亚热带常绿阔叶林幼树与灌木的地上生物量模型

周华; 孟盛旺; 刘琪璟

doi:10.3969/j.issn.1000-2006.201612051

周华,孟盛旺,刘琪璟

南京林业大学学报（自然科学版） ›› 2017, Vol. 41 ›› Issue (06) : 79-86.

PDF(2394767 KB)

国家林草科技领军期刊
中国精品科技期刊
中国高校百佳科技期刊
江苏省新闻出版政府奖期刊奖
RCCSE林学权威期刊（A+）
CSCD核心期刊
Scopus数据库收录期刊
中文核心期刊
SCD核心期刊

作者加群：102861116

微信公众号：南京林业大学学报

高级检索

PDF(2394767 KB)

南京林业大学学报（自然科学版） ›› 2017, Vol. 41 ›› Issue (06) : 79-86. DOI: 10.3969/j.issn.1000-2006.201612051

研究论文

亚热带常绿阔叶林幼树与灌木的地上生物量模型

周华,孟盛旺,刘琪璟

作者信息 +

Allometric equations for estimating aboveground biomass of broad-leaved forests saplings and shrubs in subtropical China

ZHOU Hua, MENG Shengwang, LIU Qijing^*

Author information +

文章历史 +

摘要

【目的】准确估测亚热带常绿阔叶林木本植物幼苗、幼树及灌木的地上生物量,为森林生态系统的经营管理提供理论参考。【方法】通过采样准确获得九连山39种木本植物746个单株样本的地径(d)、树高(h)和木材基本密度(ρ),以及各器官(叶、枝、干)的地上生物量观测值,并按生活型将样本分为乔木组、小乔木组和灌木组3类,分别以d²、ρd²、d²h和ρd²h为自变量拟合模型,根据拟合模型的R²值和估计值的标准误(SEE)选择最优生物量模型。【结果】九连山常见木本植物的木材基本密度在0.459～0.784 g/cm³之间; 推导的64个生物量模型都具有较高的R²值和较低的SEE值,据此选择出16个最优生物量模型。其中,小乔木组和灌木组的叶片和枝条生物量在只含自变量d时具有较高的R²值,而乔木组和小乔木组树干以及总的地上生物量在含自变量d、h和ρ时具有较高的R²值和SEE值。【结论】研究拟合的模型可准确估算该地区及相似地区常见木本植物幼苗、幼树及灌木的地上生物量。

Abstract

【Objective】Accurately estimating the biomass of seedlings, saplings and shrubs is essential for forest ecosystem management.【Method】A total of 39 woody species with 746 individuals in the Jiulian Mountain Nature Reserve located in southeast China were destructively sampled. All species were categorized as high trees, small trees and shrubs, based on their life form. In addition to component-specific biomass, the ground diameter(d), stem height(h)and basic wood density(ρ)were measured, and regressive models were established with d², ρd², d²h and ρd²h as predicting variables, respectively. Optimum models were chosen based on the determination coefficient R² and standard error of estimate.【Result】The basic wood densities of the sampled species were in the range of 0.459-0.784 g/cm³. Sixteen optimum models were chosen among 64 candidate models. For small trees and shrubs, equations for foliage and branches with a single predicting variable d, showed higher R² values, while the fitness of the stemand total-aboveground biomass was closer for equations with d, h, and ρ as the independent factors for small trees and shrubs than for the other category.【Conclusion】The models established in this study are expected to provide reliable accuracy for estimating the above ground biomass of understory woody species in the same vegetation zone.

引用本文

EndNote

Ris (Procite)

Bibtex

导出引用

周华,孟盛旺,刘琪璟. 亚热带常绿阔叶林幼树与灌木的地上生物量模型[J]. 南京林业大学学报（自然科学版）. 2017, 41(06): 79-86 https://doi.org/10.3969/j.issn.1000-2006.201612051

ZHOU Hua, MENG Shengwang, LIU Qijing. Allometric equations for estimating aboveground biomass of broad-leaved forests saplings and shrubs in subtropical China[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2017, 41(06): 79-86 https://doi.org/10.3969/j.issn.1000-2006.201612051

