Resistance of Sitka spruce (Picea sitchensis (Bong.) Carr.) to white pine weevil (Pissodes strobi Peck): characterizing the bark defence mechanisms of resistant populations
Bibliographic record
Abstract
It has long been known that strong expressions of resistance to the white pine weevil (Pissodes strobi Peck) exist in certain Sitka spruce (Picea sitchensis (Bong.) Carr.) populations, particularly among trees originating from the Fraser Valley and the Qualicum area of British Columbia (BC). In this paper, we characterize how resistance is manifested in these known resistant populations. Specifically, using cloned individuals, we investigated resistant traits associated with repellency, constitutive resin canals (CRC) and sclereid or stone cells. Results indicate significant population differences in the level of these traits between these two populations and susceptible populations. Fraser Valley populations had four times the sclereid density of susceptible populations. Although the Big Qualicum (East Vancouver Island) population had the same high resistance as the Haney (Fraser Valley) population, it was expressed primarily through increased CRC. Sclereid cell density had the strongest correlation to weevil attack followed by CRC. We discuss pathways by which two distinct resistant populations may have developed in this high weevil hazard region of south-west BC.
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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 | 0.000 | 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".