The importance of grasstrees (Xanthorrhoea preissii) as habitat for mardo (Antechinus flavipes leucogaster) during post-fire recovery
Bibliographic record
Abstract
Grasstrees (Xanthorrhoea) are an important structural component of many Australian ecosystems and also an important resource for many fauna species. Grasstrees have distinctive morphologies, with a crown of long thin leaves and skirts, the latter of which are accumulated dead leaves; both are incinerated by fire. This study determined the morphological features of Xanthorrhoea preissii, which change in response to fire from 6 months to 21 years post-burn. In addition, using radio-telemetry and spool-tracking, we determined that grasstrees are utilised as foraging and nesting resources for mardos (Antechinus flavipes leucogaster (Gray, 1841), Marsupialia: Dasyuridae). Recently burnt grasstrees (6 months post-burn) appeared not to be used by mardos at all. We found few mardos in these recently burnt sites, and the one individual we managed to track for 126 m utilised only a single grasstree: a 2-m-tall multiple-crowned grasstree that had escaped the fire was used as a nest site. For sites 5 years post-burn, mardos selectively utilised grasstrees with larger crown areas and those with a greater number of crowns compared with a random sample of available trees. At the 14-year post-burn sites, mardos still demonstrated some selection for grasstrees, although no specific single feature could be determined as most significant. We recorded humidity and temperature buffering effects in association with post-burn accumulation of grasstree skirt material and found that even dead grasstree ‘logs’ were an important resource for nests. We conclude that mardos utilise both live and dead grasstrees for foraging and nest sites, possibly owing to the availability of dense cover, a buffered microclimate, and potentially also food resources. Fire-management policies that promote habitat heterogeneity and retain several intact-skirted grasstrees within the landscape are likely to benefit mardos.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".