气候变化领域集成服务门户(CCPortal): Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory

CCPortal

DOI	10.1016/j.foreco.2019.02.041
	Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory
	Minunno F.; Peltoniemi M.; Härkönen S.; Kalliokoski T.; Makinen H.; Mäkelä A.
发表日期	2019
ISSN	0378-1127
起始页码	208
结束页码	257
卷号	440
英文摘要	Policy-relevant forest models must be environment and management sensitive and provide unbiased estimates of predicted variables over their intended areas of application. While empirical models derive their structure and parameters from representative data sets, process-based model (PBM) parameters should be evaluated in ranges that have a biological meaning independently of output data. At the same time PBMs should be calibrated against observations in order to obtain unbiased estimates and an understanding of their predictive capability. By means of model data assimilation, we Bayesian calibrated a forest model (PREBAS) using an extensive dataset that covered a wide range of climatic conditions, species composition and management practices. PREBAS was calibrated for three species in Finland: Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies [L.] H. Karst.) and Silver birch (Betula pendula L.). Data assimilation was strongly effective in reducing the uncertainty of PREBAS parameters and predictions. A country-generic calibration showed robust performances in predicting forest variables and the results were consistent with yield tables and national forest statistics. The posterior predictive uncertainty of the model was mainly influenced by the uncertainty of the structural and measurement error. © 2019 The Authors
英文关键词	Bayesian calibration; Data assimilation; Forest carbon cycle; Forest inventory data; Permanent growth experiments; Process-based model
语种	英语
scopus关键词	Calibration; Carbon; Plants (botany); Uncertainty analysis; Bayesian calibration; Data assimilation; Forest carbons; Forest inventory data; Process-based modeling; Forestry; Bayesian analysis; calibration; carbon balance; coniferous forest; coniferous tree; data assimilation; ecosystem modeling; forest inventory; growth rate; prediction; Assimilation; Calibration; Carbon; Data; Estimates; Forestry; Management; Parameters; Finland; Betula pendula; Picea abies; Pinus sylvestris
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156060
作者单位	University of Helsinki, Finland; Natural Resources Institute Finland (Luke), Finland
推荐引用方式 GB/T 7714	Minunno F.,Peltoniemi M.,Härkönen S.,et al. Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory[J],2019,440.
APA	Minunno F.,Peltoniemi M.,Härkönen S.,Kalliokoski T.,Makinen H.,&Mäkelä A..(2019).Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory.Forest Ecology and Management,440.
MLA	Minunno F.,et al."Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory".Forest Ecology and Management 440(2019).