Abstract
The Farquhar—von Caemmerer—Berry (FvCB) biochemical model of photosynthesis, commonly used to estimate CO2 assimilation at various spatial scales from leaf to global, has been used to assess the impacts of climate change on crop and ecosystem productivities. However, it is widely known that the parameters in the FvCB model are difficult to accurately estimate. The objective of this study was to assess the methods of Sharkey et al. and Gu et al., which are often used to estimate the parameters of the FvCB model. We generated An/Ci datasets with different data accuracies, numbers of data points, and data point distributions. The results showed that neither method accurately estimated the parameters; however, Gu et al.’s approach provided slightly better estimates. Using Gu et al.’s approach and datasets with measurement errors and the same accuracy as a typical open gas exchange system (i.e., Li-6400), the majority of the estimated parameters—Vcmax (maximal Rubisco carboxylation rate), Kco (effective Michaelis-Menten coefficient for CO2), gm (internal (mesophyll) conductance to CO2 transport) and Γ* (chloroplastic CO2 photocompensation point)—were underestimated, while the majority of Rd (day respiration) and α (the non-returned fraction of the glycolate carbon recycled in the photorespiratory cycle) were overestimated. The distributions of Tp (the rate of triose phosphate export from the chloroplast) were evenly dispersed around the 1:1 line using both approaches. This study revealed that a high accuracy of leaf gas exchange measurements and sufficient data points are required to correctly estimate the parameters for the biochemical model. The accurate estimation of these parameters can contribute to the enhancement of food security under climate change through accurate predictions of crop and ecosystem productivities. A further study is recommended to address the question of how the measurement accuracies can be improved.
Highlights
The Farquhar—von Caemmerer—Berry (FvCB) leaf photosynthesis model for C3 plants [1,2] is fundamental for the prediction of leaf responses to environmental variation [3]
Using Gu et al.’s method, all eight parameters were correctly retrieved in 23 datasets for high accuracy datasets with α > 0
There were a total of 33 datasets with all eight resolvable parameters, in which ten of the data sets did not meet the requirements set by Gu et al for the minimum data point distribution (3, 2, 3) to retrieve all eight parameters
Summary
The FvCB leaf photosynthesis model for C3 plants [1,2] is fundamental for the prediction of leaf responses to environmental variation [3]. This model has been widely used to simulate CO2 assimilation and the response of plants to climate change for different spatiotemporal scales [4,5,6,7,8,9,10,11], due to its solid theoretical basis and simplicity [12] It is frequently used in reverse to quantify the underlying biochemical properties (i.e., the model parameters) of leaves under different environmental conditions [13,14,15,16,17]. According to the different versions of FvCB model [1,20,21,22,23], up to 8 parameters (Vcmax, Kco, J, Tp, α, gi, Rd, and Γ*) can be estimated from an analysis of the response of the net assimilation rate (An) to intercellular CO2 concentration (Ci) if enough accurate data points are available [2]
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