Response of small mammals to clear-cutting and precommercial thinning in mixed forests of southeastern Quebec
Bibliographic record
Abstract
The impacts of forest management on habitat characteristics, species richness, and population dynamics of small mammals remain ambiguous. We studied the response of small-mammal populations, including snowshoe hares, to clear-cutting with protection of advanced regeneration and soils (CPRS) and precommercial thinning (PCT). We compared stands recently treated by CPRS or PCT with established stands dominated by deciduous or coniferous trees in two large blocks of mixed forests. We measured habitat components and abundance of small mammals in the four stand types. Trees (DBH ≥ 9 cm) became very rare in CPRS stands and remained at low density in PCT stands, which stimulated the growth of herbs and seedlings, resulting in increased lateral cover. Tree harvest also generated coarse woody debris in CPRS stands, which did not persist in PCT stands. Small mammals responded to these disturbances in a species-specific manner but, overall, relative abundance and species richness of small mammals were lower in PCT stands than in CPRS and closed stands. Our results suggest that forest managers should exclude some stands from PCT following CPRS or natural perturbations, to maintain ecosystem diversity at the landscape level.
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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 | 0.001 | 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".