Establishment of Individual Biomass Equations for Caragana korshinskiiand Armeniaca sibirica in Inner Mongolia

ZENG Wei-Sheng; BAI Jin-xian; SONG Lian-cheng; ZHAO Xue-jun; WANG Xue-jun; XING Li-jun; ZHANG Zhen-rong

Volume 28 Issue 3

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Establishment of Individual Biomass Equations for Caragana korshinskiiand Armeniaca sibirica in Inner Mongolia

1.
Academy of Forest Inventory and Planning, State Forestry Administration, Beijing 100714, China
2.
Forestry Department of Inner Mongolia, Hohhot 010010, Inner Mongolia, China
3.
Second Institute of Forest Monitoring and Planning of Inner Mongolia, Ulanhot 137400, Inner Mongolia, China
4.
Forest Monitoring and Planning Institute of Inner Mongolia, Hohhot 010020, Inner Mongolia, China
5.
Hohhot Office of Forest Resource Supervision of Forestry Department of Inner Mongolia, Hohhot 010010, Inner Mongolia, China

Received Date: 2014-08-28

Abstract

Objective Aiming at the incompatibility of shrub biomass models between total biomass and components, or above- and below-ground biomass, the authors attempted to develop compatible shrub biomass models using the approach of simultaneous equations. Method Based on the individual biomass mensuration data of two common shrub species, Caragana korshinskii and Armeniaca sibirica, in the Inner Mongolia in China, the approach of nonlinear error-in-variable simultaneous equations was used to establish compatible above- and below-ground biomass models and root-to-shoot ratio model. Result The results are as follows: 1.The determination coefficients of above-ground biomass models based on canopy area and amount of stem (or mean height of stem) were higher than 0.67, but those of below-ground biomass models were relatively lower, and that for A. sibirica was only 0.36. 2.The mean prediction precisions of above- and below-ground biomass models for the two species were above 80%, and that of whole biomass model for A. sibirica was above 86% while that for C. korshinskii was above 92%. Conclusion It could be concluded that for tufty shrub species without obvious trunk, the canopy area was the most important factor related to shrub biomass, whether above- or below-ground biomass modeling, and the next was the amount or mean height of stems; the effective approach to solve the problem of incompatibility among different biomass was using nonlinear error-in-variable simultaneous equations to develop compatible above- and below-ground biomass models and root-to-shoot ratio model; and the biomass models developed here could be applied in shrub biomass estimation for the two species in the Inner Mongolia.
- above-ground biomass,
- below-ground biomass,
- root-to-shoot ratio,
- compatibility,
- prediction precision,
- Caragana korshinskii,
- Armeniaca sibirica

