Host genetics and environment shape fungal pathogen incidence on a foundation forest tree species, <i>Populus tremuloides</i>
Bibliographic record
Abstract
Diseases can markedly alter the ecological and economic value of poplars. To better understand poplar–pathogen interactions, we investigated the independent and interactive effects of tree genotype, soil nutrient limitation, and interspecific competition on incidence of powdery mildew (caused by the fungal obligate pathogen Erysiphe adunca (Wallr.) Fr., 1829) in a foundation tree species, trembling aspen (Populus tremuloides Michx.). We established a common garden of potted aspen saplings, incorporating five tree genotypes, two levels of soil nutrients (low and high), and two levels of competition (with and without grass). We then surveyed natural incidence of powdery mildew and aspen vigor (i.e., growth). Incidence of powdery mildew varied among aspen genotypes, and variance in incidence shifted among environments in which the trees were grown. Added soil nutrients increased powdery mildew incidence on aspen, whereas grass competition had the opposite effect. Interestingly, grass competition either enhanced or dampened the variance in incidence of powdery mildew among tree genotypes, depending on soil nutrient levels. In addition, powdery mildew incidence was positively related to tree vigor. Our findings reveal strong genetic, environmental, and genetic×environmental effects of disease on a foundation tree species and that particular environments can either enhance or diminish variation in responses among tree genotypes.
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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".