Territory size and overlap in male Ovenbirds: contrasting a fragmented and contiguous boreal forest
Bibliographic record
Abstract
We evaluated if male age and body size, density of conspecifics, and arthropod biomass contributed to variation in territory size and overlap of Ovenbirds, Seiurus aurocapillus (L., 1766), in a fragmented and contiguous boreal forest. Territory size and overlap were determined by radio-tracking territorial male Ovenbirds in fragmented (n = 22) and contiguous forest (n = 13) from late May to the end of June 1999 and 2000. Variation in male territory size was most strongly associated with individual characteristics, specifically body size and age. Furthermore, we found strong support for an effect of density of conspecifics on territory overlap, suggesting that the exclusivity of territories and perhaps levels of territoriality were greater for males in contiguous forest than for those in fragments. Our findings (i.e., mean territory size was similar between landscapes and territory overlap was greater in fragments than in contiguous forest) suggest that fragments either have larger areas of unsuitable habitat or are less saturated with Ovenbirds. Furthermore, because resources were not distributed equally among individuals, our results were consistent with the ideal dominance model of habitat selection. Finally, previous studies based on acoustical surveys have likely underestimated space-use requirements in forest passerines.
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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".