Optimization and evaluation of key photosynthesis parameters in forest ecosystems based on FLUXNET data and VPM model

Gross primary productivity (GPP) plays an important role in global carbon cycle. Vegetation maximum light use efficiency (ε_max) is the key parameter for GPP simulation of terrestrial ecosystem. Based on the vegetation photosynthesis model (VPM) and the eddy covariance flux data at 40 stations from FLUXNET (179 site-years of data), we identified the key model parameters influencing the simulation of GPP with VPM through one-at-a-time (OAT) method. The cross validation method was employed to optimize the key model parameters and evaluate the model performance for global forest ecosystems. The results showed that the prediction of GPP was mostly affected by ε_max, maximum temperature for photosynthesis (T_max), and optimum temperature for photosynthesis (T_opt). There were distinguishable differences for the key optimized parameters among different forest ecosystems. The optimized ε_max ranged from 0.05 to 0.08 μmol CO₂·μmol^-1 PAR (evergreen broad-leaved forest>evergreen coniferous forest>mixed forest>deciduous broad-leaved forest). The optimized T_max ranged from 38 to 48℃, while T_opt ranged from 18 to 22℃. With the optimized key parameters based on ecosystem types, the VPM was able to simulate the seasonal and inter-annual variations of GPP in four forest ecosystems.