Modeling tree mortality in relation to climate, initial planting density, and competition in Chinese fir plantations using a Bayesian logistic multilevel method
Modeling tree mortality in relation to climate, initial planting density, and competition in Chinese fir plantations using a Bayesian logistic multilevel method
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使用贝叶斯逻辑多级方法对杉木人工林中树木死亡率与气候、初始种植密度和竞争的关系进行建模
DOI：
10.1139/cjfr-2017-0215
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发表时间：
2017-06
影响因子：
2.2
通讯作者：
Zhang Jianguo
中科院分区：
文献类型：
--
作者：
Zhang Xiongqing;Cao Quang V.;Duan Aiguo;Zhang Jianguo
林木死亡率模型是模拟森林动态过程的重要工具，Logistic回归模型被广泛应用于林木死亡率的建模。然而，大多数已经开发的死亡率模型通常忽略了层次结构。以杉木（Cunninghamia lanceolata（Lamb.）Hook.）中国南方的种植园。结果表明，贝叶斯三水平模型是最好的描述树木死亡率数据与多个来源的未观察到的异质性相比，固定效应和两个水平的模型。林木死亡率在林木水平上的方差分配系数远大于在样地水平上的方差分配系数。初植密度和地位指数与死亡率呈正相关，对称竞争与死亡率呈负相关。对于气候变量，死亡率...
Tree mortality models are important tools for simulating forest dynamic processes, and logistic regression is widely used for modeling tree mortality. However, most of the mortality models that have been developed generally ignore the hierarchical structure. In this study, Bayesian logistic multilevel mortality models were developed with the independent variables of initial planting density, competition, site index, and climate factors in Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantations in southern China. The results showed that a Bayesian three-level model was best for describing tree mortality data with multiple sources of unobserved heterogeneity compared to fixed-effects and two-level models. The variance partition coefficient of tree mortality due to the tree level was much larger than that due to the plot level. The initial planting density and site index were positively correlated with mortality and symmetric competition was negatively correlated. For climate variables, the mortality...
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影响因子：
0.5
作者：
M. D. Junior;P. A. Trazzi;A. Higa;R. Seitz
通讯作者：
M. D. Junior;P. A. Trazzi;A. Higa;R. Seitz
影响因子：
8.8
作者：
Phillip J van Mantgem;N. Stephenson
通讯作者：
Phillip J van Mantgem;N. Stephenson
影响因子：
1.4
作者：
J. Vanclay
通讯作者：
J. Vanclay
影响因子：
3.7
作者：
Dehai Zhao;B. Borders;Mingliang Wang;Michael B Kane
通讯作者：
Dehai Zhao;B. Borders;Mingliang Wang;Michael B Kane
影响因子：
3.3
作者：
M. Masuda;R. Stone
通讯作者：
M. Masuda;R. Stone