EFFECTS OF BROWSING HISTORY BY ALASKAN MOOSE ON REGROWTH AND QUALITY OF FELTLEAF WILLOW
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Bibliographic record
Abstract
We studied effects of browsing history by Alaskan moose (Alces alces gigas) on re- growth and quality of feltleaf willow (Salix alaxensis) during late winter 2002 in interior Alaska, USA. We recorded extensive browsing on willows, with 55.6% of leaders on 43 plants browsed by moose and 3.9% browsed by snowshoe hares (Lepus americanus). Foraging moose removed, on average, 15.1 mm of current annual growth from willow twigs, which averaged 24.1 mm in length (62.3% removed). Twigs re-growing from 2-year-old stems that were browsed previously had larger diameters at their bud scale scar than those re-growing from stems that were not browsed in the previous year. Browsing history by moose, however, had no effect on nitrogen content, in vitro dry matter digestibility, or tannin content of willow twigs. Willows did not respond to browsing on individual twigs with an inducible defense system that involved tannins. Diameter at point of browsing (bite size) was larger on twigs that had been browsed previously than for twigs re-growing from second-year growth that had not been browsed. Moose did not exhibit an optimal bite size, but took larger-diameter bites from larger compared with smaller leaders of current annual growth. Forage selection by moose for previously browsed twigs likely relates to greater forage biomass on those twigs rather than to forage quality. We caution, however, that foraging behavior by moose cannot be understood fully without considering additional factors, including predation risk in relation to forage availability. ALCES VOL. 39: 193-202 (2003)
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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 | 0.000 | 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 it