The effect of leaf shape on the thermoregulation and frost tolerance of an annual vine, <i>Ipomoea hederacea</i> (Convolvulaceae)
Bibliographic record
Abstract
PREMISE OF STUDY: Leaf shape is predicted to have important ecophysiological consequences; for example, theory predicts that lobed leaves should track air temperature more closely than their entire-margined counterparts. Hence, leaf-lobing may be advantageous during cold nights (∼0°C) when there is the risk of damage by radiation frost (a phenomenon whereby leaves fall below air temperature because of an imbalance between radiational heat loss and convective heat gain). METHODS: Here, we test whether radiation frost can lead to differential damage between leaf shapes by examining a leaf-shape polymorphism in Ipomoea hederacea, where leaves are either lobed or heart-shaped depending on a single Mendelian locus. We logged leaf temperature during midautumn, and measured chlorophyll fluorescence and survival as proxies of performance. Furthermore, we tested if the leaf-shape locus confers freezing tolerance using freezing assays on leaf tissue from different leaf shapes. KEY RESULTS: We found that lobed leaves consistently remain warmer than heart-shaped leaves during the night, but that no pattern emerged during the day, and that temperature differences between leaf shapes were typically small. Furthermore, we found that leaf types did not differ in frost tolerance, but that a 1°C decrease leads to a transition from moderate to complete damage. CONCLUSIONS: Our results demonstrate that Ipomoea hederacea leaf shapes do experience different nighttime temperatures, and that only minor temperature differences can lead to disparate levels of freezing damage, suggesting that the differential thermoregulation could result in different levels of frost damage.
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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".