Intracanopy variation in leaf morphology and physiology in dominant shrubs of Florida’s xeric uplands
Bibliographic record
Abstract
The variation in morphological traits and photosynthetic potentials associated with light conditions in the canopy can determine whole-plant function. However, leaf structure–function relationships are poorly studied in ecosystems experiencing nominal light attenuation. We examined morphological leaf traits (area, specific leaf area, thickness, revoluteness, length–width) and photosynthetic traits estimated from rapid light curves (PARsat, ETRmax, light harvesting efficiency α) in seven shrub species in two xeric upland ecosystems of Florida: rosemary scrub and sandhill. Across species and ecosystem types, shade leaves had greater specific leaf area, were thinner, and less revolute than sun leaves. Surprisingly, shade leaves had smaller areas than sun leaves. Three out of six species showed a tight relationship between morphological and photosynthetic traits. Species common to both sandhill and rosemary scrub ecosystems showed similar photosynthetic traits but greater sclerophylly in the scrub ecosystem. Overall, greater leaf thickness and greater leaf area of upper canopy leaves yielded higher photosynthetic capacities and saturation at higher photon flux densities compared with lower canopy leaves. Our results suggest that variation in leaf morphological traits governed by patterns in light availability have functional significance; however, ecosystem properties such as nutrient availability might also impact light-driven structure-function relationships.
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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 | 0.000 |
| 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".