Reducing spruce beetle <i> <scp>D</scp> endroctonus rufipennis </i> ( <scp>K</scp> irby) ( <scp>C</scp> oleoptera: <scp>C</scp> urculionidae) emergence for hibernation in central <scp>B</scp> ritish <scp>C</scp> olumbia by felling infested trees
Bibliographic record
Abstract
Abstract Sanitation harvesting for the removal, processing and killing of spruce beetle in infested trees the year after attack is often only partially effective because a significant percentage of beetles emerge from standing trees in the autumn and drop down to the root collar to hibernate under the bark below the duff line. When trees are harvested, these beetles are left behind in stump root collars. We hypothesized that falling of spruce beetle‐infested standing trees, in the second summer (before pre‐hibernation emergence of beetles), can increase the window of opportunity for sanitation harvesting and extract more beetles from the forest. Thirty E ngelmann spruce that had been successfully infested by spruce beetle on a 2‐year life cycle in 1995 were selected at each of two locations in the central interior of B ritish C olumbia in 1996. At each site, 10 replicates of three treatments were randomly applied. Ten spruce were felled from 29 M ay to 10 J une (early treatment), 10 were felled on 8 A ugust (late treatment) and the remaining 10 were left standing. In mid‐ A ugust, a pair of nylon screening emergence traps were attached to all trees to capture any immature adults emerging for hibernation. Emergence traps and underlying phloem were collected in late S eptember to early O ctober and revealed that 48–62% of immature adults emerged for hibernation from standing trees, whereas significantly fewer (7–17%) emerged from felled trees. We conclude that, if sanitation harvesting of 2‐year cycle spruce beetle‐infested spruce cannot occur until the second winter, pre‐harvest felling of these trees in the second year can reduce emergence for hibernation by 69–88% and allow the extraction of more beetles over a longer period.
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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) | 0.001 | 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".