GSTDTAP  > 气候变化
DOI10.1016/j.foreco.2019.03.003
A Bayesian Model Averaging approach for modelling tree mortality in relation to site, competition and climatic factors for Chinese fir plantations
Lu, Lele1,2; Wang, Hanchen1; Chhin, Sophan3; Duan, Aiguo1; Zhang, Jianguo1; Zhang, Xiongqing1,2
2019-05-15
发表期刊FOREST ECOLOGY AND MANAGEMENT
ISSN0378-1127
EISSN1872-7042
出版年2019
卷号440页码:169-177
文章类型Article
语种英语
国家Peoples R China; USA
英文摘要

Relationships between tree mortality and endogenous factors and climate factors have emerged as important concerns, and logistic stepwise regression is widely used for modeling the relationships. However, this method subsequently ignores both the variables not selected because of insignificance, and the model uncertainty due to the variable selection process. Bayesian Model Averaging (BMA) selects all possible models and uses the posterior probabilities of these models to perform all inferences and predictions. In this study, Bayesian Model Averaging (BMA) and logistic stepwise regression were used to analyze tree mortality in relation to competition, site index, and climatic factors in Chinese fir (Cunninghamia lanceolata (Lamb.) plantations established at five initial planting densities (A: 1667, B: 3333, C: 5000, D: 6667, and E: 10,000 trees/ha). Results showed that the posterior probability of the best model acquired by stepwise regression was less than that of the best model (highest posterior probability) acquired by BMA for pooling the data and density level D. Especially in the other planting densities, the model selected by stepwise regression was not in the BMA models. It indicates that the BMA method performed better than logistic stepwise regression, because BMA gave accurate posterior probability by taking into account the uncertainty of the model. In addition, the mortality increased with high competition and decreased with increasing temperature. The research has important implications for managing Chinese fir plantations under climate change.


英文关键词Tree mortality Chinese fir Endogenous factors Climate factors Bayesian Model Averaging Logistic stepwise regression
领域气候变化
收录类别SCI-E
WOS记录号WOS:000464297900017
WOS关键词LOBLOLLY-PINE ; INDIVIDUAL TREES ; LOGISTIC MODEL ; STAND-DENSITY ; WHITE SPRUCE ; LONG-TERM ; DROUGHT ; FOREST ; GROWTH ; SIZE
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/183215
专题气候变化
作者单位1.Chinese Acad Forestry, Res Inst Forestry, State Forestry Adm, Key Lab Tree Breeding & Cultivat, Beijing 100091, Peoples R China;
2.Nanjing Forestry Univ, Collaborat Innovat Ctr Sustainable Forestry South, Nanjing 210037, Jiangsu, Peoples R China;
3.West Virginia Univ, Div Forestry & Nat Resources, 322 Percival Hall,POB 6125, Morgantown, WV 26506 USA
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GB/T 7714
Lu, Lele,Wang, Hanchen,Chhin, Sophan,et al. A Bayesian Model Averaging approach for modelling tree mortality in relation to site, competition and climatic factors for Chinese fir plantations[J]. FOREST ECOLOGY AND MANAGEMENT,2019,440:169-177.
APA Lu, Lele,Wang, Hanchen,Chhin, Sophan,Duan, Aiguo,Zhang, Jianguo,&Zhang, Xiongqing.(2019).A Bayesian Model Averaging approach for modelling tree mortality in relation to site, competition and climatic factors for Chinese fir plantations.FOREST ECOLOGY AND MANAGEMENT,440,169-177.
MLA Lu, Lele,et al."A Bayesian Model Averaging approach for modelling tree mortality in relation to site, competition and climatic factors for Chinese fir plantations".FOREST ECOLOGY AND MANAGEMENT 440(2019):169-177.
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