Drought stress leads to systemic induced susceptibility to a nectrotrophic fungus associated with mountain pine beetle in Pinus banksiana seedlings
Bibliographic record
Abstract
Conifers have complex defense responses to initial attacks by insects and pathogens that can have cascading effects on success of subsequent colonizers. However, drought can affect a plant's ability to respond to biotic agents by potentially altering the resources needed for the energetically costly production of induced defense chemicals. We investigated the impact of reduced water on induced chemical defenses of jack pine (Pinus banksiana) seedlings from initial attack by biotic agents and resistance to subsequent challenge inoculation with a pathogenic fungal associate of mountain pine beetle (Dendroctonus ponderosae), Grosmannia clavigera. Applications of phytohormones (methyl salicylate and methyl jasmonate) and G. clavigera were used for initial induction of defenses. Monoterpene concentrations varied with initial induction from fungal and phytohormone application while watering treatment had no effect. Seedlings treated with G. clavigera and methyl jasmonate had the greatest monoterpene concentrations compared to the control and methyl salicylate-treated seedlings. However, the monoterpene response to the challenge inoculation varied with watering treatments, not with prior induction treatments, with lower monoterpene concentrations in fungal lesions on seedlings in the low to moderate watering treatments compared to normal watering treatment. Furthermore, prior induction from phytohormones resulted in systemic cross-induction of resistance to G. clavigera under normal watering treatment but susceptibility under low watering treatment. Seedlings stressed by low water conditions, which also had lower stomatal conductance than seedlings in the normal watering treatment, likely allocated resources to initial defense response but were left unable to acquire further resources for subsequent responses. Our results demonstrate that drought can affect interactions among tree-infesting organisms through systemic cross-induction of susceptibility.
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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".