Heat damage in sclerophylls is influenced by their leaf properties and plant environment
Bibliographic record
Abstract
:Mediterranean southwestern Australia experienced two successive days of extreme (> 45 °C) maximum temperatures and hot winds during the summer of 1991, resulting in adult mortality and extensive crown damage in a sclerophyllous mallee-heathland. To investigate the relationship between leaf attributes, plant environment, and heat tolerance in sclerophylls, measurements of plant height, leaf clustering, leaf morphology (thickness, dry density, area, perimeter/area ratio), percentage crown damage, and percentage mortality, and categories of exposure to wind, shade, and bare soils were recorded for 40 heat-damaged and 14 undamaged co-occurring species. Analyzing the entire dataset by principal components analysis showed that undamaged species had thicker leaves (on average 61% thicker) than species with damaged leaves and were more exposed to wind, sun, and bare soil. Thicker leaves are a common response to hot, dry, and more exposed environments and are more heat tolerant than thinner leaves. A separate analysis of the Proteaceae (25 damaged and six undamaged species) showed a similar trend to the overall dataset. An analysis of the Myrtaceae (10 damaged and three undamaged species) showed that wind exposure and level of shading were the most important variables influencing the degree of leaf damage. Percentage leaf damage was significantly correlated with percentage adult mortality, but not with the ability of a species to regrow (percentage of plants producing new shoots). Differences between undamaged and damaged species may be a result of preconditioning, whereby species growing in more exposed habitats were pre-adapted to tolerate periods of heat stress. It is unlikely that the study species were able to reduce leaf temperatures via transpirational cooling during the hottest part of the 2-d heatwave. The ability of a species to tolerate extreme temperature events will be determined by the interaction between leaf heat loads, leaf heat-storing capacity, and the degree of exposure to environmental elements.
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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 | 0.001 | 0.001 |
| 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".