Balancing focal species, recreation and biodiversity in mountain coal mine closure planning : Alberta, Canada
Bibliographic record
Abstract
Coal extraction in the Coal Branch region of Alberta, Canada has occurred since 1911 with surface mining dominating as of the 1940s. Coal mining in this mountain/foothills landscape now occurs in a multiple land use context along with oil and gas exploration and production, timber harvest, aggregate mining, big game hunting/guiding/outfitting, fur trapping, recreational All Terrain Vehicle (ATV) use, fishing, camping and other outdoor recreational pursuits. Currently, there are three surface coal mines in various stages of active mining, reclamation and closure in the upper elevations of the Coal Branch region. Mining has taken place within an increasingly stringent regulatory framework. In the mid-1990s, application was made for the Cheviot mine project. It’s close proximity to Jasper National Park and heightened cumulative effects assessment requirements resulted in a ground-breaking series of public hearings, legal proceedings and two federal-provincial Joint Review Panels. Focal wildlife species, with particular emphasis on large carnivores (grizzly bears) and ungulates (elk, bighorn sheep), were a major aspect of the Cheviot environmental impact assessments and subsequent research/monitoring. The Cheviot mine was approved in 2004 with the first of a series of mine licenses required through the phased mine development. A land use planning process (LUP) is on-going for the end land use closure planning of two older coal mines (Luscar and Gregg River) located near the Cheviot Mine. This process is being informed by on-going ecological research and monitoring at all three mines. The issues and discussions surrounding the LUP are in turn informing the Cheviot Mine permit application process. Three over-arching end land use goals dominate the current mine closure planning debate. They include: 1) maintaining and enhancing focal species habitat and populations as per the original Cheviot project mandate; 2) preserving either pre-disturbance or modified recreational land use opportunities; and, 3) approximating pre-disturbance native biological diversity conditions. This paper discusses challenges and lessons learned over a 15-year period concerning the balancing of these three primary end land use goals.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".