Microhabitat use by the brush-tailed bettong (Bettongia penicillata) and burrowing bettong (B. lesueur) in semiarid New South Wales: implications for reintroduction programs
Bibliographic record
Abstract
Detailed studies of how endangered species use their environments at varied habitat scales are crucial if they are to be conserved and managed effectively. In this study, we used spool-and-line tracking to investigate the microhabitats used by the brush-tailed bettong (Bettongia penicillata) and the burrowing bettong (B. lesueur), two species with geographical ranges that have been dramatically reduced since European settlement in Australia. The study was carried out at Scotia Sanctuary, in semiarid western New South Wales, where both species have been recently reintroduced. The nocturnal movements and foraging of bettongs were associated with sites containing more canopy cover (mean 10–25%) than was available on average (0–10%). Models generated to predict the probability of bettong movements or activity points showed positive correlations with ground vegetation cover and ground vegetation height. Other microhabitat components of varying importance, including sand cover, litter cover, litter depth, crust cover, and distance to shrub/tree, were incorporated into these models. Species comparisons indicated that, although slight differences occurred in the way each species moved through the habitat, both species foraged in areas with similar microhabitat characteristics. While the models should have broad utility for the selection of favourable habitat for future release sites for B. penicillata and B. lesueur, further studies of diet and food availability are recommended to refine them further.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".