The effects of selective logging on nest-site selection and productivity of hooded warblers (<i>Wilsonia citrina</i>) in Canada
Bibliographic record
Abstract
We examined nest-site selection by hooded warblers (Wilsonia citrina) in two forests differing in composition (extensive pine plantation versus largely deciduous) and management (recent selective logging versus minimal logging). We measured habitat at 52 nests and 66 controls in one forest and 57 nests and 41 controls in the second. Nests had denser ground vegetation, fewer tree stems, less basal area due to small trees and greater basal area due to large trees than controls in both forests. In the managed forest with extensive pine plantations, hooded warblers were in coniferous and logged stands more often than expected by chance, nests had more stumps and greater canopy height than controls, and 91% (52/57) of all nests were found in gaps, 84% of which were created by harvest. Gap age was 6.2 ± 0.9 years (mean ± SE) in 1999, and 7.6 ± 0.6 years in 2000. In the managed forest, 52% of 24 nests were parasitized in 1999 and 39% of 33 nests were parasitized in 2000. The daily survival rate was 0.936 ± 0.019 in 1999 and 0.944 ± 0.014 in 2000. Successful nests did not differ from unsuccessful nests in any habitat variable. To benefit hooded warblers, forest managers should mimic natural gap creation by using selective logging to create gaps no larger than 0.05 ha, and should leave a residual basal area of mature trees (>38 cm diameter at breast height) of at least 12 m2/ha.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".