The West Central Alberta Woodland Caribou Landscape Plan: Using a Modeling Approach to Develop Alternative Scenarios
Bibliographic record
Abstract
Woodland caribou (Rangifer tarandus) are classified as threatened in Alberta. In support of Canada's Species at Risk Act, a Recovery Plan for Woodland Caribou in Alberta was completed in 2004 which required local implementation plans to be completed within 5 areas of the province. The West Central Alberta Caribou Landscape Plan (WCCLP) is the first of these to be initiated and it addresses the recovery strategies for 4 herds. Two aspatial computer models built on the STELLA© modelling platform (ISee Systems, 2007) were used to assist the planning team in evaluating cumulative effects and alternative scenarios for caribou conservation. The ALCES© (Forem Technologies 2008) modelling tool was used to forecast potential changes in the west central Alberta landscape over time. Yearly landscape condition outputs from ALCES© were then exported into a caribou-specific population model, REMUS© (Weclaw, 2004), that was used to project potential population responses by woodland caribou, other primary prey species [moose (Alces alces), elk (Cervus elaphus) and deer (Odocoileus sp.)] and wolves (Canis lupus) (Weclaw & Hudson, 2004). Simulated habitat management strategies that resulted in the highest likelihood of caribou recovery included the maintenance of a high proportion of old forest, the aggregation of industrial footprints and the reclamation of historic seismic lines (although the latter took decades to provide real dividends). Sharing of industrial roads, protection of fragments of old-growth, and expanding an already aggressive fire control strategy in Alberta had little additional effect on caribou recovery. Simulated population management strategies that were successful all involved decades of intensive wolf control, either directly or indirectly through intensive primary prey control (with the exception of woodland caribou) until old-growth forests recovered to densities that provided caribou habitat and decreased alternate prey of wolves. Although this modelling approach makes broad assumptions, it provides simple fundamental relationships that were useful in a multi-stakeholder team setting when evaluating the efficacy of different management strategies for the conservation of woodland caribou.
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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 | 0.000 |
| 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".