Factors affecting site selection by beavers colonizing streams in the upper Midwest region of the United States
Bibliographic record
Abstract
Beaver management requires understanding beaver habitat preferences. Despite the American beaver ( Castor canadensis Kuhl, 1820) being relatively common in the upper Midwest region of the United States, there are no beaver habitat relationship models based on this area. We used 1735 colonization events from long-term monitoring data generated by the Chequamegon-Nicolet National Forest in northern Wisconsin, USA, to determine what geomorphological and biological factors were selected by beavers colonizing new sites. We developed and evaluated prediction performance for three colonization models: geomorphology factors only, geomorphology and vegetation factors, and a full colonization model based on geomorphology, vegetation, and availability of dispersing beavers. Overall, the geomorphology–vegetation–colonizer model was the best model, predicting actual colony locations better than the other two models. Spatially, the landscape open to beaver colonization was a mosaic of streams with suitable and unsuitable habitat. These models improve our understanding of how beaver site selection factors in the upper Midwest region differ from factors identified in the literature for the western and eastern United States. This information may be useful for land managers in this region seeking to spatially target resources for restoring northern forest landscapes such as the Chequamegon-Nicolet National Forest.
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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 | 0.001 |
| 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".