Unique songbird communities in mature riparian spruce forest compared with upland forest in southern Yukon
Bibliographic record
Abstract
There has been limited study of songbird communities in different habitats of the lowland boreal forests of southern Yukon, including the mature forest valued for timber harvest. Our goal was to describe the songbird community during the breeding season in a mature (≥80 years since wildfire) forest dominated by white spruce (Picea glauca (Moench) Voss) adjacent to streams (n = 23) and wetlands (n = 15) compared with a nearby upland forest. Based on point count surveys, songbird communities were unique in the mature forest in the riparian forest edge position, including greater species richness and four significant riparian indicator species. Songbird communities were also unique in the forest adjacent to streams versus wetlands. We mapped species observations along 300 m transects from riparian to upland forests and identified nine species with greater abundance closer to the riparian forest edge. Many of these species are typically associated with riparian and wetland habitats for breeding. Most of the variability in the songbird community was explained by study site, likely related to high variability in forest type and amount of wetland and open water but also to unmeasured habitat characteristics. Our results increase the knowledge of songbird communities in this unique boreal region and suggest that riparian reserve zones in forest management may be useful for protecting songbird habitat.
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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 | 0.001 | 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".