References

[1]	国家林业局. 中国森林资源报告(2009-2013)[M]. 北京:中国林业出版社, 2014.
[2]	Whittaker R H. Estimation of net primary production of forest and shrub communities[J]. Ecology, 1961, 42: 177-180.
[3]	Whittaker R H. Net production relations of shrubs in the Great Smoky Mountains[J]. Ecology, 1962, 43: 357-377.
[4]	姜凤歧, 卢风勇. 小叶锦鸡儿灌丛地上生物量的预测模型[J]. 生态学报, 1982, 2(2): 103-110.
[5]	Singh A, Madan M, Vasudevan P. Estimation of the aerial biomass of weedy shrubs by regression methods: studies on Adhatoda vasica[J]. Forest Ecology and Management, 1990, 32(2-4):167-172.
[6]	于九如, 韦少敏, 朱灵益, 等. 4种灌木树种生物量的估测[J]. 林业科技通讯, 1993(10): 11-12.
[7]	Haase P, Haase R. Aboveground biomass estimates for invasive trees and shrubs in the Pantanal of Mato Grosso, Brazil[J]. Forest Ecology and Management, 1995, 73(1-3):29-35.
[8]	何方, 王义强, 吕芳德, 等. 油茶林生物量与养分生物循环的研究[J]. 林业科学, 1996, 32(5): 403-410.
[9]	李钢铁, 秦富仓, 贾守义, 等. 旱生灌木生物量预测模型的研究[J]. 内蒙古林学院学报:自然科学版, 1998(2):24-31.
[10]	Rosenschein A, Tietema T, Hall D O. Biomass measurement and monitoring of trees and shrubs in a semi-arid region of central Kenya[J]. Journal of Arid Environments, 1999, 42(2):97-116.
[11]	陈遐林, 马钦彦, 康峰峰, 等. 山西太岳山典型灌木林生物量及生产力研究[J]. 林业科学研究, 2002, 15(3):304-309.
[12]	Návar J, Méndez E, Nájera A, et al. Biomass equations for shrub species of Tamaulipan thornscrub of North-eastern Mexico[J]. Journal of Arid Environments, 2004, 59(4): 657-674.
[13]	王蕾, 张宏, 哈斯, 等. 基于冠幅直径和植株高度的灌木地上生物量估侧方法研究[J]. 北京师范大学学报:自然科学版, 2004, 40(5): 700-704.
[14]	Foroughbakhch R, Reyes G, Alvarado-Vázquez M A, et al. Use of quantitative methods to determine leaf biomass on 15 woody shrub species in northeastern Mexico[J]. Forest Ecology and Management, 2005, 216:359-366.
[15]	蔡哲, 刘琪璟, 欧阳球林. 千烟洲试验区几种灌木生物量估测模型的研究[J]. 中南林学院学报, 2006, 26(3):15-18.
[16]	曾慧卿, 刘琪璟, 冯宗炜, 等. 红壤丘陵区林下灌木生物量估算模型的建立及其应用[J]. 应用生态学报, 2007, 18(10):2185-2190.
[17]	Castro H, Freitas H. Aboveground biomass and productivity in the Montado: from herbaceous to shrub dominated communities[J]. Journal of Arid Environments, 2009, 73(4-5): 506-511.
[18]	Lufafa A, Diédhiou I, Ndiaye N A S, et al. Allometric relationships and peak-season community biomass stocks of native shrubs in Senegal's Peanut Basin[J]. Journal of Arid Environments, 2009, 73(3): 260-266.
[19]	林伟, 李俊生, 郑博福, 等. 井冈山自然保护区12种常见灌木生物量的估测模型[J]. 武汉植物学研究, 2010, 28(6):725-729.
[20]	黄劲松, 邸雪颖. 帽儿山地区6种灌木地上生物量估算模型[J]. 东北林业大学学报, 2011, 39(5): 54-57.
[21]	何列艳, 亢新刚, 范小莉, 等. 长白山区临夏主要灌木生物量估算与分析[J]. 南京林业大学学报:自然科学版, 2011, 35(5):45-50.
[22]	Estornell J, Ruiz L A, Velázquez-Martí B, et al. Estimation of shrub biomass by airborne LiDAR data in small forest stands[J]. Forest Ecology and Management, 2011, 262(9):1697-1703.
[23]	Estornell J, Ruiz L A, Velázquez-Martí B, et al. Estimation of biomass and volume of shrub vegetation using LiDAR and spectral data in a Mediterranean environment[J]. Biomass and Bioenergy, 2012, 46:710-721.
[24]	赵蓓, 郭泉水, 牛树奎, 等. 大岗山灌木生物量模型研究[J]. 东北林业大学学报, 2012, 40(9): 28-33.
[25]	Giday K, Eshete G, Barklund P, et al. Wood biomass functions for Acacia abyssinica trees and shrubs and implications for provision of ecosystem services in a community managed exclosure in Tigray, Ethiopia[J]. Journal of Arid Environments, 2013, 94: 83-86.
[26]	陈富强, 罗勇, 李清湖. 粤东地区森林灌木层优势植物生物量估算模型[J]. 中南林业科技大学学报, 2013, 33(2):5-11.
[27]	杨昊天, 李新荣, 王增如, 等. 腾格里沙漠东南缘4种灌木的生物量预测模型[J]. 中国沙漠, 2013, 33(6): 1699-1704.
[28]	曾伟生. 国内外灌木生物量模型研究综述[J]. 世界林业研究, 2015, 28(1): 31-36.
[29]	唐守正, 郎奎建, 李海奎. 统计和生物数学模型计算(ForStat教程) [M]. 北京:科学出版社, 2008.
[30]	Zeng W S, Tang S Z. Modeling compatible single-tree aboveground biomass equations of Masson pine (Pinus massoniana) in southern China[J]. Journal of Forestry Research, 2012, 23(4): 593-598. doi: 10.1007/s11676-012-0299-4.
[31]	曾伟生, 唐守正. 非线性模型对数回归的偏差校正及与加权回归的对比分析[J]. 林业科学研究, 2011, 24(2): 137-143.
[32]	曾伟生, 唐守正. 立木生物量模型的优度评价和精度分析[J]. 林业科学, 2011, 47(11): 106-113.

