Effects of commercial thinning on site occupancy and habitat use by spruce grouse in boreal Quebec
Bibliographic record
Abstract
Partial cuts are increasingly proposed to maintain habitats for species negatively affected by clearcutting, even if their benefits on nonpasserine birds and large mammals are still poorly documented. Our main objective was to evaluate effects of commercial thinning (CT) on spruce grouse ( Falcipennis canadensis L.), a game bird of the boreal forest. Because this species is known to be associated with a dense vegetation cover, we hypothesized that habitat use would be lower in treated sites. In spring 2006, we evaluated site occupancy in 94 forest stands (50 CT and 44 uncut stands) in Quebec by visiting each on three occasions during the breeding season (March–May). Additionally, during the molting period (May–July), we used radiotelemetry to monitor habitat use by 19 males. As compared with uncut stands, results show that a lower proportion of CTs were used in spring (39% versus 60%, after accounting for detection). During the molting period, CTs were also used less than expected according to their availability. The significant reduction of lateral and vertical forest cover in CT may explain these results. We conclude that even if CT is perceived beneficial for wildlife, it does not completely fulfill the needs of species associated with dense understory vegetation, such as spruce grouse.
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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".