Demographics of an Experimentally Released Population of Elk in Great Smoky Mountains National Park
Bibliographic record
Abstract
ABSTRACT We assessed the potential for reestablishing elk ( Cervus elaphus ) in Great Smoky Mountains National Park (GSMNP), USA, by estimating vital rates of experimentally released animals from 2001 to 2006. Annual survival rates for calves ranged from 0.333 to 1.0 and averaged 0.592. Annual survival for subadult and adult elk (i.e., ≥ 1 yr of age) ranged from 0.690 to 0.933, depending on age and sex. We used those and other vital rates to model projected population growth and viability using a stochastic individual‐based model. The annual growth rate (λ) of the modeled population over a 25‐year period averaged 0.996 and declined from 1.059 the first year to 0.990 at year 25. The modeled population failed to attain a positive 25‐year mean growth rate in 46.0% of the projections. Poor calf recruitment was an important determinant of low population growth. Predation by black bears ( Ursus americanus ) was the dominant calf mortality factor. Most of the variance of growth projections was due to demographic variation resulting from the small population size (n = 61). Management actions such as predator control may help increase calf recruitment, but our projections suggest that the GSMNP elk population may be at risk for some time because of high demographic variation.
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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".