Highway Effects on Wildlife in Banff National Park: A Research, Monitoring and Adaptive Mitigation Program
Bibliographic record
Abstract
– continued on page 6 – The current rate of habitat fragmentation and human development along the TransCanada corridor is a threat for the long term survival of wildlife in Banff National Park (BNP) (Banff-Bow Valley Study 1996). The TransCanada Highway (TCH) has serious effects on wildlife populations in the Park, fragmenting habitat, acting as a barrier to natural movements in the Bow Valley and more importantly, it is a significant factor in wildlife mortality. Roughly half of the reported wildlife deaths in BNP can be attributed to highways (Shury 1996). Levels of highway-related mortality for some populations in Banff is equal or greater than mortality rates in hunted populations (Gibeau and Heuer 1996). Ironically, the Park is intended serve as a core refuge and a source for replenishing peripheral, unprotected populations outside its boundaries. The TCH, the most important transporation route in Canada, brings high-speed and high-volume traffic into the Park. In the last 20 years, traffic volume has increased steadily, and the highway has been frequently upgraded to meet the demand. The first upgrade began in 1980 at the east gate. Today, twenty-seven kilometers have been twinned (expanded from 2 to 4 lanes; Phase I & II), another 18 km twinnng project is currently underway (Phase IIIA), and the remaining 30 km to the Yoho National Park boundary will likely be upgraded in the next five years (Phase IIIB). Several measures were taken to mitigate the adverse effects of the highway upgrades on wildlife. Crossing structures (under- and overpasses) were constructed to link habitat and provide wildlife with safe routes accross the highway. Wildlife exclusion fencing keeps animals off the highway right-of-way (ROW) and directs them to the crossing structures. Studies show that when crossing structures are used in conjunction with fencing, highway-related
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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 | 0.001 |
| 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".