Run rabbit run: spotted-tailed quoll diet reveals invasive prey is top of the menu
Bibliographic record
Abstract
Information about the ecological functional roles of native predators may help inform the conservation of wildlife and pest management. If predators show preferences for certain prey, such as invasive species, this could potentially be used as a conservation tool to help restore degraded (e.g. overgrazed) ecosystems via the reintroduction of native predators and suppression of exotic prey (e.g. introduced herbivores). The diet of spotted-tailed quolls was studied in a fenced reserve in south-eastern Australia where native mammals have been reintroduced, foxes and cats removed, but invasive European rabbits still persist. A total of 80 scats were collected over 12 months and analysis of macroscopic prey remains was conducted to determine diet. Rabbits were by far the most commonly consumed prey species by volume (~76%) and frequency (~60%), followed by brushtail possums (~11% for both volume and frequency), and other small and medium-sized native mammals in much smaller amounts. Quoll scat analysis revealed 10 mammal species in total, eight of which were native. Bird, reptile and invertebrate remains were uncommon in quoll scats. This suggests that spotted-tailed quolls may show a preference for preying on invasive European rabbits in certain contexts, and this could potentially be used as part of quoll reintroductions to aid rabbit population suppression and ecosystem restoration.
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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 | 0.001 | 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".