Foliar nutrients and induced susceptibility: genetic mechanisms of Douglas-fir resistance to western spruce budworm defoliation
Bibliographic record
Abstract
We conducted greenhouse defoliation experiments with clones of interior Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn.) Franco) over 3 years to assess the role of foliar nutrients as a resistance mechanism to western spruce budworm (Choristoneura occidentalis Freeman) defoliation. The grafted clones were derived from mature trees (i.e., ortets) that showed resistance or susceptibility to budworm defoliation in the forest. Current-year foliage was analyzed for concentrations of nitrogen (N), sugars (sucrose + fructose + glucose), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), manganese (Mn), copper (Cu), iron (Fe), and zinc (Zn). We computed rank correlations between foliar nutrient levels in the ortets and their corresponding clones to test the null hypothesis that foliar chemistry does not have a genetic basis (H01). Foliar concentrations of sugars and P were under genetic control to some degree, but concentrations of other nutrients were not. We used analysis of variance to test the null hypotheses that foliar chemistry does not change in response to budworm defoliation (H02) and that it is not different between resistant and susceptible clones (H03). We rejected H02 for sugars, P, K, Mn, and Zn; defoliation by the budworm changed levels of these nutrients and had divergent effects on concentrations of P, K, and Zn in resistant clones. We concluded that induced susceptibility, whereby defoliation alters foliar nutrients to make trees more favorable for insect feeding, appears to be an important determinant of Douglas-fir resistance to the western spruce budworm. Failure to reject H03 implies that previously reported differences between the foliar nutrient levels in resistant Douglas-firs and those in susceptible Douglas-firs in the forest are probably caused by induced susceptibility.
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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".