The effects of patch harvesting and site preparation on ground beetles (Coleoptera, Carabidae) in yellow birch dominated forests of southeastern Quebec
Bibliographic record
Abstract
We studied the impacts of increasing size and number of gapcuts and the effects of site preparation by scarification on the species richness and community composition of ground beetles (Coleoptera: Carabidae), using pitfall traps in early-successional yellow birch dominated forests in eastern Canada. Catches of all carabids, forest specialists, and generalists were generally higher in uncut controls than in treatments. The catch of open-habitat specialists was generally lower in controls than in treatments. Although not significant, there was a common trend for scarification to decrease the catches of forest specialists and generalists. BrayCurtis similarity measures and nonmetric multidimensional scaling ordination indicated that the composition of the carabid assemblage was more affected by harvesting treatment than by scarification. Carabid species composition varied consistently with increasing gap size and corresponded to the a priori generalized habitat-preference designations. Forest-specialist species were confined to uncut sites, while generalist species were widely distributed across all sites. Open-habitat species were found predominantly in clear-cut and two-gap sites. Hygrophilous species were consistently associated with two-gap, four-gap, and clear-cut sites. Small-gap harvesting is more favorable to the maintenance of the structure of natural arthropod assemblages than are traditional, larger clearcuts.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".