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Application of the ecosystem model and Markov Chain Monte Carlo for parameter estimation and productivity prediction

文献类型：期刊论文

作者Li, Weizhong1; Peng, Changhui1,2; Zhou, Xiaolu2; Sun, Jianfeng2; Zhu, Qiuan1; Wu, Haibin2,3; St-Onge, Benoit4
刊名ECOSPHERE
出版日期2015-12-01
卷号6期号:12
关键词Carbon Balance Data Assimilation Forest Ecosystem Model-data Fusion Parameter Estimation Triplex-flux Model
DOI10.1890/ES15-00034.1
文献子类Article
英文摘要It is increasingly being recognized that global ecological research requires novel methods and strategies in which to combine process-based ecological models and data in cohesive, systematic ways. In process-based model applications, inherent spatial and temporal heterogeneities found within terrestrial ecosystems may lead to the uncertainties of model predictions. To reduce simulation uncertainties due to inaccurate model parameters, the Markov Chain Monte Carlo (MCMC) method was applied in this study to improve the estimations of four key parameters used in the process-based ecosystem model of TRIPLEX-FLUX. These four key parameters include a maximum photosynthetic carboxylation rate of 25 degrees C (Vmax), an electron transport (Jmax) light-saturated rate within the photosynthetic carbon reduction cycle of leaves, a coefficient of stomatal conductance (m), and a reference respiration rate of 10 degrees C (R10). Seven forest flux tower sites located across North America were used to investigate and facilitate understanding of the daily variation in model parameters for three deciduous forests, three evergreen temperate forests, and one evergreen boreal forest. Eddy covariance CO2 exchange measurements were assimilated to optimize the parameters in the year 2006. After parameter optimization and adjustment took place, net ecosystem production prediction significantly improved (by approximately 25%) compared to the CO2 flux measurements taken at the seven forest ecosystem sites. Results suggest that greater seasonal variability occurs in broadleaf forests in respect to the selected parameters than in needleleaf forests. This study also demonstrated that the model-data fusion approach by incorporating MCMC method is able to better estimate parameters and improve simulation accuracy for different ecosystems located across North America.
WOS关键词SIMULATING CARBON EXCHANGE ; STOMATAL CONDUCTANCE MODEL ; DOUGLAS-FIR FOREST ; SOIL RESPIRATION ; PHOTOSYNTHETIC CAPACITY ; NONLINEAR INVERSION ; DATA ASSIMILATION ; DECIDUOUS FOREST ; HARDWOOD FOREST ; LEAF PHENOLOGY
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000367311800023
资助机构National Basic Research Program (973) of China(2013CB956602) ; National Basic Research Program (973) of China(2013CB956602) ; International S & T Cooperation Program of China(2013DFA32190) ; International S & T Cooperation Program of China(2013DFA32190) ; Fluxnet-Canada ; Fluxnet-Canada ; Natural Science and Engineering Research Council (NSERC) ; Natural Science and Engineering Research Council (NSERC) ; National Basic Research Program (973) of China(2013CB956602) ; National Basic Research Program (973) of China(2013CB956602) ; International S & T Cooperation Program of China(2013DFA32190) ; International S & T Cooperation Program of China(2013DFA32190) ; Fluxnet-Canada ; Fluxnet-Canada ; Natural Science and Engineering Research Council (NSERC) ; Natural Science and Engineering Research Council (NSERC)
源URL[http://ir.iggcas.ac.cn/handle/132A11/62130]  
专题地质与地球物理研究所_中国科学院新生代地质与环境重点实验室
作者单位1.Northwest A&F Univ, Coll Forestry, Lab Ecol Forecasting & Global Change, Yangling 712100, Shaanxi, Peoples R China
2.Univ Quebec, Inst Environm Sci, Dept Biol Sci, Montreal, PQ H3C 3P8, Canada
3.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Cenozo Geol & Environm, Beijing 100029, Peoples R China
4.Univ Quebec, Dept Geog, Montreal, PQ H3C 3P8, Canada
推荐引用方式
GB/T 7714		 Li, Weizhong,Peng, Changhui,Zhou, Xiaolu,et al. Application of the ecosystem model and Markov Chain Monte Carlo for parameter estimation and productivity prediction[J]. ECOSPHERE,2015,6(12).
APA Li, Weizhong.,Peng, Changhui.,Zhou, Xiaolu.,Sun, Jianfeng.,Zhu, Qiuan.,...&St-Onge, Benoit.(2015).Application of the ecosystem model and Markov Chain Monte Carlo for parameter estimation and productivity prediction.ECOSPHERE,6(12).
MLA Li, Weizhong,et al."Application of the ecosystem model and Markov Chain Monte Carlo for parameter estimation and productivity prediction".ECOSPHERE 6.12(2015).

入库方式： OAI收割

来源：地质与地球物理研究所

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