Effects of two silvicultural practices on ground beetles (Coleoptera: Carabidae) in a northern hardwood
Bibliographic record
Abstract
Rock Ouimet, Daniel Houle, and Claude Camiré Abstract: The impact of selective cutting (6 and 8 years after treatment) and strip clear-cutting (12 and 13 years after treatment) on abundance and diversity of carabid beetles was evaluated in a northern hardwood forest of Quebec, Can-ada. A total of 1078 individuals belonging to 14 species were captured with pitfall traps from June to September 1996 during 2568 day-trap. Abundance of Synuchus impunctatus Say was significantly higher in clear-cut compared with un-cut control strips. There were no within-species differences between selectively cut and uncut plots. None of these two silvicultural systems had any significant impacts on species diversity and richness 6–13 years after treatment. Although we observed an effect of strip clear-cutting on the abundance of S. impunctatus in this northern hardwood forest, the discrepancy between the response of carabids to forest disturbance in this study compared with other studies in differ-ent ecological regions suggests that the same carabid beetle species cannot be used as an indicator of forest disturbance over a large region. Our results suggest the use of carabid beetles as a disturbance indicator at the ecological-type scale (relatively similar soil and forest type) in a given region. Résumé: L’impact de la coupe de jardinage (6 et 8 ans après le traitement) et de la coupe totale par bande (12 et
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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 | 0.001 | 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".