Susceptibility of Trees to Windthrow Storm Damage in Partially Harvested Complex-Structured Multi-Species Forests
Bibliographic record
Abstract
In Canada and elsewhere, logging practices in natural-origin forests have shifted toward retention systems where variable levels of mature trees are retained post-logging to promote a diversity of values. We examine multiple sites that experienced a wide range of prior harvest regimes (0–76% basal area removal) to evaluate how harvest intensity and proximity to a logging-created edge affects susceptibility to windthrow for a suite of tree species in complex-structured mature and old-growth mixed-species stand types in British Columbia. We found no increased susceptibility to windthrow as a function of the level of partial harvesting. We observed a reduced susceptibility to windthrow of smaller trees after partial harvesting. There were clear differences in susceptibility to windthrow among different tree species close to the edge of gaps and small openings (<1 ha in size) created by partial harvesting. Hemlock and redcedar, the two most common trees species, were unaffected by edge environments, whereas the less common conifers and deciduous species were more susceptible to windthrow along partial harvest edges. This suggests tree-marking guidelines should remove the species most prone to windthrow from edges around small openings in these forest types. Our study and others suggest use of retention systems in structurally diverse, multi-species forests does not lead to elevated risk of windthrow, especially if retention levels exceed 20–30%.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".