Maximum carboxylation rate estimation with chlorophyll content as a proxy of rubisco content
Bibliographic record
Abstract
The maximum carboxylation rate (Vcmax) is a key parameter in determining the plant photosynthesis rate per unit leaf area. However, most terrestrial biosphere models currently treat Vcmax as constants changing only with plant functional types, leading to large uncertainties in modelled carbon fluxes. Vcmax is tightly linked with Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco). Here we investigated the relationship between leaf chlorophyll content and Rubisco (Chl-Rub) within a winter wheat paddock. With chlorophyll as a proxy of Rubisco, a semi-mechanistic model was developed to model Vcmax25. The Chl-Rub relationship was validated using measurements in a temperate forest in Canada. The results showed that Rubisco was strongly correlated with chlorophyll (R2 = 0.96, p < 0.001) for winter wheat, due to the absorption of light energy by chlorophyll and the amount of CO2 catalysed by Rubisco are tightly coupled. Incorporating the Chl-Rub relationship into the semi-mechanistic model, the root mean square error of modelled Vcmax25 was the lowest among all estimation models. The slopes of Chl-Rub relations were almost identical for the winter wheat and temperate forest, demonstrating the potential for using leaf chlorophyll content as a proxy of leaf Rubisco in modelled Vcmax25 at large spatial scales. We anticipate that improving Vcmax25 estimates over time and space will reduce uncertainties in terrestrial biosphere models and improve the estimates of global carbon budgets.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.009 |
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; both teacher heads agree on what is shown here.
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".