利用非线性混合模型模拟杉木林优势木平均高  

Modeling Dominant Height for Chinese Fir Plantation Using a Nonlinear Mixed-Effects Modeling Approach

作　　者：李春明[1] 张会儒[1] 

机构地区：[1]中国林业科学研究院资源信息研究所,北京100091

出　　处：《林业科学》2010年第3期89-95,共7页Scientia Silvae Sinicae

基　　金：中央级公益性科研院所基本科研业务费专项资金"不同发展阶段的天然林生长模拟研究"(RIFRIGTZGZ2007005);国家"十一五"科技支撑课题"东北天然林保护与可持续经营技术试验示范"(2006BAD03A08)部分研究内容

摘　　要：介绍国内外利用非线性混合效应模型方法模拟林分优势木平均高的研究进展情况。以江西省大岗山实验局不同初植密度的人工杉木为研究对象,考虑初植密度的随机效应,选择常用的Richards和Logistic形式,通过变换混合效应参数个数来构造优势木平均高和林龄关系的非线性混合效应模型。采用确定系数、均方误差和平均绝对残差等模型评价指标对不同模型的精度进行比较分析。结果表明:无论是Richards形式还是Logistic形式的优势木平均高与林龄关系的非线性混合效应模型,其估计精度比传统的回归模型估计精度明显提高;但是增加随机效应参数个数并不一定绝对提高模型的估计精度,相反估计精度有可能下降。以(4)式为基础的Logistic方程中,3个参数都作为混合模型的模拟精度最高。The paper described the evolvement of home and abroad in modeling dominant height using nonlinear mixed effect models. The nonlinear mixed effect model of dominant height related with forest age was developed by changing the number of random effect parameter of Richards and Logistic growth model based on the data of Chinese Fir plantation of different initial planting density in Dagangshan Experiment Bureau of Jiangxi Province. The simulation’s precision of different models was compared with coefficient of determination,mean square error and absolute bias. The results showed that the precision of nonlinear mixed effect model which takes into account the random effect of different initial planting density was better than that of conventional regression model. But increasing the number of random effect parameter was not absolutely able to increase the simulation’s precision of model,on the contrary the precision may decrease possibly. The simulation’s precision of Logistics including three random effect parameter based on the fourth equation was maximal.

关 键 词：杉木 非线性混合效应模型 优势木平均高 Richards形式 Logistic形式 

分 类 号：S758.5[农业科学—森林经理学]