Use of small streams and forest gaps for breeding habitats by winter wrens in Coastal British Columbia
Bibliographic record
Abstract
Few studies have examined the value of riparian areas adjacent to streams <=10-m wide as habitat for forest birds. In mature (80-120 years) and young (40-60 years) coastal forests of southern British Columbia, Canada, we examined the habitat values for male winter wrens [Troglodytes troglodytes] of riparian areas adjacent to small streams and areas upslope of these streams. In both riparian and upslope areas, wrens preferentially located nests (n=47) and song perches (n=77) in disturbed sites with fewer trees than randomly located sites. Hydrological processes associated with streams, mortality of dominant canopy trees or uprooted trees can produce these disturbed sites. In mature forest, winter wrens chose stream banks and upturned root masses when available for building their nests with most nest substrates located within 5 m of small streams. In both young and mature forests, they also chose areas near small streams as locations for song perches. Winter wrens may use areas closer to streams when available because channel morphology, the associated heterogeneous forest structure, and microclimate likely provide optimal nesting and foraging habitat. Our research supports operational efforts by forest managers to conserve structures near small streams and in upslope areas because these structures maintain long-term habitat values for wildlife such as winter wrens.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".