林业科学2016，Vol.52Issue(7)：13-21,9.DOI:10.11707/j.1001-7488.20160702
大兴安岭东部天然落叶松林可加性林分生物量估算模型
Additive Stand-Level Biomass Models for Natural Larch Forest in the East of Daxing’an Mountains
摘要
Abstract
Objective]The traditional method based on forest inventory data plays an import role in assessment of forest biomass at regional scale and its dynamics and verification of the remote-sensing based model and improvement of its prediction precision. The forest biomass methods at regional scale have attracted most attention of researchers,developing the stand-level biomass model has become a new trend. Based on 1990—2010 forestry inventory data (the 5th inventory) of natural larch forest in the east of Daxing’an Mountains,we studied how to use two methods ( i. e. ,stand biomass models respectively based on stand variables and stand volume ) to establish the additive system of stand-level biomass equations,and analyzed their prediction precisions. These provided technical and theoretical support for accounting and monitoring the Chinese forest biomass and carbon stock.[Method]Structure of model errors ( additive vs. multiplicative) of total and component biomass allometric equations in two stand-level biomass of natural larch forest in the east of Daxing ’an Mountains were evaluated using the likelihood analysis,and aggregation system was used to establish the stand-level biomass additive models,while nonlinear seemly unrelated regression was used to estimate the parameters in the additive system of biomass equations. The stand-level biomass model validation was accomplished by Jackknifing technique in this study.[Result]The assumption of multiplicative error structure was strongly supported for total and tree components biomass equations in two stand-level biomass additive systems. Thus,the additive system of log-transformed biomass equations should be developed. The adjusted coefficient of determination ( R2a ) of two stand-level biomass additive systems for natural larch forest in the east of Daxing’an Mountains were above 0. 94,the mean relative error ( ME) was between 0% -5%,and the mean absolute relative error ( MAE) was less than 15%. All the precisions of total and tree components biomass equations in stand-level biomass additive system were above 98%.[Conclusion]Although the significance of likelihood analysis was used in individual tree biomass equations by several studies,it has not been widely applied in stand-level biomass equations. In addition,in order to estimate model parameters more effectively,the additivity of total and components biomass should be taken into account. Overall,there were differences between the two methods,but good precisions of the two methods were obtained. The two methods would be suitable for predicting the stand-level biomass of natural larch forest in the east of Daxing’an Mountains.关键词
天然落叶松林/林分生物量/误差结构/似然分析法/可加性模型Key words
natural larch forest/stand-level biomass/error structure/likelihood analyses/additive system分类
农业科技引用本文复制引用
董利虎,李凤日..大兴安岭东部天然落叶松林可加性林分生物量估算模型[J].林业科学,2016,52(7):13-21,9.基金项目
国家“十二五”科技支撑计划课题(2012BAD22B02) （2012BAD22B02）
中央高校基本科研业务费专项资金项目(2572015BX03) （2572015BX03）
黑龙江省留学归国人员科学基金项目(LC2016007)。 （LC2016007）
