Estimating CO2 Response in a Mixed Broadleaf Forest using the Dynamic Assimilation Technique

Background Estimating the CO ₂ response of forest trees is of great significance in plant photosynthesis research. CO ₂ response measurement is traditionally employed under steady state conditions. With the development of open-path gas exchange systems, the Dynamic Assimilation Technique (DAT), allows measurement under non-steady state conditions. This greatly improves the efficiency and data density of CO ₂ response measurement. However, the effects of different models in fitting the DAT data have not been extensively verified. Results This research was conducted for three common broadleaf tree species ( Ulmus macrocarpa , Fraxinus mandshurica , and Tilia amurensis ) in North Eastern China. Among the three species, Fraxinus mandshurica is the most adapted to high CO ₂ concentration conditions. Four models were compared, the rectangular hyperbola (RH) model, the Michaelis-Menten (MM) model, the modified rectangular hyperbola (MRH) model and a non-rectangular hyperbola (NRH) model. Conclusions Considering the model parsimony and parameter accuracy, the NRH model emerged as the best choice (R ²  = 0.9966, RMSE = 0.1862, AIC=-199.86). This study provides a reference for the further application of DAT in the field of photosynthesis.