Tamm review: The impact of forest tent caterpillar defoliation on maple fitness and syrup production
Bibliographic record
Abstract
The forest tent caterpillar ( Malacosoma disstria Hübner) is a major defoliator of sugar maple ( Acer saccharum Marsh.) stands, with recurrent outbreaks that can impact tree growth and health, while posing a significant challenge as well to the maple syrup industry. Severe and prolonged outbreaks can weaken trees, potentially reducing growth rates and increasing their susceptibility to secondary stressors, such as other pests and diseases, with possible implications for long-term stand biomass productivity. This review examines the effects of defoliation on sugar maple physiology, focusing on sap exudation dynamics, sugar concentration, and tree health. It also explores the potential compounding effects of tapping during outbreak years and the role of starch reserves in tree survival. Additionally, we provide broader perspectives on sugarbush management strategies, such as species composition and stand structure adjustments in mitigating forest tent caterpillar damage and spread. Future research should aim to deepen our understanding of the physiological effects of defoliation to support the establishment of clear guidelines for tapping defoliated trees as well as explore adaptive silvicultural strategies to increase sugarbush resilience in the face of recurrent outbreaks of the forest tent caterpillar. • Sap yield and sugar content response to defoliation have limited empirical evidence. • Defoliation alters carbohydrates annual dynamics in maples. • Early defoliation impacts differ from late-season leaf loss.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".