Managing habitat for mycophagous (fungus-feeding) mammals: a burning issue?
Bibliographic record
Abstract
In the past two decades the ecological relationships among mycophagous (fungus-feeding) mammals and their fungal food resources have been variously investigated. An unresolved issue stemming from this research is the importance of fire in creating and enhancing fungal supply for animals such as potoroos, bettongs and bandicoots. Some authors have suggested fire is a major positive influence, because it stimulates fruit-body production by fungi and is therefore necessary for mycophagous mammals to survive. However, careful review of relevant literature identifies no clear pattern in effects of fire on the wide range of hypogeous fungi eaten by mammals. Evidence of a ‘co-evolutionary relationship’, as some authors have implied, is also ambiguous. We are concerned that some land management agencies, which use prescribed fire for hazard reduction or silvicultural purposes, selectively use speculative data about fire effects on hypogeous fungi to further justify the fire regimes they ordinarily apply. A series of rigorous studies is necessary to better understand the effects of fire on the fruiting of hypogeous fungi and how that influences populations of mycophagous mammals.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".