The relationship between ice thickness and northern hardwood tree damage during ice storms
Bibliographic record
Abstract
The response of four tree species, Acer saccharum Marsh., Acer rubrum L., Populus tremuloides Michx., and Betula populifolia Marsh., to ice storm damage was studied in the northern hardwood forest of southern Quebec. The focus of the study was the impact of ice accretion on trees as a function of damage type and species at the stand and regional scales along a gradient of ice accumulation ranging from 2 to 88 mm radial thickness and to assess the role of the combined effect of ice and wind stress. Further, we estimate the return time for death resulting from ice storms in these forests. The study showed that the magnitude of ice accumulation was the primary determinant of tree damage (measured as the mean percentage of individual tree canopy removed) and that tree size was the primary determinant of damage type (bending, snapping, or substantial branch loss). Stand position (edge versus interior) did not influence susceptibility to damage. The research demonstrated that edge and slope trees bent or snapped in the direction dictated by crown asymmetry. We have no evidence that the modest winds during this icing event played a major role. Lastly, we couple the return time for a given ice thickness with the probability of severe damage to argue that (i) canopy tree mortality from icing is primarily due to glaze accumulations of moderate rarity (around 1235 mm of ice) rather than extraordinary events such as 1998 and (ii) ice storms are likely the greatest single source of canopy tree mortality in the hardwood forests of southern Quebec with an estimated return time for death of about 250 years.
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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".