Lodgepole pine provenances differ in chemical defense capacities against foliage and stem diseases
Bibliographic record
Abstract
Maximization of lodgepole pine ( Pinus contorta Douglas ex Louden var. latifolia Engelm. ex S. Watson) growth in a future climate with increased pest activity requires an understanding of the natural variability of quantitative resistance to disease. Foliar and bark secondary metabolites from different lodgepole pine provenances (populations) were quantified and correlated with severity of foliar diseases caused by Lophodermella spp. ( Lophodermella concolor (Dearn.) Darker or Lophodermella montivaga Petre.) or Elytroderma deformans (Wier) Darker and bark diseases caused by Elytroderma or Endocronartium harknessii (J.P. Moore) Y. Hiratsuka. Greater foliar concentrations of lignin, tannins, and some phenolics were associated with increased resistance to single or multiple foliar pathogens. Bark secondary metabolites levels were generally unassociated with resistance to bark diseases. Provenances appearing to originate in ecosystems where lodgepole pine are not the dominant species generally were more susceptible to foliar diseases and had less foliar defense-associated compounds than trees from areas where pines were the dominant species, yet clear trends proved to be elusive. Regardless, pine provenances with greater foliar levels of identified defense-associated compounds should be preferred seed sources for replanting forests in areas in which foliar disease is expected to be increasingly prevalent.
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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 | 0.000 |
| 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".