Nest Survival of Chickadees in Managed Forests: Habitat, Predator, and Year Effects
Bibliographic record
Abstract
We examined the influence of year, habitat, and predators on nest survival by monitoring 69 natural cavity nests of the chestnut-backed chickadee (Poecile rufescens) across a range of uncut and partial cut stands in northwest British Columbia during 2000–2003. We considered 3 spatial scales of habitat: 1) the stand (19–24 ha of uncut and partial cut stands), 2) the nest patch (a 0.03-ha patch centered on nest trees), and 3) the nest tree. At each scale we hypothesized that nest survival time of chickadees differed among years, as a result of harvest treatment, habitat characteristics, and predator activity. Nest predation rates fluctuated among years: 56% in 2000, 64% in 2001, 10% in 2002, and 12% in 2003. We identified the red squirrel (Tamiasciurus hudsonicus) as the dominant nest predator. At the stand and nest patch scales, only the covariate year reliably predicted survival time: Risk = 1.81 (Year 2001) for both models. At the nest tree scale, we found the most support for a model with year and nest height: Risk = 1.67 (Year 2001) – 0.08 (Nest Height). All models indicated that for chickadees nesting in 2001, the probability of nest failure increased by more than 5 times. We found no effect of harvest treatment in the stand, nest patch, and nest tree models. Since squirrel density, space use, and activity near nest areas did not differ among years, we suggest that squirrels undergo a functional response and consume food items like eggs and nestlings following low mast years and cones following high mast years. Resource fluctuations that alter the availability and quality of food for red squirrels may result in strong variability in chickadee nest survival. Studies that do not consider such temporal variation may conclude that sites with low nest survival are sink habitats. Managers and researchers may need to consider longer term and/or multitrophic level studies to examine interactions among birds, their predators, and the environment.
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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".