A Pine in Distress: How Infection by Different Pathogenic Fungi Affect Lodgepole Pine Defenses
Bibliographic record
Abstract
Abstract In North America, lodgepole pine is frequently subjected to attacks by various biotic disturbances that compromise its ability to defend against subsequent attacks by insect herbivores. We investigated whether infections of lodgepole pine by different pathogenic fungal species have varying effects on its defense chemistry. We selected two common pathogens: Atropellis canker and western gall rust, affecting mature lodgepole pine trees in western Canada. We also included three ophiostomoid fungi associated with the mountain pine beetle, Grosmannia clavigera, Ophiostoma montium, and Leptographium longiclavatum because symbiotic fungi are commonly used to investigate induced defenses of host trees of bark beetles. We collected phloem samples from lodgepole pine trees infected with the rust or the canker, and healthy lodgepole pine trees in the same stand. We also inoculated mature lodgepole pine trees with the three fungal symbionts and collected phloem two weeks later when the defense chemistry at its highest level. All samples were analyzed for their terpene composition in gas chromatograph/mass spectrometry. Different pathogenic fungal species differentially altered the terpene chemistry of lodgepole pine trees. Western gall rust and the beetle-fungal symbionts altered the tree terpene chemistry in a similar fashion while trees responded to the infection by the Atropellis canker differently. Our study highlights the importance of considering specific biotic stress agents in tree susceptibility or resistance to the subsequent biotic attacks by insect herbivores, such as mountain pine beetle.
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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".