Extraterritorial Movements of a Forest Songbird in a Fragmented Landscape
Bibliographic record
Abstract
Abstract: Forest isolation resulting from fragmentation is thought to impede the movement of forest songbirds. Because of the difficulty of tracking birds continuously, however, few data exist documenting the influence of isolation and landscape features on avian movements. During the breeding season, male Hooded Warblers ( Wilsonia citrina ) leave their small (<2.5 ha), isolated forest patches to travel between forest fragments. We documented a total of 106 forays ( n = 20 males) and found that individuals traveled up to 2.5 km away from their resident forest patch, primarily to solicit covert extra‐pair copulations. Forays occurred despite the absence of forested corridors connecting fragments; even when corridors were present, males most often chose to fly directly across open fields. Resident patch size and distance to forests visited were not correlated with the frequency of forays. The maximum distance males flew over open fields did not exceed 465 m, and longer distances likely inhibit males from traveling outside their woodlots. If territorial establishment depends on the availability of extra‐pair partners, then higher degrees of isolation between forests could explain why some species avoid settling in extremely fragmented landscapes. Conservation efforts should limit isolation between forest stands, thereby preserving the ability of animals to move within fragmented landscapes during the breeding season.
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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 | 0.000 | 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".