Global S&T Development Trend Analysis Platform of Resources and Environment
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, Francesco1; Peltoniemi, Mikko2; Harkonen, Sanna1; Kalliokoski, Tuomo1; Makinen, Harri2; Makela, Annikki1 | |
2019-05-15 | |
发表期刊 | FOREST ECOLOGY AND MANAGEMENT |
ISSN | 0378-1127 |
EISSN | 1872-7042 |
出版年 | 2019 |
卷号 | 440页码:208-257 |
文章类型 | Article |
语种 | 英语 |
国家 | Finland |
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. |
英文关键词 | Process-based model Data assimilation Bayesian calibration Forest carbon cycle Forest inventory data Permanent growth experiments |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000464297900021 |
WOS关键词 | NORWAY SPRUCE ; SITE PRODUCTIVITY ; DATA ASSIMILATION ; ECOSYSTEM MODEL ; BIOMASS ; STAND ; PHOTOSYNTHESIS ; UNCERTAINTY ; RESPIRATION ; SENSITIVITY |
WOS类目 | Forestry |
WOS研究方向 | Forestry |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/183219 |
专题 | 气候变化 |
作者单位 | 1.Univ Helsinki, Helsinki, Finland; 2.Nat Resources Inst Finland Luke, Helsinki, Finland |
推荐引用方式 GB/T 7714 | Minunno, Francesco,Peltoniemi, Mikko,Harkonen, Sanna,et al. Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory[J]. FOREST ECOLOGY AND MANAGEMENT,2019,440:208-257. |
APA | Minunno, Francesco,Peltoniemi, Mikko,Harkonen, Sanna,Kalliokoski, Tuomo,Makinen, Harri,&Makela, Annikki.(2019).Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory.FOREST ECOLOGY AND MANAGEMENT,440,208-257. |
MLA | Minunno, Francesco,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):208-257. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论