Identifying the determinants of windthrow damage in wildlife tree patches in the Boreal White and Black Spruce biogeoclimatic zone of northeastern British Columbia
Bibliographic record
Abstract
Leaving wildlife tree patches (WTPs) has become a common strategy employed to maintain biodiversity among managed forest ecosystems in British Columbia. High levels of wind damage have been observed in many of these reserves owing to the increased wind loading after harvesting. The ensuing damage disrupts forest management plans and reduces the value of WTPs. The objective of this study was to identify the primary determinants of windthrow in WTPs in the boreal forest of northeastern British Columbia andto suggest management strategies to minimize wind-related damage. Line transects oriented parallel and perpendicular to prevailing and dominant winds across 13 WTP reserves were used to quantify wind-related damage and factors that may contribute to windthrow incidence. The occurrence of windthrow corresponded with the exposure of WTP edges to high velocity winds; common, but lower-velocity winds resulted in little windthrow damage. Edaphic, site, and forest-stand factors appeared to have little influence on the incidence of windthrow in this study as compared to exposure to strong winds. The study suggests that forest managers can reduce the incidence of windthrow in WTPs in the boreal forests of northeastern British Columbia by:(1) creating patches that are elliptically shaped with the long axis in the direction of the dominant winds;(2) reducing wind exposure of susceptible edges; and (3) increasing the size of WTPs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".