Nesting success and nest-site selection by a neotropical migrant in a fragmented landscape
Bibliographic record
Abstract
Information on breeding-habitat requirements for neotropical migrants is important for managing remnant woodlots used by these species. In 1998, we examined nest-site selection and nesting success of hooded warblers (Wilsonia citrina) in seven woodlots of the highly fragmented Carolinian Forest in southwestern Ontario, Canada. We sampled and compared 23 nest and unoccupied sites. We recorded number of eggs, number of nestlings, and number of young fledged, as measures of productivity, and the presence of cowbird (Molothrus ater) parasitism. Nest sites had an overall higher percentage of vegetation cover than unoccupied sites (U [Formula: see text] 75.0, P < 0.04) and a lower basal area of trees with a diameter at breast height between 7.5 and 15 cm (U = 376.0, P = 0.014). Our best logistic regression model showed that the probability of a site being occupied by nesting hooded warblers increased with the height of the subcanopy and with the percentage of vegetation cover at the 1- to 2-m height interval. The model correctly classified 74.6% of the nest and unoccupied sites. Nest survivorship for the entire nesting period was estimated at 67.1%. Cowbird parasitism was low (18%). No nest-site characteristics were correlated with any of the productivity parameters (rs[Formula: see text] 0.663, P [Formula: see text] 0.536, n = 17). We conclude that canopy gaps and understory vegetation, rather than forest maturity, appear to be the limiting factors affecting the selection of a site by hooded warblers. Further research should focus on the use of gaps by breeding hooded warblers, and logging prescriptions should be formulated to include the creation of openings in the forest canopy.
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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".