Badger Resource Selection in the Rocky Mountain Trench of British Columbia
Bibliographic record
Abstract
Conservation of species at risk requires an understanding of resource-selection patterns and habitat distribution. We used 1,795 radio-telemetry locations from 55 study animals to model resource selection for an endangered population of American badger (Taxidea taxus jeffersonii, eastern population) in the Rocky Mountain Trench of British Columbia. The badgers were associated with low elevations, shallow slopes, high solar radiation, and low crown closure. They selected higher elevations only on sites with shallow slopes or high solar radiation. Compared to mesic low-elevation forests, badgers selected locations where the climax ecoclass was riparian forest or very open low-elevation forest. In comparison to Douglas-fir stands, badgers selected clearings, moist forest, and open range. They avoided lodgepole pine stands, western larch stands, and wet areas. Relative to the Brunisol soil order, they avoided Podzolic – Luvisolic and Regosolic-Gleysolic orders. Compared to Morainal soil parent material, the badgers avoided colluvial, rock, aeolian, and anthropogenic and selected for glaciolacustrine parent material. Results were consistent both with expectations from other provincial studies and with cover types used by Columbian ground squirrels (Spermophilus columbianus), which are their main prey. Our model provides a spatially explicit tool to prioritize areas for restoration or critical habitat designation. Reduction of crown closure would benefit badgers, and would probably be the most advantageous on Brunisolic or Chernozemic soils and glaciolacustrine parent material.
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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 | 0.001 | 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".