Tree Diversity has Limited Effects on Beech Bark Disease Incidence in American Beech Population of Mont St-Hilaire
Bibliographic record
Abstract

 
 
 
 Background: American beech trees (Fagus gandifolia) exist in many areas in northeastern North America. Beech bark disease (BBD) is caused by a scale insect and bark-killing fungus (Cryptococcus fagisuga and Nectria spp.). We aim to study the correlation between diversity and the presence of BBD, and predict that tree diversity in Gault’s Nature Reserve in Mont St-Hilaire (MSH), Québec decreases the presence of BBD and that F. grandifolia density would increase the presence of this disease.
 Methods: We randomly chose 15 sites for sampling of individual tree species. F. grandifolia trees were identified as “healthy” or “infected”. Simple regressions, ANOVA, two and three-way interaction, linear mix effect model, and paired t-test were performed using R and Excel.
 Results: Our results show no significant correlation of infected individuals and total number of either A. saccharum or A. pensylvanica, unless analyzed with a linear mixed effect model (p=0.0256). However, there was a strong, positive correlation between the number of infected trees and the density of F. grandifolia (R2=0.6712), and this relationship was stronger in disturbed areas compared to undisturbed areas in the reserve (t=2.0492, p=0.047, tcritical=2.0211).
 Conclusion: We found beech tree density and habitat disturbance, but not community diversity, to have a significant positive effect on Beech Bark Disease infection rates.
 
 
 
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".