Invading white‐tailed deer change wolf–caribou dynamics in northeastern Alberta
Bibliographic record
Abstract
Abstract Human‐caused habitat change has been implicated in current woodland caribou ( Rangifer tarandus caribou ) population declines across North America. Increased early seral habitat associated with industrial footprint can result in an increase in ungulate densities and subsequently those of their predator, wolves ( Canis lupus ). Higher wolf densities can result in increased encounters between wolves and caribou and consequently higher caribou mortality. We contrasted changes in moose ( Alces alces ) and deer ( Odocoileus spp.) densities and assessed their effects on wolf–caribou dynamics in northeastern Alberta, Canada, pre (1994–1997) versus post (2005–2009) major industrial expansion in the region. Observable white‐tailed deer ( O. virginianus ) increased 17.5‐fold but moose remained unchanged. Wolf numbers also increased from approximately 6–11.5/1,000 km 2 . Coincident with these changes, spatial overlap between wolf pack territories and caribou range was high relative to the mid‐1990s. The high number of wolf locations in caribou range suggests that forays were not merely exploratory, but rather represented hunting forays and denning locations. Scat analysis indicated that wolf consumption of moose declined substantively during this time period, whereas use of deer increased markedly and deer replaced moose as the primary prey of wolves. Caribou increased 10‐fold in the diet of wolves and caribou population trends in the region changed from stable to declining. Wolf use of beaver ( Castor canadensis ) increased since the mid‐1990s. We suggest that recent declines in woodland caribou populations in the southerly extent of their range have occurred because high deer densities resulted in a numeric response by wolves and consequently higher incidental predation on caribou. Our results indicate that management actions to conserve caribou must now include deer in primary prey and wolf reduction programs. © 2010 The Wildlife Society
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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 | 0.000 |
| 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 | 0.000 | 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".