Additive Allometric Equations to Improve Aboveground Biomass Estimation for Mongolian Pine Plantations in Mu Us Sandy Land, Inner Mongolia, China
文献类型：期刊论文
| 作者 | Siqing, Bilige4,5; Meng, Shengwang3; Liu, Liping4; Zhou, Guang2; Yu, Jian1; Xu, Zhenzhao5; Liu, Qijing5 |
| 刊名 | FORESTS
 |
| 出版日期 | 2022-10-01 |
| 卷号 | 13期号:10页码:14 |
| 关键词 | biomass equations additivity allometry heteroscedasticity biomass allocation |
| DOI | 10.3390/f13101672 |
| 通讯作者 | Liu, Qijing(liuqijing@bjfu.edu.cn) |
| 英文摘要 | Afforestation is conducive to improving ecosystem service functions and ecosystem diversity in the Mu Us Sandy Land, however, the important attribute of biomass for Mongolian pine (Pinus sylvestris var. mongolica Litv.) plantations has yet to be accurately evaluated. This study aimed to develop additive allometric biomass equations for the species and evaluate biomass partitioning patterns within tree components. A total of 131 trees were measured for stem, branch, and leaf biomass by destructively sampling and tree climbing, with the latter as a supplement. For each biomass component, we tested three equations with the diameter at breast (D) alone, height (H) as additional, and diameter in combination with height ((DH)-H-2) as predictors using the weighted least squared method. Weighted nonlinear seemingly unrelated regression was adopted to fit a system of additive allometric biomass equations utilizing the selected equations. A leave-one-out cross-validation method (the jackknife procedure) was used to assess the predictive ability. The biomass partitioning pattern was evaluated by calculating the ratios. The results revealed that the diameter alone is a good predictor for branches and foliage biomass estimates, while the stem requires H included to improve estimation accuracy. Mongolian pine allocates relatively more biomass to the crown (51.4%) compared to the stem (48.6%). Branch biomass fraction increased monotonously with increasing tree size while a reverse trend was observed for foliage. In conclusion, the additive models developed in this study provide a robust biomass estimation and can be extensively used to estimate Mongolian pine forests biomass in Mu Us Sandy Land. |
| WOS关键词 | TREE BIOMASS ; CARBON STOCKS ; MODELS ; REGRESSION ; PATTERNS ; STAND |
| 资助项目 | National Key R&D Program of China[2020YFA0608102] ; National Key R&D Program of China[2017YFC0506503] |
| WOS研究方向 | Forestry |
| 语种 | 英语 |
| WOS记录号 | WOS:000875129800001 |
| 出版者 | MDPI |
| 资助机构 | National Key R&D Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/186199]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Liu, Qijing |
| 作者单位 | 1.Jiangsu Vocat Coll Agr & Forestry, Sch Landscape Architecture, Zhenjiang 212400, Jiangsu, Peoples R China 2.Jiangxi Acad Forestry, Nanchang 330013, Jiangxi, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Qianyanzhou Ecol Res Stn, Beijing 100101, Peoples R China 4.Ordos Forestry & Grassland Dev Ctr, Ordos 017000, Peoples R China 5.Beijing Forestry Univ, Coll Forestry, Beijing 100083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Siqing, Bilige,Meng, Shengwang,Liu, Liping,et al. Additive Allometric Equations to Improve Aboveground Biomass Estimation for Mongolian Pine Plantations in Mu Us Sandy Land, Inner Mongolia, China[J]. FORESTS,2022,13(10):14. |
| APA | Siqing, Bilige.,Meng, Shengwang.,Liu, Liping.,Zhou, Guang.,Yu, Jian.,...&Liu, Qijing.(2022).Additive Allometric Equations to Improve Aboveground Biomass Estimation for Mongolian Pine Plantations in Mu Us Sandy Land, Inner Mongolia, China.FORESTS,13(10),14. |
| MLA | Siqing, Bilige,et al."Additive Allometric Equations to Improve Aboveground Biomass Estimation for Mongolian Pine Plantations in Mu Us Sandy Land, Inner Mongolia, China".FORESTS 13.10(2022):14. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。