中图分类号： S718

参考文献

[1] RITTER T, SABOROWSKI J. Point transect sampling of deadwood: a comparison with well-established sampling techniques for the estimation of volume and carbon storage in managed forests[J]. European Journal of Forest Research, 2012, 131(6): 1845-1856. DOI: 10.1007/s10342-012-0637-2.
[2] SPECHT A, WEST P W. Estimation of biomass and sequestered carbon on farm forest plantations in northern New South Wales, Australia[J]. Biomass and Bioenergy, 2003, 25(4): 363-379. DOI: 10.1016/s0961-9534(03)00050-3.
[3] COLE T G, EWEL J J. Allometric equations for four valuable tropical tree species[J]. Forest Ecology and Management, 2006, 229(1): 351-360. DOI:10.1016/j.foreco.2006.04.017.
[4] CHAVE J, ANDALO C, BROWN S, et al. Tree allometry and improved estimation of carbon stocks and balance in tropical forests[J]. Oecologia, 2005, 145(1): 87-99. DOI: 10.1007/s00442-005-0100-x.
[5] CHAVE J, RÉJOU-MÉCHAIN M, BU^'RQUEZ A, et al. Improved allometric models to estimate the aboveground biomass of tropical trees[J]. Glob Chang Biol, 2014, 20(10): 3177-3190. DOI:10.1111/gcb.12629.
[6] WEST G B, BROWN J H, ENQUIST B J. A general model for the origin of allometric scaling laws in biology[J]. Science, 1997, 276(5309): 122-126. DOI:10.1126/science.276.5309.122.
[7] 何列艳, 亢新刚, 范小莉, 等. 长白山区林下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. DOI:10.3969/j.issn.1000-2006.2011.05.010. HE L Y, KANG X G, FAN X L, et al. Estimation and analysis of understory shrub biomass in Changbai Mountains[J]. Journal of Nanjing Forestry University(Natural Sciences Edition), 2011, 35(5): 45-50.
[8] 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. DOI:10.3724/SP.J.1142.2010.60725. LIN W, LI J S, ZHENG B F, et al. Models for estimating biomass of twelve shrub species in Jinggang Mountain Nature Reserve[J]. Journal of Wuhan Botanical Research, 2010, 28(6): 725-729.
[9] 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. DOI:10.13287/j.1001-9332.2007.0359 ZENG H Q, LIU Q J, FENG Z W, et al. Estimation models of understory shrub biomass and their applications in red soil hilly region[J]. Chinese Journal of Applied Ecology, 2007, 18(10): 2185-2190.
[10] 曾慧卿, 刘琪璟, 马泽清, 等. 基于冠幅及植株高度的檵木生物量回归模型[J]. 南京林业大学学报(自然科学版), 2006, 30(4): 101-104. DOI:10.3969/j.issn.1000-2006.2006.04.024. ZENG H Q, LIU Q J, MA Z Q, et al. The regression model of loropetalum Chinese biomass based on canopy diameter and plant height[J]. Journal of Nanjing Forestry University(Natural Sciences Edition), 2006, 30(4): 101-104.
[11] NELSON B W, MESQUITA R, PEREIRA J L G, et al. Allometric regressions for improved estimate of secondary forest biomass in the central Amazon[J]. Forest Ecology and Management, 1999, 117(1): 149-167. DOI: 10.1016/s0378-1127(98)00475-7.
[12] CHATURVEDI R K, RAGHUBANSHI A S. Aboveground biomass estimation of small diameter woody species of tropical dry forest[J]. New Forests, 2012, 44(4): 509-519. DOI: 10.1007/s11056-012-9359-z.
[13] HENRY M, BESNARD A, ASANTE W A, et al. Wood density, phytomass variations within and among trees, and allometric equations in a tropical rainforest of Africa[J]. Forest Ecology and Management, 2010, 260(8): 1375-1388. DOI:10.1016/j.foreco.2010.07.040.
[14] BROWN S L, SCHROEDER P E. Spatialpatterns of aboveground production and mortality of woody biomass for eastern US forest[J]. Ecological Applications, 1999, 9(3): 968. DOI: 10.2307/2641343.
[15] OLIVEIRA A A, MORI S A. A central Amazonian terra firme forest. I. high tree species richness on poor soils[J]. Biodiversity and Conservation, 1999(8): 1219-1244. DOI: 10.1023/A: 1008908615271
[16] BROWN S, GILLESPIE A J R, LUGO A E. Biomass estimation methods for tropical forests with applications to forest inventory data[J].Forest Science, 1989, 35(4):881-902. https://www.researchgate.net/publication/233643575_Biomass_Estimation_Methods_for_Tropical_Forests_with_Applications_to_Forest_Inventory_Data.
[17] SINGH V, TEWARI A, KUSHWAHA S P S, et al. Formulating allometric equations for estimating biomass and carbon stock in small diameter trees[J]. Forest Ecology and Management, 2011, 261(11): 1945-1949. DOI:10.1016/j.foreco.2011.02.019.
