Fungi and fire in Australian ecosystems: a review of current knowledge, management implications and future directions
Bibliographic record
Abstract
Fungi are essential components of all ecosystems in roles including symbiotic partners, decomposers and nutrient cyclers and as a source of food for vertebrates and invertebrates. Fire changes the environment in which fungi live by affecting soil structure, nutrient availability, organic and inorganic substrates and other biotic components with which fungi interact, particularly mycophagous animals. We review the literature on fire and fungi in Australia, collating studies that include sites with different time since fire or different fire regimes. The studies used a variety of methods for survey and identification of fungi and focussed on different groups of fungi, with an emphasis on fruit-bodies of epigeal macrofungi and a lack of studies on microfungi in soil or plant tissues. There was a lack of replication of fire treatment effects in some studies. Nevertheless, most studies reported some consequence of fire on the fungal community. Studies on fire and fungi were concentrated in eucalypt forest in south-west and south-eastern Australia, and were lacking for ecosystems such as grasslands and tropical savannahs. The effects of fire on fungi are highly variable and depend on factors such as soil and vegetation type and variation in fire intensity and history, including the length of time between fires. There is a post-fire flush of fruit-bodies of pyrophilous macrofungi, but there are also fungi that prefer long unburnt vegetation. The few studies that tested the effect of fire regimes in relation to the intervals between burns did not yield consistent results. The functional roles of fungi in ecosystems and the interactions of fire with these functions are explained and discussed. Responses of fungi to fire are reviewed for each fungal trophic group, and also in relation to interactions between fungi and vertebrates and invertebrates. Recommendations are made to include monitoring of fungi in large-scale fire management research programs and to integrate the use of morphological and molecular methods of identification. Preliminary results suggest that fire mosaics promote heterogeneity in the fungal community. Management of substrates could assist in preserving fungal diversity in the absence of specific information on fungi.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".