Nest-Tree Use by Northern and Southern Flying Squirrels in Central Ontario
Bibliographic record
Abstract
Little is known about nest use by flying squirrels (Glaucomys) in partially harvested forests, especially for northerly populations where cavity use is prevalent. We used radiotelemetry to examine nest use by 24 southern flying squirrels (G. volans) in 2003 in logged and unlogged hardwood forests, and by 18 northern flying squirrels (G. sabrinus) in 2004 in conifer forests, in Algonquin Provincial Park, Ontario, Canada. Of 76 nest trees used by G. volans, 71% were in declining trees and 22% were in snags. Sixty tree nests used by G. sabrinus included 28% snags, 46% declining trees, and 25% healthy trees, although nearly one-half of nests of G. sabrinus that were used on more than 3 occasions were in snags. G. volans used larger-diameter trees and American beech (Fagus grandifolia) more often than expected by chance, whereas G. sabrinus used trembling aspen (Populus tremuloides), white birch (Betula papyrifera), and yellow birch (B. alleghaniensis) more than expected by chance. Both species used a high proportion of cavity nests, few external nests, and trees that were decayed or diseased. We found indications that nest supply was limited in recently harvested sites, where there were fewer cavity trees and snags; however, G. volans may compensate by using abandoned yellow-bellied sapsucker nests and by nesting in aggregations. Hardwood snags and decaying trees appear to provide crucial nesting habitats for both squirrel species, particularly for females.
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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".