Balancing risks of disturbance from mountain pine beetle and western spruce budworm
Bibliographic record
Abstract
The effect of removing lodgepole pine ( Pinus contorta Dougl. ex Loud.) and retaining Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) to reduce the risk of disturbance from mountain pine beetle ( Dendroctonus ponderosae Hopk.) in mixed conifer stands in southern British Columbia, Canada, on population processes influencing outbreaks of western spruce budworm ( Choristoneura occidentalis Free.) was evaluated in 10 paired (open vs. closed) field plots. Overall feeding damage to Douglas-fir was significantly, but only slightly, lower in open stands compared with closed stands. Although open plots tended to recruit more budworms, the losses resulting from the dispersal of spring-emerging budworms in search of feeding sites were significantly greater in open plots. The forest management benefits of these early season losses were mitigated, however, by more mortality of budworms from natural enemies, particularly diseases, in the closed plots during the budworm feeding period. These results are discussed in terms of compensating population processes and balancing objectives in forest pest management. In this case, selective harvesting of lodgepole pine as a mitigation strategy for the mountain pine beetle conserved the midterm timber supply potential represented by associated Douglas-fir even in the presence of an outbreak of the western spruce budworm.
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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 | 0.000 | 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".