Survival of Adult Female Elk in Yellowstone Following Wolf Restoration
Bibliographic record
Abstract
Counts of northern Yellowstone elk (Cervus elaphus) in northwestern Wyoming and adjacent Montana, USA, have decreased at an average rate of 6–8% per year since wolves (Canis lupus) were reintroduced in 1995. Population growth rates of elk are typically sensitive to variations in adult female survival; populations that are stable or increasing exhibit high adult female survival. We used survival records for 85 radiocollared adult female elk 1–19 years old to estimate annual survival from March 2000 to February 2004. Weighted average annual survival rates were approximately 0.83 (95% CI = 0.77–0.89) for females 1–15 years old and 0.80 (95% CI = 0.73–0.86) for all females. Our estimates were much lower than the rate of 0.99 observed during 1969–1975 when fewer elk were harvested by hunters, wolves were not present, and other predators were less numerous. Of 33 documented deaths included in our analysis, we attributed 11 to hunter harvest, 14 to predation (10 wolf, 2 unknown, 1 cougar [Puma concolor], and 1 bear [Ursus sp.]), 6 to unknown causes, and 2 to winter-kill. Most deaths occurred from December through March. Estimates of cause-specific annual mortality rates were 0.09 (0.05–0.14) for all predators, 0.08 (0.04–0.13) for hunting, and 0.07 (0.03–0.11) for wolves specifically. Wolf-killed elk were typically older (median = 12 yr) than hunter-killed elk (median = 9 yr, P = 0.03). However, elk that winter outside the park where they were exposed to hunting were also younger (median = 7 yr) than elk that we did not observe outside the park (median = 9 yr, P < 0.01). Consequently, differences in ages of elk killed by wolves and hunters may reflect characteristics of elk exposed to various causes of mortality, as well as differences in susceptibility. Unless survival rates of adult females increase, elk numbers are likely to continue declining. Hunter harvest is the only cause of mortality that is amenable to management at the present time.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".