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Seasonal fluctuations of photosynthetic parameters for light use efficiency models and the impacts on gross primary production estimation

Lin, Xiaofeng, Chen, Baozhang, Chen, Jing, Zhang, Huifang, Sun, Shaobo, Xu, Guang, Guo, Lifeng, Ge, Mengyu, Qu, Junfeng, Li, Lijuan, Kong, Yawen
Agricultural and forest meteorology 2017 v.236 pp. 22-35
Mediterranean climate, algorithms, ambient temperature, cold season, ecosystems, equations, forests, grasses, latitude, leaf area index, leaves, light, models, photosynthesis, primary productivity, seasonal variation, spring, summer, tropics, winter, Mediterranean region
How parameterization improves Light-use efficiency (LUE) models by taking into account the seasonal variations of the maximum LUE (εmax) has been rarely investigated. The LUE models include two categories which are the one-leaf LUE model (SL-LUE) and the two-leaf LUE model (TL-LUE) with separation of sunlit and shaded leaves (εmsu and εmsh). In this study, the SL-LUE and TL-LUE models were parameterized for 46 towers (176 site-years data) representing eighteen typical plant functional types (PFTs) by using the Metropolis-Hasting algorithm at monthly time scales. The results indicate that the maximum LUE parameters varied seasonally for most PFTs having a significant positive linear correlation with leaf area index (LAI) and ambient temperature changes. The relationships of εmsu and εmsh with εmax can be well described by linear equations, indicating the existence of general patterns across biomes. And as expected, The LUE models with the seasonal fluctuations of εmax, εmsu and εmsh significantly improved GPP estimation except for needleleaf evergreen forests in mid- and low- latitude regions. The improvements of both the SL-LUE and TL-LUE models were most significant in summer for tropical and Mediterranean climate regions, while most evident in spring and winter for temperate and boreal climate regions. Even with seasonal parameters, both the LUE models still cannot well capture GPP dynamics in cold season for some PFTs in Mediterranean and tropical regions (e.g., Tropical-BEF, C3-C4 grass). This study suggests that further improvement of modelling GPP requires taking into account seasonal variations of the key parameters.