Resistance of forest songbirds to habitat perforation in a high-elevation conifer forest
Bibliographic record
Abstract
We examined responses of songbirds breeding in high-elevation Engelmann spruce subalpine fir (Picea englemannii Parry ex Engelm. Abies lasiocarpa (Hook.) Nutt.) forests to four perforation harvest patterns near Sicamous, British Columbia. Each treatment removed approximately 30% of the timber volume but varied the size of openings from 10-ha clearcuts to small gaps (<0.01 ha), where individual trees were removed. Abundance and diversity of breeding songbirds were monitored over a 4-year period, including 2 years each of pre- and post-harvest conditions. Two-thirds of the original songbird assemblage consisted of mature forest species that showed only modest changes in relative abundance following harvest. Two species showed significant responses to harvesting: golden-crowned kinglet (Regulus satrapa Lichtensteins) declined significantly postharvest, with the largest declines occurring in single-tree and 10-ha treatments; and dark-eyed junco (Junco hyemalis L.) responded positively to harvest. At high elevations, 30% volume removal allowed much of the songbird community to be accommodated immediately after harvest. Future research should address whether the apparent short-term accommodation of high-elevation birds persists across time and as more of the continuous forest cover is removed.
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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 | 0.000 | 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".