Effects of Postfire Salvage Logging on Deadwood‐Associated Beetles
Bibliographic record
Abstract
In Canada and the United States pressure to recoup financial costs of wildfire by harvesting burned timber is increasing, despite insufficient understanding of the ecological consequences of postfire salvage logging. We compared the species richness and composition of deadwood-associated beetle assemblages among undisturbed, recently burned, logged, and salvage-logged, boreal, mixed-wood stands. Species richness was lowest in salvage-logged stands, largely due to a negative effect of harvesting on the occurrence of wood- and bark-boring species. In comparison with undisturbed stands, the combination of wildfire and logging in salvage-logged stands had a greater effect on species composition than either disturbance alone. Strong differences in species composition among stand treatments were linked to differences in quantity and quality (e.g., decay stage) of coarse woody debris. We found that the effects of wildfire and logging on deadwood-associated beetles were synergistic, such that the effects of postfire salvage logging could not be predicted reliably on the basis of data on either disturbance alone. Thus, increases in salvage logging of burned forests may have serious negative consequences for deadwood-associated beetles and their ecological functions in early postfire successional forests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".