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东北林区4个天然针叶树种单木生物量模型误差结构及可加性模型

董利虎1,李凤日1**,宋玉文2   

  1. (1东北林业大学林学院,哈尔滨 150040;2吉林省松江河林业局,吉林白山 134300)
  • 出版日期:2015-03-18 发布日期:2015-03-18

Error structure and additivity of individual tree biomass model for four natural conifer species in Northeast China.

DONG Li-hu1, LI Feng-ri1, SONG Yu-wen2   

  1. (1School of Forestry, Northeast Forestry University, Harbin 150040, China; 2Songjianghe Forestry Bureau, Baishan 134300, Jilin, China)
  • Online:2015-03-18 Published:2015-03-18

摘要:

基于276株实测生物量数据,构建了东北林区红松、臭冷杉、红皮云杉和兴安落叶松4个天然针叶树种总量及各分项生物量一元、二元可加性生物量模型.采用似然分析法判断总量及各分项生物量异速生长模型的误差结构(可加型或相乘型),而模型参数估计采用非线性似乎不相关回归模型方法.结果表明: 经似然分析法判断,4个天然树种总量及各分项生物量异速生长模型的误差结构都是相乘型的,对数转换的可加性生物量可以被选用.各树种可加性生物量模型的调整后确定系数Ra2为0.85~0.99,平均相对误差为-7.7%~5.5%,平均相对误差绝对值<30.5%.增加树高可以显著提高各树种可加性生物量模型的拟合效果和预测能力,而且总量、地上和树干生物量模型效果较好,树根、树枝、树叶和树冠生物量模型效果较差.所建立的可加性生物量模型的预测精度为77.0%~99.7%(平均92.3%),可以很好地预估东北林区天然红松、臭冷杉、红皮云杉和兴安落叶松的生物量.

 

Abstract: Based on the biomass data of 276 sampling trees of Pinus koraiensis, Abies nephrolepis, Picea koraiensis and Larix gmelinii, the monoelement and dualelement additive system of biomass equations for the four conifer species was developed. The model error structure (additive vs. multiplicative) of the allometric equation was evaluated using the likelihood analysis, while nonlinear seemly unrelated regression  was used to estimate the parameters in the additive system of biomass equations. The results indicated that the assumption of multiplicative error structure was strongly supported for the biomass equations of total and tree components for the four conifer species. Thus, the additive system of logtransformed biomass equations was developed. The adjusted coefficient of determination (Ra2) of the additive system of biomass equations for the four conifer species was 0.85-0.99, the mean relative error  was between -7.7% and 5.5%, and the mean absolute relative
error  was less than 30.5%. Adding total tree height in the additive systems of biomass equations could significantly improve model fitting performance and predicting precision, and the biomass equations of total, aboveground and stem were better than biomass equations of root, branch, foliage and crown. The precision of each biomass equation in the additive system varied from 77.0% to 99.7% with a mean value of 92.3% that would be suitable for predicting the biomass of the four natural conifer species.