Seasonal changes in habitat features influencing nest survival of sharp-tailed grouse in northeastern British Columbia, Canada
Bibliographic record
Abstract
Nest survival is an important determinant of overall reproductive success in birds and is often most influenced by factors such as habitat quality and predator communities. We examined the impacts of several variables hypothesized to affect nest survival by monitoring 74 radio-collared female sharp-tailed grouse(Tympanuchus phasianellus) during 2004 and 2005 in northeastern British Columbia, Canada. We tested candidate models using Program MARK and used an information-theoretic approach to assess the effects of habitat characteristics on daily nest survival rates, as well as the influence of female attributes on nest survival. Nest success, defined as hatching at least one egg, was 35% (95% CI = 21, 59) for first nests and 32% (95% CI = 12, 78) for renests. Daily nest survival probabilities increased with the amount of cover provided by woody shrubs at nest sites during first nest attempts and decreased with greater residual cover(i.e., the amount of dead, vegetative material from the previous growing season) at nest sites during renest attempts. As cover provided from shrubs became less important later in the nesting season, and residual vegetation was not a significant predictor of early-season nest survival, our results suggest that habitat features influencing survival of sharp-tailed grouse nests may change seasonally. We further suggest that this trend may be more pronounced at northern latitudes, where growing seasons are shortened and annual temperatures are reduced, which can influence the availability and effectiveness of habitats throughout the duration of the nesting season. We therefore caution against making broad management recommendations when managing habitats to increase nesting success of sharp-tailed grouse, as factors influencing success may vary across the species' range.
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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".