Variations in foliar monoterpenes across the range of jack pine reveal three widespread chemotypes: implications to host expansion of invasive mountain pine beetle
Bibliographic record
Abstract
The secondary compounds of pines (Pinus) can strongly affect the physiology, ecology and behaviors of the bark beetles (Coleoptera: Curculionidae, Scolytinae) that feed on sub-cortical tissues of hosts. Jack pine (Pinus banksiana) has a wide natural distribution range in North America (Canada and USA) and thus variations in its secondary compounds, particularly monoterpenes, could affect the host expansion of invasive mountain pine beetle (Dendroctonus ponderosae), which has recently expanded its range into the novel jack pine boreal forest. We investigated monoterpene composition of 601 jack pine trees from natural and provenance forest stands representing 63 populations from Alberta to the Atlantic coast. Throughout its range, jack pine exhibited three chemotypes characterized by high proportions of α-pinene, β-pinene, or limonene. The frequency with which the α-pinene and β-pinene chemotypes occurred at individual sites was correlated to climatic variables, such as continentality and mean annual precipitation, as were the individual α-pinene and β-pinene concentrations. However, other monoterpenes were generally not correlated to climatic variables or geographic distribution. Finally, while the enantiomeric ratios of β-pinene and limonene remained constant across jack pine's distribution, (-):(+)-α-pinene exhibited two separate trends, thereby delineating two α-pinene phenotypes, both of which occurred across jack pine's range. These significant variations in jack pine monoterpene composition may have cascading effects on the continued eastward spread and success of D. ponderosae in the Canadian boreal forest.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".