EFFECTS OF HABITAT FRAGMENTATION ON PAIRING SUCCESS OF OVENBIRDS: IMPORTANCE OF MALE AGE AND FLOATER BEHAVIOR
Bibliographic record
Abstract
Abstract Between 1996 and 1998, we compared pairing success of territorial male Ovenbirds (Seiurus aurocapillus) in forest fragments created by forestry (n = 3) and agriculture (n = 10) to contiguous forest plots (n = 3) in the southern boreal mixedwood forest of central Saskatchewan. The percentage of Ovenbird males paired per site was lower in fragments created by agriculture (86 ± 3%) and forestry (87 ± 3%) than in contiguous forest (97 ± 3%). At the individual level, second-year males (82%) were less likely to be paired than after-second-year males (94%), whereas males closer to edges were less likely to be paired than those in forest interiors. Although pairing success differed among landscapes, those differences were smaller than reported in studies conducted in eastern North America. The high density of birds in our study area may have resulted in intense intraspecific competition, which could have prevented unpaired individuals from maintaining territories. Removal experiments in 1997 and 1998 demonstrated floaters occurred in contiguous forest, but rarely occurred in fragments created by agriculture. The presence of floaters in contiguous forest suggests the ratio of breeding to nonbreeding males in forest fragments and contiguous forest may be similar, but that the strategy (i.e. floater vs. territorial) used by unpaired birds may differ among landscapes.
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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 | 0.001 | 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) | 0.002 | 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".