Using approximate Bayesian computation to infer photosynthesis model parameters
(2.Department of Environmental Science, Hainan University, Haikou, China 570228)
【Abstract】We developed a method, namely Adaptive Population Monte Carlo Approximate Bayesian Computation (APMC), to estimate the parameters of Farquhar photosynthesis model. Treating the canopy as a big leaf, we applied this method to derive the parameters at canopy scale. Validations against observational data showed that the parameters estimated based on the APMC optimization were un-biased for predicting the photosynthetic rate. We conclude that APMC has greater advantages in estimating the model parameters than those of the conventional nonlinear regression models.
【Keywords】 Monte Carlo; big-leaf model; Farquhar photosynthesis model; net ecosystem exchange;
(Translated by CHEN YF)
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