Beech bark disease: spatial patterns of thicket formation and disease spread in an aftermath forest in the northeastern United States
Bibliographic record
Abstract
Beech bark disease (BBD) has affected the composition, structure, and function of forests containing a significant proportion of American beech (Fagus grandifolia Ehrh.) across North America. BBD spread has been investigated at landscape and regional scales, but few studies have examined spatial patterns of disease severity and spread within stands where forest management mitigation measures can be implemented. We analyzed changes in forest composition between 1985 and 2009 and fine-scale spatial patterns of BBD between 2000 and 2009 in a ∼2 ha northern hardwood stand in the Adirondack Mountains of New York using location and disease severity of beech trees. A bivariate point pattern analysis was implemented to examine spatial patterns of beech thicket formation and BBD spread to beech saplings. Abundance of beech saplings increased near highly diseased canopy beech trees and around dead beech and sugar maple (Acer saccharum Marsh.). Disease severity of beech saplings was highest in close proximity to highly cankered canopy beech trees. Thus, BBD leads to the formation of beech thickets, and thickets are often located where saplings are most likely to become infected, increasing the likelihood that secondary killing fronts will develop and lead to heavy BBD-induced mortality in aftermath northern hardwood forests of North America.
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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 | 0.000 |
| 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) | 0.000 | 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".