4.5 Article

Additive tree biomass equations for Betula platyphylla Suk. plantations in Northeast China

期刊

ANNALS OF FOREST SCIENCE
卷 75, 期 2, 页码 -

出版社

SPRINGER FRANCE
DOI: 10.1007/s13595-018-0738-2

关键词

Biomass additivity; Destructive sampling; White birch

类别

资金

  1. National Natural Science Foundation of China [31670476]
  2. Fundamental Research Funds for the Central Universities [2572016CA02]

向作者/读者索取更多资源

Key message A new system of additive tree biomass equations was developed for juvenile white birch plantations based on tree diameter at breast height (DBH) and tree height (HT). Compared with previous equations developed for natural white birch forests, the new system included one more biomass component and provided more accurate predictions. Context Accurate estimates of tree component and total biomass are necessary for evaluating alternative forest management strategies for biomass feedstock, carbon sequestration, and products. Previous biomass equations developed for white birch trees in natural stands provided substantially biased predictions for white birch plantations. Aims A new system of additive tree biomass equations was developed for juvenile white birch plantations in the northeastern China. Methods With destructive biomass sampling data from 501 trees sampled from white birch provenance and family trails at ages 7, 9, 10, and 13 in three provinces, a system of nonlinear additive tree biomass equations based on DBH and tree height was developed using the nonlinear seemingly unrelated regressions (NSUR) approach. Results Compared with previously published equations developed for natural white birch forests, the new system provided more accurate predictions of white birch tree component and aboveground and total biomass, especially of branch, foliage, and root biomass. Conclusion The new system extended the applicability of biomass equations to white birch plantations in the northeastern China.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据