Beech bark disease in northern hardwood forests: the importance of nitrogen dynamics and forest history for disease severity
Bibliographic record
Abstract
Beech bark disease has been a major cause of mortality of American beech (Fagus grandifolia Ehrh.) in North America during the past century. Previous studies have suggested a positive relationship between disease severity and both bark nitrogen content and tree size, presumably due to higher rates of infestation by beech scale insects, which allow more extensive infection of the tree by Nectria fungi. Recent concerns about nitrogen saturation in northeastern forests, particularly in old-growth forests, led us to examine patterns of disease severity as a function of bark tissue nitrogen content in old-growth and second-growth forests in the Adirondack region of New York and northern Maine. Trees growing in old-growth stands possessed significantly higher levels of bark nitrogen than similarly sized trees in second-growth forests. The severity of disease symptoms was more acute in the old-growth forests and was positively correlated with the percent nitrogen of the bark in both forest types. Comparisons of the coefficients of variation between beech bark sampled from disease-free forests in the upper peninsula of Michigan and that sampled from diseased forests indicated that elevated bark nitrogen concentrations in diseased trees were a cause and not an effect of disease presence. While there was no difference in disease severity between control and nitrogen-fertilized forests in Maine, these forests had both been exposed to the disease for longer time periods than the other studied forests and they are likely approaching nitrogen saturation.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".