The leaf size/number trade-off within species and within plants for woody angiosperms
Bibliographic record
Abstract
Background and aims – The leaf size/number trade-off has been recently established as a wide-spread and highly predictable relationship associated with between-species leaf size variation. In this study, we examine whether this trade-off relationship also applies at the between-plant (within-species), and at the between-shoot (within-plant) levels associated with spatial variation in incident light availability within tree canopies. Methods – Replicate current-year shoots were sampled from north-facing (shaded) and south-facing (sun-exposed) canopy sides of sixteen broadleaf tree species in eastern Ontario, Canada. For each shoot, measurements were recorded for mean individual leaf dry mass, number of leaves, number of side branches, and stem length, girth, and tissue dry mass. Leafing intensity was calculated as the number of leaves produced per unit of supporting stem tissue dry mass. Key results – All of the direct trait measurements had generally larger values for shoots collected from south-facing canopy sides (as expected). However, negative isometric relationships between leaf size and leafing intensity were found at the between-plant level (for Acer saccharum) and the between-shoot (within-tree) level for at least some individuals of most species. The predominant trend at the within-tree level, however, was allometric – i.e. north-facing (light-limited) shoots generally had lower individual leaf dry mass but disproportionately higher leafing intensity compared with south-facing shoots. Conclusions – The results confirm that there is a fundamental leaf size/number trade-off at the between-plant (within-species) level and also at the between-shoot (within-plant) level, as previously reported at the between-species level. But more specifically, the results reveal distinctly different leaf deployment strategies in response to spatial light variability within tree canopies: Under high light exposure, larger leaves are favoured (with lower leafing intensity imposed as a trade-off), but in deeply shaded portions of the canopy, smaller leaves result, we suggest, for two reasons: (i) they are favoured directly (because they minimize overlap of closely spaced adjacent leaves); (ii) they are imposed as a trade-off of selection favouring high leafing intensity, which in turn maximizes the size of the reserve bud bank (number of axillary meristems per unit of supporting stem tissue) available for initiating continued growth or reproduction in the following year.
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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 | 0.001 | 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 | 0.001 | 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".