Insect herbivory (Choristoneura fumiferana, Tortricidea) underlies tree population structure (Picea glauca, Pinaceae)
Bibliographic record
Abstract
Variation in insect herbivory can lead to population structure in plant hosts as indicated by defence traits. In annual herbaceous, defence traits may vary between geographic areas but evidence of such patterns is lacking for long-lived species. This may result from the variety of selection pressures from herbivores, long distance gene flow, genome properties, and lack of research. We investigated the antagonistic interaction between white spruce (Picea glauca) and spruce budworm (SBW, Choristoneura fumiferana) the most devastating forest insect of eastern North America in common garden experiments. White spruces that are able to resist SBW attack were reported to accumulate the acetophenones piceol and pungenol constitutively in their foliage. We show that levels of these acetophenones and transcripts of the gene responsible for their release is highly heritable and that their accumulation is synchronized with the most devastating stage of SBW. Piceol and pungenol concentrations negatively correlate with rate of development in female SBW and follow a non-random geographic variation pattern that is partially explained by historical damage from SBW and temperature. Our results show that accumulation of acetophenones is an efficient resistance mechanism against SBW in white spruce and that insects can affect population structure of a long-lived plant.
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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 | 0.000 |
| 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".