The projected distributions of Mastacomys fuscus and Rattus lutreolus in south-eastern Australia under a scenario of climate change: potential for increased competition?
Bibliographic record
Abstract
Animal distribution is strongly controlled by climate, especially at higher altitudes where harsher conditions favour fewer vertebrate species. A predicted consequence of climate change is increased pressure on these higher-altitude faunal communities by invasion of lower-altitude species more suited to warmer conditions. The distribution of two such species, the broad-toothed rat (Mastacomys fuscus) and swamp rat (Rattus lutreolus) (with the former generally occurring at higher altitude except in Tasmania), were examined using BIOCLIM. Modelled climate change with a 20% reduction in precipitation and a warming of 2.9°C at latitude 36°S (Snowy Mountains) and 3.4°C at 42°S (central Tasmania) suggests that M. fuscus will retreat to higher altitudes. The core areas of R. lutreolus will also contract, but significantly they will also move so that they overlap current core areas of M. fuscus on the mainland. Barrington Tops is the northernmost known location for M. fuscus and is climatically marginal. The recent invasion of Barrington Tops by R. lutreolus and decline of M. fuscus raises the question as to whether the modelled broader range changes will result in greater competition between the invading R. lutreolus and the cool-climate specialist M. fuscus, resulting in the further loss of the latter.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".