Habitat suitability and protected area coverage for an expanding cougar <i>Puma concolor</i> population in Canada
Bibliographic record
Abstract
) are expanding their range eastwards and little research is available for use in decision making by land managers and conservation planners. To inform proactive management regarding expanding populations of cougars in Canada, we utilized open-source cougar presence and land-cover data in a maximum entropy habitat suitability model to determine potentially suitable habitat for cougars across the country. We then used a gap analysis to determine the effectiveness of existing formal protected areas to protect potential cougar habitat. Suitable habitat exists for range-expanding cougars dispersing eastwards through the central and eastern provinces to the Atlantic coast. While the habitat is highly fragmented, the highest suitability occurs in areas of medium road density, indicating that the potential for new human-cougar conflict will likely involve residents of exurban and rural areas. Protected areas offered 16% coverage of suitable habitat, although most protected areas that overlap predicted cougar habitat are not large enough to effectively conserve the large home range requirements of cougars. Synthesis and Applications: High fragmentation of suitable habitat and the potential for human-wildlife conflict requires proactive management to ensure appropriately sized and connected areas are maintained for the establishment of expanding cougar populations. Many of the management actions intended to aid in the conservation of cougars and their habitat can also serve to mitigate potential human-cougar conflict arising as a consequence of an expanding population, such as highway wildlife crossing structures and formal habitat protection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".