Nutritional quality of willows for moose: effects of twig age and diameter.
Bibliographic record
Abstract
Alaskan moose (Alces alces gigas) consume willow (Salix spp.) as a fundamental component of their winter diet. We collected Barclay willow (S. barclayi) from 5 nearby sites (1580 m apart) on the Kenai Peninsula, Alaska, USA, during winter 1999-2000. We tested effects of diameter and age of twigs on nutritional quality of willows for moose. Smaller-diameter twigs had higher in vitro dry matter digestibility (IVDMD), and protein content, but lower fiber content (P < 0.001) than larger twigs. An inverse relationship occurred between the age of twigs and protein content (P < 0.001), with older-aged twigs containing less protein. Accordingly, age of twigs was negatively related to fiber content (P = 0.002). Conversely, no relation existed between age of twigs and IVDMD (P = 0.34). Tannin content (P < 0.001) and age of twigs (P = 0.04) varied among sites, with older twigs possessing more tannins than younger ones. No difference in tannins, however, occurred between diameter categories of twigs (P = 0.48). Digestible energy differed between diameter categories (P = 0.02) and among ages of twigs (P = 0.02), as well as among collection sites (P < 0.001). Thus, structural components of the twig to support growth were more important in affecting digestibility, whereas age of the twig was more influential in determining nitrogen and tannin content. The relation between twig age and tannin content, however, was the inverse of that expected. More research is needed to understand how quality of winter browse interacts with additional factors, such as predation risk, population density, and allometric differences between sexes, to affect diet selection and foraging behavior of moose and other large herbivores. ALCES VOL. 38: 143-154 (2002)
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".