Nest-Site Reuse Patterns for a Cavity-Nesting Bird Community in Interior British Columbia
Bibliographic record
Abstract
Abstract Most obligate cavity-nesting birds are considered to be nest-site limited, either by time or energy to excavate or to acquire suitable holes for nesting. We examined rates of nest-cavity reuse for a rich community of cavity-nesting birds in mixed forests in interior British Columbia. Using a sample of 402 cavity-reuse cases over five years, we measured cavity reuse for 20 cavity-nesting bird and mammal species (three guilds), and examined the relationship between nest-cavity reuse and features of cavities, nest trees, and forest stands. Eight percent of used cavities were destroyed between years. Reuse rates were 17% for the cavities of weak excavators such as nuthatches and chickadees, 28% for formerly active woodpecker nests, and 48% for cavities previously used by secondary cavity nesting birds, but there was considerable species variation within all guilds. Nest cavities in aspen that were deep with large entrances had the highest reuse. At the forest stand level, cavities in trees close to edges and in sites with more edge habitat had greater reuse. Reused cavities tended to be occupied in sequential years rather than being inactive for a year. With increasing amounts of managed landscapes, availability of suitable cavities for forest nesting vertebrates is decreasing. Reuse of existing cavities might help mitigate the problem of nest-site limitation.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".