The distribution and trophic ecology of an introduced, insular population of red-necked wallabies (<i>Notamacropus</i> <i>rufogriseus</i>)
Bibliographic record
Abstract
Introduced non-native mammals can have negative impacts on native biota and it is important that their ecologies are quantified so that potential impacts can be understood. Red-necked wallabies (Notamacropus rufogriseus (Desmarest, 1817)) became established on the Isle of Man (IOM), an island with UNESCO Biosphere status, following their escape from zoological collections in the mid-1900s. We estimated wallaby circadial activity and population densities using camera trap surveys and random encounter models. Their range in the IOM was derived from public sightings sourced via social media. Wallaby diet and niche breadth were quantified via microscopic examination of faecal material and compared with those of the European hare (Lepus europaeus Pallas, 1778). The mean (±SE) population density was 26.4 ± 6.9 wallabies/km2, the mean (±SE) population size was 1742 ± 455 individuals, and the species’ range was 282 km2, comprising 49% of the island. Wallaby diets were dominated by grasses, sedges, and rushes; niche breadth of wallabies and hares (0.55 and 0.59, respectively) and overlap (0.60) suggest some potential for interspecific competition and (or) synergistic impacts on rare or vulnerable plant species. The IOM wallaby population is understudied and additional research is required to further describe population parameters, potential impacts on species of conservation interest, and direct and indirect economic costs and benefits.
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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) | 0.001 | 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".