Consequences of forest fragmentation on territory quality of male Ovenbirds breeding in western boreal forests
Bibliographic record
Abstract
We evaluated the effects of forest fragmentation caused by agriculture on arthropod prey biomass and vegetation structure found in territories of male Ovenbirds (Seiurus aurocapillus) breeding in the southern boreal mixed woods of Saskatchewan, Canada. The objective of this study was to determine if previously documented differences in pairing success of male Ovenbirds in contiguous forests and forest fragments in our study area were associated with differences in arthropod prey biomass and vegetation structure between contiguous and fragmented forests. A secondary objective was to examine the correspondence between vegetation and arthropods to evaluate whether vegetation cues could be useful for birds attempting to predict future arthropod biomass during territory selection. Our results indicate that both vegetation structure and arthropod prey composition in Ovenbird territories differed between fragmented and contiguous forests, whereas total arthropod biomass did not. Furthermore, the correspondence of vegetation with arthropod prey composition and total prey biomass was weak, a result that questions the use of vegetation structure by male Ovenbirds for predicting future prey availability during territory selection. Overall, the current extent of forest fragmentation in our study area is not likely reducing pairing success of territorial male Ovenbirds by lowering the biomass of arthropod prey. However, landscape differences in vegetation structure could influence pairing success of male Ovenbirds in forest fragments by reducing suitable microhabitats for nesting or by increasing habitat suitability for nest predators and Brown-headed Cowbird (Molothrus ater) parasites.
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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".