Habitat occupancy patterns of a forest dwelling songbird: causes and consequences
Bibliographic record
Abstract
We examined patterns of habitat use and reproductive performance of a migratory songbird, the black-throated blue warbler (Dendroica caerulescens (Gmelin, 1789)), within a 3160-ha forested landscape. We surveyed 371 sites over a 3-year period. Some sites were never occupied, while others were occupied for 1, 2, or 3 years. For these 3 years we found that warbler abundance increased with frequency of occupancy. Additionally, we found that (i) deciduousness and understory shrub density increased with frequency of occupancy; (ii) in 1 of 3 years, food abundance was higher at the most frequently occupied sites; and (iii) nest predators exhibited predator-specific abundance patterns across occupancy categories. We next used occupancy patterns documented in the first 3 years of the study to predict settlement, age structure, and reproductive performance at a subset of sites in the final year of the study. We found that males settled earlier in the breeding season at sites with a high frequency of occupancy. There were no differences in arrival times of females. Additionally, age structure did not vary for either males or females across sites with different occupancy levels. Although we found no difference in mean reproductive output across sites with different occupancy levels, over 50% of the young produced fledged from territories overlapping the high occupancy sites.
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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 | 0.000 |
| 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".