Leaf Longevity as a Normalization Constant in Allometric Predictions of Plant Production
Bibliographic record
Abstract
In metabolic scaling theory the size-dependence of plant processes is described by a power function of form Y=Y o M (θ) where Y is a characteristic such as plant productivity that changes with plant size (M) raised to the θ (th) power and Y o is a normalization constant that adjusts the general relationship across environments and species. In essence, the theory considers that the value of θ arises in the size-dependent relationship between leaf area and vascular architecture that influences plant function and that Y o modulates this general relationship to account for ecological and evolutionary effects on the exchange of resources between plant and environment. Enquist and colleagues have shown from first principles that Y o is a function of carbon use efficiency, the carbon fraction of a plant, the area-specific carbon assimilation rate of a leaf, the laminar area of a leaf, and the mass of a leaf. We show that leaf longevity provides a functional integration of these traits that can serve as a simpler normalization in scaling plant productivity for individual species and potentially for mixed-species communities as well.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".