A tale of two parks: contemporary fire regimes of Litchfield and Nitmiluk National Parks, monsoonal northern Australia
Bibliographic record
Abstract
Fires burn vast areas of the monsoonal savannas of northern Australia each year. This paper describes the contemporary fire regimes of two ecologically similar, relatively large national parks (Litchfield—1464 km2; Nitmiluk—2924 km2) in the Top End of the Northern Territory, over 8 and 9 years, respectively. Fire histories for both parks were derived from interpretation of LANDSAT TM imagery, supplemented with NOAA-AVHRR for cloudy periods at the end of the 7-month dry season ( c . April–Oct). Data concerning seasonality, extent and frequency of burning were analysed with respect to digital coverages for the park as a whole, landscape units, vegetation types, infrastructure and tenure boundaries. Ground-truth data established that interpreted accuracy overall, for 2 assessment years, ranged between 82 and 91% for both parks. Over 50% of Litchfield and 40% of Nitmiluk was burnt on average over this period, with Litchfield being burnt substantially in the earlier, cooler, and moister, dry season, and Nitmiluk mostly in the parched late dry season, after August. On both parks the current frequency of burning in at least low open woodland / heath habitats is ecologically unsustainable. Both parks are prone to extensive fire incursions. The data support earlier regional assessments that the average fire return interval is around 2 years in at least some areas of northern Australia. Nevertheless, comparison of contemporary fire regimes operating in three major regional national parks shows distinct differences, particularly with respect to the extent and seasonality (hence intensity) of burning in relation to different landscape components. Management implications are considered in discussion.
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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) | 0.001 | 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 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".