Manipulations of black bear and coyote affect caribou calf survival
Bibliographic record
Abstract
ABSTRACT The population of woodland caribou ( Rangifer tarandus ) in Newfoundland declined from approximately 94,000 to 32,000 animals between 1996 and 2013. Poor calf survival was the primary cause of the population decline, largely because of predation of newborn calves by American black bear ( Ursus americanus ) and the non‐native coyote ( Canis latrans ). This situation offered an opportunity to test the efficacy of preventative management options such as diversionary feeding and lethal removal of predators for improving calf survival. We monitored caribou calves ( n = 536) in 4 calving areas (3 untreated, 1 treatment) for 2 years (2008–2009) followed by diversionary feeding of black bears and coyotes in 2010–2011 and lethal removal of coyotes in 2012–2013. We estimated calf survival for 70 days, the period calves and females remain on the calving grounds, and for 182 days, after which calves were considered recruited into the population. Calf survival was nearly constant over the 6‐year study period on the untreated areas. Calf survival was initially lower on the treatment area compared to the untreated areas but increased substantially on the treatment area during the lethal removal period, especially during the initial 70‐day period. Predation on calves by coyote decreased substantially during the lethal removal period. Diversionary feeding had little influence on survival rates. This study suggests that lethal removal of coyotes could be a viable management option for improving calf survival, but it is expensive and logistically challenging in remote field settings. © 2016 The Wildlife Society.
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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 | 0.000 |
| 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".