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通讯作者: 陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

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Establishment of Individual Biomass Equations for Caragana korshinskiiand Armeniaca sibirica in Inner Mongolia

1. Academy of Forest Inventory and Planning, State Forestry Administration, Beijing 100714, China

2. Forestry Department of Inner Mongolia, Hohhot 010010, Inner Mongolia, China

3. Second Institute of Forest Monitoring and Planning of Inner Mongolia, Ulanhot 137400, Inner Mongolia, China

4. Forest Monitoring and Planning Institute of Inner Mongolia, Hohhot 010020, Inner Mongolia, China

5. Hohhot Office of Forest Resource Supervision of Forestry Department of Inner Mongolia, Hohhot 010010, Inner Mongolia, China

Received Date: 2014-08-28

Abstract: Objective Aiming at the incompatibility of shrub biomass models between total biomass and components, or above- and below-ground biomass, the authors attempted to develop compatible shrub biomass models using the approach of simultaneous equations. Method Based on the individual biomass mensuration data of two common shrub species, Caragana korshinskii and Armeniaca sibirica, in the Inner Mongolia in China, the approach of nonlinear error-in-variable simultaneous equations was used to establish compatible above- and below-ground biomass models and root-to-shoot ratio model. Result The results are as follows: 1.The determination coefficients of above-ground biomass models based on canopy area and amount of stem (or mean height of stem) were higher than 0.67, but those of below-ground biomass models were relatively lower, and that for A. sibirica was only 0.36. 2.The mean prediction precisions of above- and below-ground biomass models for the two species were above 80%, and that of whole biomass model for A. sibirica was above 86% while that for C. korshinskii was above 92%. Conclusion It could be concluded that for tufty shrub species without obvious trunk, the canopy area was the most important factor related to shrub biomass, whether above- or below-ground biomass modeling, and the next was the amount or mean height of stems; the effective approach to solve the problem of incompatibility among different biomass was using nonlinear error-in-variable simultaneous equations to develop compatible above- and below-ground biomass models and root-to-shoot ratio model; and the biomass models developed here could be applied in shrub biomass estimation for the two species in the Inner Mongolia.

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Reference (32)

