Winter nest trees of sympatric northern (<i>Glaucomys sabrinus</i>) and southern (<i>Glaucomys volans</i>) flying squirrels: a test of reinforcement in a hybrid zone
Bibliographic record
Abstract
Shifting range boundaries can lead to secondary contact of closely related species, which might in turn lead to hybridization when the evolution of reproductive isolation is incomplete. We examined winter nest use of northern (Glaucomys sabrinus (Shaw, 1801)) and southern (Glaucomys volans (Linnaeus, 1758)) flying squirrels in an area of recent secondary contact and known hybridization in Ontario, Canada, to test for evidence of reinforcement due to different and diverging nesting behaviours. We radio-collared 26 flying squirrels (12 G. sabrinus and 14 G. volans) between two survey periods (winters of 2008–2009 and 2019–2020) and identified all nest trees used by individuals throughout each winter. For each nest tree, we identified the nest type and collected tree classification information to compare differences in nest use between species. We also present a novel application of habitat suitability modelling to test for evidence of divergence in nest use through time, which would suggest reinforcement. We found southern flying squirrels used a higher proportion of cavities in large, hardwood trees, whereas northern flying squirrels used more external nests and softwood trees. Conditional probabilities provided some evidence for increased differentiation in nest use by flying squirrels through time. Overall, we found relatively little overlap in winter nest use between flying squirrel species, despite evidence for hybridization at this site, and some weak evidence for increased divergence between species in nest use over 11 years.
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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 | 0.001 |
| 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 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".