Does diet constrain the occupation of high elevations by macropods? A comparison between Macropus rufogriseus and Wallabia bicolor
Bibliographic record
Abstract
The ability to utilise a diet of shrubs or trees is key to the survival of herbivores in deep snow. However, reduction in snow depth with climate change may allow herbivores into higher elevations where herbfields are dominant. Wallabia bicolor occurs above the winter snowline of the Snowy Mountains in the subalpine zone, whereas Macropus rufogriseus, does not although it is present in alpine Tasmania. The winter diet of W. bicolor in the Snowy Mountains consisted of shrubs, trees, and herbs. With >60% of food sources (shrubs and trees) available above the snow, the change from occupation of habitat below the winter snowline to above requires little change in its diet. Consumption of shrubs, forbs and monocots by M. rufogriseus was similar between the Snowy Mountains and alpine Tasmania. M. rufogriseus includes a high proportion of shrubs in its diet; however, it may be excluded from snow-covered habitat due to a lesser ability to utilise poor-quality browse. Globally, migratory herbivores respond to deep snow with seasonal movements. However, W. bicolor and M. rufogriseus are not migratory and can only occupy higher elevations of the Snowy Mountains as snow depth and duration diminish. Because they do not currently occupy the alpine zone and the vegetation has not evolved to accommodate their presence, their impact on alpine vegetation is likely to be greater than migratory alpine grazers/browsers.
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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 | 0.000 |
| 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) | 0.002 | 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".