Contemporary fire regimes in a fragmented and an unfragmented landscape: implications for vegetation structure and persistence of the fire-sensitive malleefowl
Bibliographic record
Abstract
Habitat fragmentation alters fire regimes by changing the spatial and temporal context in which fire operates, potentially altering ecosystem state and threatening taxa. In the fragmented wheatbelt of Western Australia, spatial patterns of contemporary fire and their effects on biodiversity conservation are poorly understood. We addressed this by: (1) determining if fire regimes differed between vegetation remnants of differing sizes and uncleared vegetation, using analysis of satellite imagery; (2) determining vegetation structural responses to time since fire in three habitats: mallee-shrub, Acacia shrublands and mallee-heath; and (3) exploring the consequences of these differences, using the fire-sensitive malleefowl (Leipoa ocellata) as a case study. Fire was infrequent in small remnants, more frequent in large remnants, and most frequent in uncleared areas. Key vegetation structural attributes for malleefowl, such as canopy and litter cover, increased beyond 45 years post-fire in mallee-shrub, reached a plateau in mallee-heath after 30–40 years, and declined in Acacia shrublands after 25–40 years. Senescence in long-unburnt vegetation, combined with rare contemporary fires, suggest progressive decline in habitat quality of Acacia shrublands for malleefowl in the wheatbelt. In the adjacent, continuously vegetated landscapes, more frequent (and extensive) fires in structurally developing mallee-shrub communities are of concern for malleefowl conservation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".