Diet of two fossorial herbivores in a seasonally snow-covered environment
Bibliographic record
Abstract
To understand the recent elevational range expansion of European rabbits (Oryctolagus cuniculus) with declining snow cover and earlier snow thaw we examined their diet in relation to that of long-term residents, common wombats (Vombatus ursinus). The colonisation of eastern Australia by rabbits was effectively completed by 1910 when they reached an elevation of 1500 m (the winter snowline). Rabbits began to penetrate higher elevations only from the 1970s in association with anthropogenic habitat modification. Since 2011, rabbits have occupied elevations to the alpine treeline (~1850 m) throughout the year without the ameliorating presence of infrastructure or anthropogenically modified vegetation. Rabbits and wombats are both grazers preferring grasses (largely inaccessible beneath winter snow) and are spatially restricted in their foraging by their need to return to their burrows. Wombats used a much wider foraging range, enabling them to select preferred food. Rabbits, with a much smaller range, were constrained in their choice of forage mainly to plants that projected above the snow. Unexpectedly, rabbits fed intensively on leaves of eucalypts, food not typically consumed in substantial quantities by this species. These leaves, on stems regenerating after fire, will diminish in availability as stems mature, possibly halting the range expansion of rabbits.
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 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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".