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- Title
Sensitivity analysis and estimation using a hierarchical Bayesian method for the parameters of the FvCB biochemical photosynthetic model.
- Authors
Han, Tuo; Zhu, Gaofeng; Ma, Jinzhu; Wang, Shangtao; Zhang, Kun; Liu, Xiaowen; Ma, Ting; Shang, Shasha; Huang, Chunlin
- Abstract
Photosynthesis is a major process included in land surface models. Accurately estimating the parameters of the photosynthetic sub-models can greatly improve the ability of these models to accurately simulate the carbon cycle of terrestrial ecosystems. Here, we used a hierarchical Bayesian approach to fit the Farquhar–von Caemmerer–Berry model, which is based on the biochemistry of photosynthesis using 236 curves for the relationship between net CO2 assimilation and changes in the intercellular CO2 concentration. An advantage of the hierarchical Bayesian algorithm is that parameters can be estimated at multiple levels (plant, species, plant functional type, and population level) simultaneously. The parameters of the hierarchical strategy were based on the results of a sensitivity analysis. The Michaelis–Menten constant (Kc25), enthalpies of activation (EJ and EV), and two optical parameters (θ and α) demonstrated considerable variation at different levels, which suggests that this variation cannot be ignored. The maximum electron transport rate (Jmax25), maximum rate of Rubisco activity (Vcmax25), and dark respiration in the light (Rd25) were higher for broad-leaved plants than for needle-leaved plants. Comparison of the model's simulated outputs with observed data showed strong and significant positive correlations, particularly when the model was parameterized at the plant level. In summary, our study is the first effort to combine sensitivity analysis and hierarchical Bayesian parameter estimation. The resulting realistic parameter distributions for the four levels provide a reference for current and future land surface models. Furthermore, the observed variation in the parameters will require attention when using photosynthetic parameters in future models.
- Subjects
BIOCHEMICAL models; SENSITIVITY analysis; CARBON cycle; PARAMETER estimation; ELECTRON transport; PARTIAL pressure; HETEROTROPHIC respiration
- Publication
Photosynthesis Research, 2020, Vol 143, Issue 1, p45
- ISSN
0166-8595
- Publication type
Article
- DOI
10.1007/s11120-019-00684-z