Leaf Anatomical Traits of Lianas and Trees at the Canopy of Two Contrasting Lowland Tropical Forests in the Context of Leaf Economic Spectrum
Bibliographic record
Abstract
The leaf economic spectrum describes a comprehensive framework of how the surrounding environment modulates leaf functional traits (LFT) and how these are associated between them. This framework has traditionally focused on physiological, chemical, and biomass assignation traits, but rarely in leaf anatomical traits. Here we compare leaf anatomical metrics and traits of 40 liana and tree species from two lowland tropical forests in Panama with contrasting rainfall regimes: Parque Natural Metropolitano (dry-forest) and Parque Nacional San Lorenzo (wet-forest). Then we evaluate how anatomical traits are associated with well-established LFTs. Anatomical metrics were collected from leaf cross-section images estimating the area, thickness, cell count, and size of the upper and lower epidermis and palisade and spongy mesophyll. Ratios between metrics were performed as potential anatomical traits to reduce the leaf size effect between species. Our results suggest that anatomical changes between life forms are associated with increases in the palisade area and thickness of trees in comparison with lianas, while anatomical changes between forest type species are related to increases in the spongy area and thickness of wet-forest species than dry-forest. These differences could be associated with the high photosynthetic rates of trees or the need to enhance the gas exchange in humid environments. Our results also suggest that anatomical traits are related to well-established LFT; however, the degree of association between them may depend on the life forms and forest type. For example, our results suggest that reductions in the palisade and spongy cell density are associated with increases in leaf mass area and maximum photosynthetic capacity, but this association was not observed when we compared life forms or forest types. The use of leaf anatomical information may facilitate to describe the mechanism that drives the leaf economy, improving our understanding of the resource allocation strategies embedded in functional groups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".