The importance of species-specific and temperature-sensitive parameterisation of A/C_i models: A case study using...

Leaf gas exchange measurements are an important tool for inferring a plant's photosynthetic biochemistry. In most cases, the responses of photosynthetic CO₂ assimilation to variable intercellular CO₂ concentrations (A/C_i response curves) are used to model the maximum (potential) rate of carboxylation by ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco, V_cmax) and the rate of photosynthetic electron transport at a given incident photosynthetically active radiation flux density (PAR; J_PAR). The standard Farquhar-von Caemmerer-Berry model is often used with default parameters of Rubisco kinetic values and mesophyll conductance to CO₂ (g_m) derived from tobacco that may be inapplicable across species. To study the significance of using such parameters for other species, here we measured the temperature responses of key in vitro Rubisco catalytic properties and g_m in cotton (Gossypium hirsutum cv. Sicot 71) and derived V_cmax and J₂₀₀₀ (J_PAR at 2000 µmol m^-2 s^-1 PAR) from cotton A/C_i curves incrementally measured at 15°C-40°C using cotton and other species-specific sets of input parameters with our new automated fitting R package 'OptiFitACi'. Notably, parameterisation by a set of tobacco parameters produced unrealistic J₂₀₀₀:V_cmax ratio of <1 at 25°C, two- to three-fold higher estimates of V_cmax above 15°C, up to 2.3-fold higher estimates of J₂₀₀₀ and more variable estimates of V_cmax and J₂₀₀₀, for our cotton data compared to model parameterisation with cotton-derived values. We determined that errors arise when using a g_m,25 of 2.3 mol m^-2 s^-1 MPa^-1 or less and Rubisco CO₂-affinities in 21% O₂ (K_C ^21%O2) at 25°C outside the range of 46-63 Pa to model A/C_i responses in cotton. We show how the A/C_i modelling capabilities of 'OptiFitACi' serves as a robust, user-friendly, and flexible extension of 'plantecophys' by providing simplified temperature-sensitivity and species-specificity parameterisation capabilities to reduce variability when modelling V_cmax and J₂₀₀₀.