Impacts of moose (Alces alces) browsing on paper birch (Betula papyrifera) morphology and potential timber quality
Bibliographic record
Abstract
Although moose browsing effects on the growth and morphology of birch are well studied, effects of moose browsing on potential timber quality of birch have received little attention. Here, an assessment was made of the impacts of moose (Alces alces L.) damage to Paper Birch (Betula papyrifera Marsh.) trees from a 20-year old clear cut area in a sub-boreal spruce forest within the Aleza Lake Research Forest, near Prince George, British Columbia, Canada. Specifically, differences in overall tree architecture and in the internal characteristics of trees that had been severely damaged and suppressed by moose winter browsing were compared to birch trees that had not been damaged by moose in this way and were considered free-to-grow. The average stem diameter, number of annular growth rings, and height of stem breaks made by moose on suppressed birches at the point of breakage was 17.9 ± 6.6 mm, 4.6 ± 1.2, and 141.8 ± 32.0 cm, respectively. Stem diameters and the heights above-the-ground of stem breaks made by moose during sequential breakage events were not significantly different (all p ≥ 0.05) from one another. Decay was significantly (all p ≤ 0.001) more extensive in trees where branches had been broken off by moose than in trees with no breaks or where breaks were from unknown agents. Suppressed birches were significantly (p = 0.048) more exposed (farther from their nearest tree neighbor) when compared to birches that were free-to-grow. The distance from birch trees to species-specific neighbors (of any species) did not differ (all p ≥ 0.05) between suppressed and free-to-grow birches. Suppressed birches damaged from intense browsing and stem breakage were significantly (≤ 0.001) farther away from other birches showing signs of slight to moderate browsing than free-to-grow birches were from similar conspecifics. Because moose appear to impact the potential wood quality of birch, forest managers should consider the impacts that browsing and stem breakage can have on birch timber where these trees co-occur with and are eaten by moose.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".