The Role of Forest Tent Caterpillar Defoliations and Partial Harvest in the Decline and Death of Sugar Maple
Bibliographic record
Abstract
BACKGROUND AND AIMS: Natural and anthropogenic disturbances can act as stresses on tree vigour. According to Manion's conceptual model of tree disease, the initial vigour of trees decreases as a result of predisposing factors that render these trees more vulnerable to severe inciting stresses, stresses that can then cause final vigour decline and subsequent tree death. This tree disease model was tested in sugar maple (Acer saccharum) by assessing the roles of natural and anthropogenic disturbances in tree decline and death. METHODS: Radial growth data from 377 sugar maple trees that had undergone both defoliations by insects and partial harvest were used to estimate longitudinal survival probabilities as a proxy for tree vigour. Radial growth rates and survival probabilities were compared among trees subjected to different levels of above- and below-ground disturbances, between periods of defoliation and harvest, and between live and dead trees. KEY RESULTS: Manion's tree disease model correctly accounts for vigour decline and tree death in sugar maple; tree growth and vigour were negatively affected by a first defoliation, predisposing these trees to death later during the study period due to a second insect outbreak that initiated a final vigour decline. This decline was accelerated by the partial harvest disturbance in 1993. Even the most severe anthropogenic disturbances from partial harvest did not cause, unlike insect defoliation, any growth or vigour declines in live sugar maple. CONCLUSIONS: Natural disturbances acted as predisposing and inciting stresses in tree sugar maple decline and death. Anthropogenic disturbances from a partial harvest at worst accelerated a decline in trees that were already weakened by predisposing and inciting stresses (i.e. repeated insect defoliations). Favourable climatic conditions just before and after the partial harvest may have alleviated possible negative effects on growth resulting from harvesting.
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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 | 0.001 |
| 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 | 0.000 |
| 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".