Production of complementary defense metabolites reflects a co‐evolutionary arms race between a host plant and a mutualistic bark beetle‐fungal complex
Bibliographic record
Abstract
Intra-specific variation in conifers has been extensively studied with respect to defense against herbivores and pathogens. While studies have shown the ability of individual or specific mixtures of compounds to influence insects and microbes, research testing biologically relevant mixtures of defense compounds reflecting intra-specific variation amongst tree populations to enemy complexes is needed. We characterized the variations in lodgepole pine monoterpenes from a progeny trial in western Canada and grouped trees in four clusters using their monoterpene profiles. We then selected 11 representative families across four clusters and amended their entire monoterpene profiles (with the exception of β-phellandrene) in media to determine how representative families affect the performance of the mountain pine beetle or its fungal symbiont. We placed adult beetles or inoculated fungus on the amended media and measured beetle performance and fungal growth as a proxy to host suitability. We found that different clusters or families differentially influenced beetle or fungal responses. However, monoterpene profiles of trees suitable to the beetle or the fungus were dissimilar. These outcomes reflect a co-evolutionary arms-race between the host and the bark beetle-fungus complex, which has resulted in the production of complementary defense metabolites among different pine populations to enhance tree survival.
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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".