globalchange  > 气候变化事实与影响
CSCD记录号: CSCD:6377808
论文题名:
基于不同预测变量的天然椴树可加性地上生物量模型构建
其他题名: Additive aboveground biomass equations based on different predictors for natural Tilia Linn
作者: 王佳慧; 李凤日; 董利虎
刊名: 应用生态学报
ISSN: 1001-9332
出版年: 2018
卷: 29, 期:11, 页码:721-733
语种: 中文
中文关键词: 生物量 ; 椴树 ; 可加性模型 ; 异速生长方程 ; 刀切法
英文关键词: biomass ; Tilia Linn. ; additive system ; allometric equation ; Jackknifing technique
WOS学科分类: FORESTRY
WOS研究方向: Forestry
中文摘要: 森林生物量是森林生态系统的最基本数量特征,生物量数据是研究许多林业问题和生态问题的基础,因此,准确测定生物量对于计算碳储量以及研究气候变化、森林健康、森林生产力、养分循环等十分重要.目前,测算森林生物量常用的方法为生物量模型估算法.本研究基于小兴安岭地区和张广才岭地区97株实测生物量数据,建立了3个天然椴树立木可加性生物量模型系统(基于胸径的一元可加性生物量模型系统、基于胸径和树高的二元可加性生物量模型系统、基于最优变量的最优可加性生物量模型系统),采用非线性似乎不相关回归法进行参数估计,用加权方法解决模型的异方差问题,并采用刀切法进行模型检验.结果表明: 3种可加性生物量模型系统均能较好地对椴树各部分生物量进行拟合和预测(调整后确定系数R_a~2>0.84,平均预测误差百分比MPE<8.5%,平均绝对误差MAE<16.3 kg,平均百分标准误差MPSE<28.5%),其中,树干和地上生物量的拟合效果优于树叶、树枝和树冠;在引入树高和树冠因子后,提高了模型的拟合效果和预测能力(R_a~2提高0.01 ~ 0.04,MAE降低0.01 ~ 4.55 kg),缩小了预测值置信区间的范围,树干、树叶和地上生物量提高较多,树枝和树冠提高较少.总体来看,最优生物量模型系统效果最好,其次为二元生物量模型系统,再次是一元生物量模型系统,添加树高和树冠因子进行生物量模型的构建十分必要.
英文摘要: Biomass is a basic quantitative character of forest ecosystem. Biomass data are foundation of researching many forestry and ecology problems. Accurate quantification of tree biomass is critical and essential for calculating carbon storage,as well as for studying climate change,forest health, forest productivity, nutrient cycling, etc. Constructing biomass models is considered a good approach to estimate forest biomass. Based on biomass data of 97 sampling trees of natural Tilia Linn. in Xiaoxing'an Mountains and Zhangguangcai ranges,three additive systems of individual tree biomass equations were developed: based on tree diameter at breast height ( D) only,based on tree diameter at breast height and height ( H),and based on the best models. The nonlinear seemly unrelated regression was used to estimate the parameters in the additive system of biomass equations. The heteroscedasticity in model residuals was addressed by applying a unique weight function to each equation. The individual tree biomass model validation was accomplished by Jackknifing technique. The results showed that three additive systems of individual tree biomass equations could fit and predict the biomass of Tilia Linn. well ( adjusted coefficient of determination R_a~2>0.84,mean predicted error percentage MPE<8.5%,mean absolute error MAE<16.3 kg,mean standard error percentage MPSE<28.5%). The biomass equations of stem and aboveground were better than biomass equations of branch,foliage and crown. Adding total tree height and crown factor in the additive systems of biomass equations could significantly improve model fitting performance and predicting precision ( R_a~2 improved from 0.01 to 0.04,MAE decreased from 0.01 to 4.55 kg),narrow the confidence interval of the predicted value and the biomass of stem,foliage and aboveground were increased more than the biomass of branch and crown. In general,the equations of the additive system based on the best models produced the best model fitting,followed by that of the additive system based on D and H,and that based on D. It was essential to develop biomass model by adding total tree height and crown factor.
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/155093
Appears in Collections:气候变化事实与影响

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作者单位: 东北林业大学林学院, 哈尔滨, 黑龙江 150040, 中国

Recommended Citation:
王佳慧,李凤日,董利虎. 基于不同预测变量的天然椴树可加性地上生物量模型构建[J]. 应用生态学报,2018-01-01,29(11):721-733
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