Patterns of damage and mortality in red pine plantations following a major ice storm
Bibliographic record
Abstract
The impact of a major ice storm in eastern Ontario on 28 pine plantations (red pine, Pinus resinosa Ait.; Scots pine, Pinus sylvestris L.; white pine, Pinus strobus L.; and jack pine, Pinus banksiana Lamb.) was examined for 4 years after the event. Degree of crown loss and tree mortality were quantified in relation to tree and stand characteristics (e.g., tree species, diameter at breast height (DBH), stand density, stand edge versus interior). We also tested whether salvaging damaged material reduced subsequent tree mortality. Jack and Scots pine were 2.5 times more likely to be damaged by the ice storm than were red pine and white pine. Overstocked stands, and stands with lower mean DBH, were most susceptible to storm damage. Trees were five times more likely to be damaged in the interior versus the edge of a stand, in contrast with previous findings in hardwood stands. In unsalvaged stands, ca. 75% tree mortality was observed in severely damaged trees (>50% crown loss) compared with ca. 45% tree mortality in salvaged stands. Properly timed thinnings to increase diameter growth and the removal of dead and dying wood from heavily damaged stands are recommended to reduce the long-term effects of ice storms.
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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 | 0.000 | 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 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".