TERRITORY AND NEST-SITE SELECTION OF CERULEAN WARBLERS IN EASTERN ONTARIO
Bibliographic record
Abstract
We examined habitat selection by breeding Cerulean Warblers (Dendroica cerulea) at three spatial scales in eastern Ontario over three years (1997–1999). Territories were characterized by well-spaced large trees, with high canopies and dense foliage cover at heights between 12–18 m. Nesting habitat additionally was characterized by dense foliage cover above 18 m. The results of our nest-patch (0.04 ha circle around nest) and nest-site (0.01 ha circle) analyses indicate that male Cerulean Warblers may take active roles in nest-site selection when selecting territories. We conclude from our nest-patch and nest-site selection analyses that territories likely contain multiple nest patches and sites and that male Cerulean Warblers may defend areas with multiple nest patches or sites, which may attract females to settle with them. Whether or not Cerulean Warbler females use nest-site availability as a mate- or territory-choice cue remains unknown. We also tested the validity of a commonly made assumption that a random sampling of habitat by researchers is representative of the habitat actually available to birds and found that, in our study area, the assumption was invalid. Taken together, our results point toward the need to maintain sizeable stands of mature, deciduous forest to ensure the persistence of Cerulean Warblers in eastern Ontario. Population characteristics such as lower minimum area requirements and a resilience to habitat disturbance may make that an easier job in eastern Ontario than elsewhere in this species' breeding range.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".