[1]	国家林业局. 中国森林资源报告(2009-2013)[M]. 北京:中国林业出版社, 2014.
[2]	Whittaker R H. Estimation of net primary production of forest and shrub communities[J]. Ecology, 1961, 42: 177-180.
[3]	Whittaker R H. Net production relations of shrubs in the Great Smoky Mountains[J]. Ecology, 1962, 43: 357-377.
[4]	姜凤歧, 卢风勇. 小叶锦鸡儿灌丛地上生物量的预测模型[J]. 生态学报, 1982, 2(2): 103-110.
[5]	Singh A, Madan M, Vasudevan P. Estimation of the aerial biomass of weedy shrubs by regression methods: studies on Adhatoda vasica[J]. Forest Ecology and Management, 1990, 32(2-4):167-172.
[6]	于九如, 韦少敏, 朱灵益, 等. 4种灌木树种生物量的估测[J]. 林业科技通讯, 1993(10): 11-12.
[7]	Haase P, Haase R. Aboveground biomass estimates for invasive trees and shrubs in the Pantanal of Mato Grosso, Brazil[J]. Forest Ecology and Management, 1995, 73(1-3):29-35.
[8]	何方, 王义强, 吕芳德, 等. 油茶林生物量与养分生物循环的研究[J]. 林业科学, 1996, 32(5): 403-410.
[9]	李钢铁, 秦富仓, 贾守义, 等. 旱生灌木生物量预测模型的研究[J]. 内蒙古林学院学报:自然科学版, 1998(2):24-31.
[10]	Rosenschein A, Tietema T, Hall D O. Biomass measurement and monitoring of trees and shrubs in a semi-arid region of central Kenya[J]. Journal of Arid Environments, 1999, 42(2):97-116.
[11]	陈遐林, 马钦彦, 康峰峰, 等. 山西太岳山典型灌木林生物量及生产力研究[J]. 林业科学研究, 2002, 15(3):304-309.
[12]	Návar J, Méndez E, Nájera A, et al. Biomass equations for shrub species of Tamaulipan thornscrub of North-eastern Mexico[J]. Journal of Arid Environments, 2004, 59(4): 657-674.
[13]	王蕾, 张宏, 哈斯, 等. 基于冠幅直径和植株高度的灌木地上生物量估侧方法研究[J]. 北京师范大学学报:自然科学版, 2004, 40(5): 700-704.
[14]	Foroughbakhch R, Reyes G, Alvarado-Vázquez M A, et al. Use of quantitative methods to determine leaf biomass on 15 woody shrub species in northeastern Mexico[J]. Forest Ecology and Management, 2005, 216:359-366.
[15]	蔡哲, 刘琪璟, 欧阳球林. 千烟洲试验区几种灌木生物量估测模型的研究[J]. 中南林学院学报, 2006, 26(3):15-18.
[16]	曾慧卿, 刘琪璟, 冯宗炜, 等. 红壤丘陵区林下灌木生物量估算模型的建立及其应用[J]. 应用生态学报, 2007, 18(10):2185-2190.
[17]	Castro H, Freitas H. Aboveground biomass and productivity in the Montado: from herbaceous to shrub dominated communities[J]. Journal of Arid Environments, 2009, 73(4-5): 506-511.
[18]	Lufafa A, Diédhiou I, Ndiaye N A S, et al. Allometric relationships and peak-season community biomass stocks of native shrubs in Senegal's Peanut Basin[J]. Journal of Arid Environments, 2009, 73(3): 260-266.
[19]	林伟, 李俊生, 郑博福, 等. 井冈山自然保护区12种常见灌木生物量的估测模型[J]. 武汉植物学研究, 2010, 28(6):725-729.
[20]	黄劲松, 邸雪颖. 帽儿山地区6种灌木地上生物量估算模型[J]. 东北林业大学学报, 2011, 39(5): 54-57.
[21]	何列艳, 亢新刚, 范小莉, 等. 长白山区临夏主要灌木生物量估算与分析[J]. 南京林业大学学报:自然科学版, 2011, 35(5):45-50.
[22]	Estornell J, Ruiz L A, Velázquez-Martí B, et al. Estimation of shrub biomass by airborne LiDAR data in small forest stands[J]. Forest Ecology and Management, 2011, 262(9):1697-1703.
[23]	Estornell J, Ruiz L A, Velázquez-Martí B, et al. Estimation of biomass and volume of shrub vegetation using LiDAR and spectral data in a Mediterranean environment[J]. Biomass and Bioenergy, 2012, 46:710-721.
[24]	赵蓓, 郭泉水, 牛树奎, 等. 大岗山灌木生物量模型研究[J]. 东北林业大学学报, 2012, 40(9): 28-33.
[25]	Giday K, Eshete G, Barklund P, et al. Wood biomass functions for Acacia abyssinica trees and shrubs and implications for provision of ecosystem services in a community managed exclosure in Tigray, Ethiopia[J]. Journal of Arid Environments, 2013, 94: 83-86.
[26]	陈富强, 罗勇, 李清湖. 粤东地区森林灌木层优势植物生物量估算模型[J]. 中南林业科技大学学报, 2013, 33(2):5-11.
[27]	杨昊天, 李新荣, 王增如, 等. 腾格里沙漠东南缘4种灌木的生物量预测模型[J]. 中国沙漠, 2013, 33(6): 1699-1704.
[28]	曾伟生. 国内外灌木生物量模型研究综述[J]. 世界林业研究, 2015, 28(1): 31-36.
[29]	唐守正, 郎奎建, 李海奎. 统计和生物数学模型计算(ForStat教程) [M]. 北京:科学出版社, 2008.
[30]	Zeng W S, Tang S Z. Modeling compatible single-tree aboveground biomass equations of Masson pine (Pinus massoniana) in southern China[J]. Journal of Forestry Research, 2012, 23(4): 593-598. doi: 10.1007/s11676-012-0299-4.
[31]	曾伟生, 唐守正. 非线性模型对数回归的偏差校正及与加权回归的对比分析[J]. 林业科学研究, 2011, 24(2): 137-143.
[32]	曾伟生, 唐守正. 立木生物量模型的优度评价和精度分析[J]. 林业科学, 2011, 47(11): 106-113.

Establishment of Individual Biomass Equations for Caragana korshinskiiand Armeniaca sibirica in Inner Mongolia

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通讯作者: 陈斌, bchen63@163.com

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Establishment of Individual Biomass Equations for Caragana korshinskiiand Armeniaca sibirica in Inner Mongolia

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