Habitat attributes and chestnut-backed chickadee nest site selection in uncut and partial-cut forests
Bibliographic record
Abstract
We examined the relationship between habitat attributes and nest-site selection by chestnut-backed chickadees ( Poecile rufescens (Townsend, 1837); hereinafter chickadees) in uncut and partial-cut forests in northwest British Columbia. We described the characteristics of uncut sites and compared them with structurally modified partial-cut sites (mature and old forests). We then compared the use and selection of habitat by chickadees at uncut and partial-cut sites at three spatial scales: (1) the stand (19–24 ha uncut or partial-cut stand), (2) the nest patch (a 0.031 ha patch centered on nest trees), and (3) the nest tree. At the stand scale, we found no correlation between the density of breeding chickadees and the characteristics of uncut and partial-cut sites. At the nest-patch scale, chickadees in uncut and old partial-cut sites selected nest patches with higher densities of broken-top trees compared with available habitat within territories. At the nest-tree scale, chickadees selected nest trees with boring insects and broken tops in uncut and mature partial-cut sites and large trees with boring insects in old partial-cut sites. Our results suggest that chickadees exhibited flexibility in resource selection but also selected resources with similar attributes at the nest-patch and nest-tree scales. Managed stands that maintain a range of tree species and conditions, including live trees with areas of disease, insect attack, and damage, will provide the specific structural attributes used for nesting by weak cavity excavators such as the chickadee.
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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".