Harvest retention patches are insufficient as stand analogues of fire residuals for litter-dwelling beetles in northern coniferous forests
Bibliographic record
Abstract
We compared litter-dwelling beetle assemblages of <1- to 2-ha unharvested coniferous patches embedded in 1-year-old clearcuts with beetle assemblages from <1- to 10-ha unburned fire residuals within 15- and 37-year-old burned forests. Our primary objective was to determine whether unharvested patches retain biotic elements that are similar to those of the surrounding uncut forests and to those of patches of forest skipped by wildfires. Beetle assemblages of the harvest residuals were similar to those of the uncut forest, suggesting that harvest residuals retain elements of the mature forest. However, beetle assemblages of harvest residuals differed from those of fire residuals. Thus, harvest residuals sited without regard to microhabitat characteristics or stand structure in fire residuals are insufficient analogues for the late successional habitats provided by fire residuals. There was no relationship between size of harvest residuals and either beetle catch or diversity. Beetle catches were higher in round harvest residuals, and a number of forest species also appeared to be aggregated in round residuals. Forest managers may preserve biotic elements of young uncut forest by leaving round harvest residuals in clearcuts; however, a closer habitat match between harvest and fire residuals is likely required to preserve and maintain landscape-level forest biodiversity.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".