Seasonal roost selection of wild turkeys at their northern range edge
Bibliographic record
Abstract
Wild turkeys Meleagris gallopavo are diurnally active birds that spend the dark hours roosting in trees. We tested the hypothesis that multiple benefits exist for roost tree selection by wild turkeys, including thermoregulation, resource acquisition, and protection from predators. We compared 48 roost trees used by eastern wild turkeys M. g. silvestris in Ontario, Canada to 48 non‐roost trees sampled contemporaneously during 2017–2019 to determine roost site selection between seasons. Mean (± SE) roost tree height (21.4 ± 0.8 m) was taller than non‐roost trees (18.2 ± 0.8 m), and roost trees were also larger in diameter at breast height (58.1 ± 5.5 vs 38.7 ± 3.1 cm). Using ibuttons to collect microclimate temperatures at the tree, we found that mean temperature (± SE) of a deciduous roost (14.5 ± 0.1°C) was higher than temperature at either a coniferous roost (13.9 ± 0.1°C) or ambient temperature (13.2 ± 0.1°C) during the summer months. In winter however, we did not find any relationship between temperature and tree type. Roosts were closer to buildings (150.8 ± 26.0 m) in the winter compared to summer and year‐round roosts, and winter roosts were also farther away from crops (395.2 ± 63.7 m) compared to roost sites used year‐round. Summer roosts were closer to roads (143 ± 36.3 m) than the roosts in the winter and roosts used year‐round. Our data suggest that thermoregulation is not the driving force behind roost selection; instead, predator avoidance appears to play the most important role, with some weaker evidence in support of proximity to resources.
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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) | 0.001 | 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".