Soil heating and germination: investigations using leaf scorch on graminoids and experimental seed burial
Bibliographic record
Abstract
Burns conducted to reduce fuels are usually carried out under mild weather conditions. This introduces a risk that soil heating will be insufficient to trigger germination in species with a heat-shock requirement. Resprouting graminoids with leaves or culms arising from subterranean meristems can be used to estimate soil heating because the leaf is burnt to soil level and the subterranean tissue is killed to a depth dependent on the level of soil heating. Provided the meristem survives, the length of dead tissue is exposed following subsequent growth. We sought to determine whether the length of dead tissue (scorch length) was correlated with the post-fire recovery of Acacia suaveolens, a fire-sensitive shrub with seed germination dependent on heat shock. The peak emergence depth for this species varies as a function of soil heating: temperatures above 100°C induce seed death whereas temperatures below 60°C do not break dormancy. We found that average scorch length was correlated with average seedling emergence depth. However, experimental burial of scarified (i.e. non-dormant) seeds showed that the peak emergence depth was similar for seeds sown before, after or in the absence of fire. This suggests that post-germination mortality is also depth-dependent, with seedling survival reduced at depths from 0 to 20 mm. The results suggest that survival of seedlings will be enhanced if soil heating is sufficient to promote germination of seeds buried at least 20 mm deep. Scorch lengths on graminoid leaves provide an indication of whether this condition is met.
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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 | 0.000 |
| 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 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".