Effect of experimental fire on seedlings of Australian and Gondwanan trees species from a Tasmanian montane vegetation mosaic
Bibliographic record
Abstract
The montane area of the Tasmanian Wilderness World Heritage Area was recently burnt by large fires ignited by lightning, and such fires are predicted to become more frequent with climate change. The region has a mix of fire-sensitive and fire-tolerant vegetation, but there is little information available on resprouting ability of seedlings of the dominant species of these mosaics. We predicted that seedlings of species found in fire-prone locations would exhibit more post-fire resprouting than seedlings of Gondwanan relictual species, which typically occur in fire-protected locations. To test this hypothesis we compared topkill and resprouting ability of seedlings from five tree species characteristic of the montane vegetation mosaics by exposing them to a propane burner flame for 0, 15, 30, 45 and 60 s, simulating a fire intensity of 33 kW m–1. Overall, 93 of 100 flame-exposed plants were topkilled. Topkill was related to duration of flame exposure and seedling size rather than species. By contrast, resprouting of topkilled seedlings was strongly correlated with species rather than seedling size, and was not affected by duration of flame exposure. Contrary to expectations, the rainforest plant Nothofagus cunninghamii was the strongest resprouter, whereas few of the topkilled eucalypt seedlings resprouted. Our study shows the commonly held association between palaeoendemic Gondwanan species and low fire tolerance versus Australian species and high fire tolerance is overly simplistic. We need to better understand fire recovery mechanisms in the Tasmanian flora using a combination of field observation and experimental approaches.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".