Degrees of population-level susceptibility of Australian terrestrial non-volant mammal species to predation by the introduced red fox (Vulpes vulpes) and feral cat (Felis catus)
Bibliographic record
Abstract
Context Over the last 230 years, the Australian terrestrial mammal fauna has suffered a very high rate of decline and extinction relative to other continents. Predation by the introduced red fox (Vulpes vulpes) and feral cat (Felis catus) is implicated in many of these extinctions, and in the ongoing decline of many extant species. Aims To assess the degree to which Australian terrestrial non-volant mammal species are susceptible at the population level to predation by the red fox and feral cat, and to allocate each species to a category of predator susceptibility. Methods We collated the available evidence and complemented this with expert opinion to categorise each Australian terrestrial non-volant mammal species (extinct and extant) into one of four classes of population-level susceptibility to introduced predators (i.e. ‘extreme’, ‘high’, ‘low’ or ‘not susceptible’). We then compared predator susceptibility with conservation status, body size and extent of arboreality; and assessed changes in the occurrence of species in different predator-susceptibility categories between 1788 and 2017. Key results Of 246 Australian terrestrial non-volant mammal species (including extinct species), we conclude that 37 species are (or were) extremely predator-susceptible; 52 species are highly predator-susceptible; 112 species are of low susceptibility; and 42 species are not susceptible to predators. Confidence in assigning species to predator-susceptibility categories was strongest for extant threatened mammal species and for extremely predator-susceptible species. Extinct and threatened mammal species are more likely to be predator-susceptible than Least Concern species; arboreal species are less predator-susceptible than ground-dwelling species; and medium-sized species (35 g–3.5 kg) are more predator-susceptible than smaller or larger species. Conclusions The effective control of foxes and cats over large areas is likely to assist the population-level recovery of ~63 species – the number of extant species with extreme or high predator susceptibility – which represents ~29% of the extant Australian terrestrial non-volant mammal fauna. Implications Categorisation of predator susceptibility is an important tool for conservation management, because the persistence of species with extreme susceptibility will require intensive management (e.g. predator-proof exclosures or predator-free islands), whereas species of lower predator susceptibility can be managed through effective landscape-level suppression of introduced predators.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".