Habitat use and ecologically sustainable carrying capacity for elk (cervus elaphus) in the Takhini Valley, Yukon
Bibliographic record
Abstract
Population growth of a (re)introduced elk (Cervus elaphus) herd (n = 144) in the Takhini Valley, southwest Yukon, has increased the need to determine an ecologically sustainable carrying capacity for the primary range.Elk telemetry data, aerial photographs, and contour maps were used to define the study area (95 km2), which represented 56% of the total local range used in 2007 and 2008.Plot sampling, plant community classification, and air-photo mapping were used to determine the composition and areal extent of vegetation types, each of which was used to evaluate forage availability.Seven treed and five nontreed types were recognized, with treed forest types representing 68% of the area.Nontreed vegetation produced more forage (279-652 kg/ha) than all treed types, except Populus tremuloides/Rosa acicularis-Arciostaphylos uva-ursi vegetation (438 kg/ha), which was the second-most common type in study area (15% of area).No significant differences (P 0.05) were found between crude protein amounts among vegetation types, though graminoids were lower in crude protein than 111 either forbs or shrubs (P 0.00 1).Different carrying capacity scenarios were developed based on cumulative assumptions.These included considerations of forage quantity, availability and preference, horse (Equusferus caballus) and mule deer (Odocoileus hemionus) requirements, and diet similarities with elk.Winter was the most limiting season because forage was senesced.The most conservative scenario included ecologically sustainable safe-use factors, and resulted in an estimated winter carrying capacity of 72-144 elk for the study area.The assessment of carrying capacity was most sensitive to browse consumption and competition with horses.These factors require further investigation to refine the estimated ecologically sustainable carrying capacity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".