and (iii) both inoculation with L. abietinum and water deficit inhibited the formation of callus tissue at wound sites. We conclude that L. abietinum isolates vary in their virulence and that inoculation is not lethal but may benefit beetles by altering tree defensive responses.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".