Animal-unit equivalence of bison, wapiti, and mule deer in the aspen parkland of Alberta
Bibliographic record
Abstract
Animal-unit equivalences needed for joint-stocking calculations of ungulates are rarely studied because of difficulties deriving accurate estimates of forage intake. We used indigestible internal and external markers (double n-alkane ratio) to determine animal-unit equivalence of bison ( Bison bison (L., 1758)), wapiti ( Cervus elaphus canadensis L., 1758), and mule deer ( Odocoileus hemionus (Rafinesque, 1817)) in the aspen parkland of east-central Alberta. We hypothesized that dry matter intake would differ among species in absolute terms (kg·day–1) but not when expressed as percent body mass (%BM) or when related to metabolic mass (g·kg–1·day–1 BM0.75). We administered slow-release n-alkane capsules to 12 bison, 3 wapiti, and 11 mule deer and released them into separate 3–7 ha paddocks during summer and fall. Intake of dry matter by bison, wapiti, and mule deer differed significantly among species when expressed as total intake (p = 0.009) and %BM (p = 0.014) but not when related to metabolic mass (p = 0.237). Dry matter intake related to metabolic mass did not differ between bison and mule deer in any comparison despite a 6.8-fold difference in body size, suggesting that intake scales to metabolic mass, and is the preferred expression of animal-unit equivalents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".