Quantitative expression of mesophyll conductance temperature response in the FvCB model and impacts on plant gas exchange estimations

The way of quantitatively expressing mesophyll conductance (gm) in the Farquhar-von Caemmerer-Berry (FvCB) photosynthesis model and its impacts on plant gas exchange estimations have not been well explored, primarily due to huge uncertainties in gm parameterization. Here, a peaked Arrhenius function to depict gm temperature response was introduced into the FvCB model and parameterized through evaluating four different gm estimation methods in 19 C3 species at 31 experimental treatments. Results indicated that the FvCB model without explicitly considering gm cannot perform well in eight species/treatments, while the model that considers gm estimated by the chlorophyll fluorescence-gas exchange method and biochemical parameters estimated by the Bayesian retrieval algorithm was superior. Overall modeling accuracy was not further ameliorated when taking anatomy -based gm into consideration. The increasing Arrhenius function without considering the suboptimal stage of gm temperature response caused significant overestimations in photosynthesis under high leaf temperatures by 2-3 folds. The gm explicit expression had equally important effects on photosynthesis and transpiration estimations, which disagreed with the asymmetric effects on photosynthesis and transpiration estimations hypothesis proposed by Knauer et al. (2020). Literature survey plus our data indicated that observed variations of photo-synthesis optimal temperature (ToptA) were primarily explained by the gm optimal temperature (Topt_gm) (58%) rather than biochemical limitations, which disagreed with the JVr biochemical limitations hypothesis proposed by Kumarathunge et al. (2019).

Automated summary

This study investigates the quantification of mesophyll conductance (gm) in the photosynthesis model and its impact on plant gas exchange estimations. It introduces a peaked Arrhenius function to depict the temperature response of gm and evaluates four different gm estimation methods in 19 C3 species. The results show that explicitly considering gm in the model can improve the modeling accuracy, and not considering the suboptimal stage of gm temperature response can lead to significant overestimations in photosynthesis. The explicit expression of gm has equally important effects on photosynthesis and transpiration estimations.