Conditions for caribou persistence in the wolf-elk-caribou systems of the Canadian Rockies
Bibliographic record
Abstract
Woodland caribou populations are considered threatened in Alberta and have declined in the Canadian Rocky Mountain National Parks of Banff and Jasper despite protection from factors causing caribou populations to decline outside of parks. Recent research emphasizes the importance of the numeric response of wolves to moose in moose-caribou-wolf systems to caribou persistence. Moose are rare in the Canadian Rockies, where the dominant ungulate prey for wolves is elk. Few studies have explored wolf-elk dynamics and none have examined implications for caribou. We used data collected in Banff to estimate the numeric response of wolves to elk from 1985 to 2005. Because no caribou kill-rate data exist for the Rockies, we explore the consequences of a range of hypothetical kill-rates based on kill-rates of alternate prey collected from 1985 to 2000 in Banff. We then multiplied the numeric response of wolves by the estimated caribou kill-rates to estimate the wolf predation response on caribou as a function of elk density. Caribou predation rates were inversely density dependent because wolf numbers depend on prey species besides caribou in multiple prey species systems. We then combined this simple wolf-elk-caribou model with observed demographic and population estimates for Banff and Jasper caribou from 2003-2004 and solved for the critical kill-rate thresholds above which caribou populations would decline. Using these critical kill-rate thresholds, Jasper caribou are likely to persist when wolf densities are below 2.1 - 4.3 wolves/1000km2 and/or when elk densities are below 0.015- 0.033 elk/km2. Thresholds for Banff caribou persistence are much lower because of inverse density dependence. Future research is needed on some of the necessary assumptions underlying our modeling including multi-prey wolf numeric responses, wolf kill-rates of caribou, caribou mortality by other predators, and spatial aspects of wolf-elk-caribou dynamics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".