Bark stripping of <i>Pinus contorta</i> caused by moose and deer: wounding patterns, discoloration of wood, and associated fungi
Bibliographic record
Abstract
The aim of this study was to assess the extent of bark stripping wounds, subsequent wood discoloration, and associated fungi in 30-year-old Pinus contorta Douglas ex Loudon stems damaged by large game. In total, 90 trees were evaluated, and 170 bark stripping wounds of different ages (1–20 years) were measured. From each wound, wood samples were collected for subsequent fungal isolation. Thirty trees were cut to evaluate the length of the discoloration column. Of 170 injuries, 16 of them represented closed scars and 154 of them represented open wounds that exposed 4–4355 cm 2 of sapwood. The wound length had a strong impact on the length of decay (r = 0.716); however, the spread of discoloration beyond the wound margin was limited (0–20 cm). The most commonly isolated fungus was Sarea difformis (Fr.) Fr. and, among the Basidiomycetes, Peniophora pini (Schleich.) Boidin. The results suggest that when planning to grow P. contorta in areas of Europe, the population size of large game animals needs to be considered, in view of potential risk of bark stripping damage.
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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 | 0.001 | 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".