Health of Eastern North American Sugar Maple Forests and Factors Affecting Decline
Bibliographic record
Abstract
Abstract Sugar maple (Acer saccharum) is a keystone species in the forests of the northeastern and midwestern United States and eastern Canada. Its sustained health is an important issue in both managed and unmanaged forests. While sugar maple generally is healthy throughout its range, decline disease of sugar maple has occurred sporadically during the past four decades; thus, it is important to understand the abiotic and biotic factors contributing to sugar maple health. Soil moisture deficiency or excess, highway deicing salts, and extreme weather events including late spring frosts, midwinter thaw/freeze cycles, glaze damage, and atmospheric deposition are the most important abiotic agents. Defoliating insects, sugar maple borer (Glycobius speciosus), Armillaria root disease, and injury from management activities represent important biotic factors. Studies of sugar maple declines over the past four decades reveal that nutrient deficiencies of magnesium, calcium, and potassium; insect defoliation; drought; and Armillaria were important predisposing, inciting, and contributing factors in sugar maple declines. Forestland managers can contribute to sustained health of sugar maple by choosing appropriate sites for its culture, monitoring stress events, and examining soil nutrition.
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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 | 0.001 | 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".