Effects of Forest Management on Postfledging Survival of Rose-breasted Grosbeaks (<i>Pheucticus ludovicianus</i>)
Bibliographic record
Abstract
Many studies have examined the effects of forest fragmentation and management on songbird nesting success, but few have quantified postfledging survival, which is a critical component of population productivity. In 2005–2006, we estimated daily postfledging survival of Rose-breasted Grosbeaks (Pheucticus ludovicianus) by radiotracking 42 fledglings in forest fragments that had been managed by single-tree selection, by diameter-limit harvest, or as reference (not harvested for at least 25 years). Survival probability over the 3-week fledgling period was 0.62, and 86% of total fledgling mortality occurred during the first week out of the nest. Despite large differences in forest structure between forest management treatments, there was no effect of forest treatment on fledgling survival. Date of fledging, shrub cover, and patch size also had limited influence on fledgling survival. For all sites combined, females produced an estimated 0.23–0.37 recruiting daughters per year for the worst- and best-case scenarios of female fecundity and annual juvenile survival, which is lower than the expected annual mortality rate of breeding females (0.40–0.55). Even reference sites did not produce enough offspring to offset annual female mortality, which suggests that forest fragments in this region are population sinks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".