Lower reproductive output of Mountain Bluebirds (<i>Sialia currucoides</i>) in clearcut versus grassland habitat is consistent with a passive ecological trap
Bibliographic record
Abstract
Clearcutting of forests results in habitats that structurally resemble grasslands and so may act as ecological traps for grassland birds. Several studies have implicated predation as the factor that decreases the number of offspring, but few have examined performance at other breeding stages. Consistent with a passive ecological trap, Mountain Bluebirds (Sialia currucoides (Bechstein, 1798)) that settled in clearcuts in central British Columbia did not differ in age or quality from adults in grasslands. Nest building and laying date of the first egg did not differ between habitats, suggesting an equal propensity for settling in each habitat. In clearcuts, however, the body condition of female parents was lower, and they abandoned their nests more often in harsh weather. This higher total clutch loss in clearcuts meant that seasonal production of fledglings per female was 13% less in clearcuts. Furthermore, fledglings in grasslands weighed 4% more and female fledglings had plumage with shorter (UV-shifted) wavelengths (hence greater ornamentation) than those in clearcuts, suggesting that they were also of better quality. Thus, predation rates were not the cause of reduced reproduction in clearcuts; rather, our results suggest that lower prey abundance was linked to nest abandonment in harsh weather and reduced both the number and quality of offspring in those habitats.
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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 | 0.001 | 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) | 0.002 | 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".