[18] BRANDEIS T J, DELANEY M, PARRESOL B R, et al. Development of equations for predicting Puerto Rican subtropical dry forest biomass and volume[J]. Forest Ecology and Management, 2006, 233(1): 133-142. DOI:10.1016/j.foreco.2006.06.012.
[19] 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): 5-10. DOI:10.14067/j.cnki.1673-923x.2013.02.010. CHEN F Q, LUO Y, LI Q H. Allometric equations for estimating biomass of dominant shrub species in subtropical forests in eastern Guangdong province, China[J]. Journal of Central South University of Forestry & Technology, 2013, 33(2): 5-10.
[20] CLARK D A, CLARK D B. Life history diversity of canopy and emergent trees in a neotropical rain forest[J]. Ecological Monographs, 1992, 62(3): 315-344. DOI: 10.2307/2937114.
[21] ZHOU X, BRANDEL J R, SCHOENEBERGER M M, et al. Developing above-ground woody biomass equations for open-grown, multiple-stemmed tree species: shelterbelt-grown Russian-olive[J]. Ecological Modelling, 2007, 202(3): 311-323.
[22] ARBAINSYAH, de IONGH H H, KUSTIAWAN W, et al. Structure, composition and diversity of plant communities in FSC-certified, selectively logged forests of different ages compared to primary rain forest[J]. Biodiversity and Conservation, 2014, 23(10):2445-2472. DOI: 10.1007/s10531-014-0732-4.
[23] PARRESOL B R. Assessing tree and stand biomass: a review with examples and critical comparisons[J]. Forest Science, 1999, 45(4):573-593.
[24] SUGIHARA G. Minimalcommunity structure: an explanation of species abundance patterns[J]. The American Naturalist, 1980, 116(6): 770-787. DOI: 10.1086/283669.
[25] PÉREZ CORDERO L D, KANNINEN M. Wood specific gravity and aboveground biomass of Bombacopsis quinata plantations in Costa Rica[J]. Forest Ecology and Management, 2002, 165(1): 1-9. DOI: 10.1016/s0378-1127(01)00627-2.
[26] MULLER-LANDAU H C. Interspecific andinter-site variation in wood specific gravity of tropical trees[J]. Biotropica, 2004, 36(1): 20-32. DOI:10.1111/j.1744-7429.2004.tb00292.x.
[27] NOGUEIRA E M, FEARNSIDE P M, NELSON B W, et al. Wood density in forests of Brazil's ‘arc of deforestation': implications for biomass and flux of carbon from land-use change in Amazonia[J]. Forest Ecology and Management, 2007, 248(3): 119-135. DOI:10.1016/j.foreco.2007.04.047.
[28] MARTINEZ-YRIZAR A, SARUKHAN J, PEREZ-JIMENEZ A, et al. Above-ground phytomass of a tropical deciduous forest on the coast of Jalisco, México[J]. Journal of Tropical Ecology, 1992, 8(1): 87-96. DOI: 10.1017/s0266467400006131.
[29] CHATURVEDI R K, RAGHUBANSHI A S. Assessment of carbon density and accumulation in mono-and multi-specific stands in teak and sal forests of a tropical dry region in India[J]. Forest Ecology and Management, 2015, 339: 11-21. DOI:10.1016/j.foreco.2014.12.002.
[30] CHATURVEDI R K, RAGHUBANSHI A S, SINGH J S. Carbon density and accumulation in woody species of tropical dry forest in India[J]. Forest Ecology and Management, 2011, 262(8): 1576-1588. DOI:10.1016/j.foreco.2011.07.006.
[31] CHATURVEDI R K, RAGHUBANSHI A S, SINGH J S. Plant functional traits with particular reference to tropical deciduous forests: a review[J]. Journal of Bioscience and Bioengineering, 2011, 36(5): 963-981. DOI: 10.1007/s12038-011-9159-1.
[32] SHINOZAKI K, YODA K, HOZUMI K, et al. A quantitative analysis of plant form:the pipe model theory. II. further evidence of the theory and its application in forest ecology[J]. Japanese Journal of Ecology, 1964(14): 133-139. DOI: 10.18960/seitai.14.4_133.
[33] 李根, 周光益, 王旭, 等. 南岭小坑藜蒴栲群落地上部分生物量分配规律[J]. 生态学报, 2011, 31(13): 3650-3658. LI G, ZHOU G Y, WANG X, et al. Aboveground biomass of natural Castanopsis fissa community at the Xiaokeng of Nanling Mountain, southern China[J]. Acta Ecologica Sinica, 2011, 31(13): 3650-3658.
[34] CHAVE J, CONDIT R, AGUILAR S, et al. Error propagation and scaling for tropical forest biomass estimates[J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2004(359): 409-420. DOI:10.1098/rstb.2003.1425.
[35] BASKERVILLE G L. Use of logarithmic regression in the estimation of plant biomass[J]. Canadian Journal of Forest Research, 1972(2): 49-53.

基金

基金项目:国家高技术研究发展计划(2013AA122003) 第一作者:周华(jeamourvous@163.com),博士生。*通信作者:刘琪璟(liuqijing@bjfu.edu.cn),教授。引文格式:周华,孟盛旺,刘琪璟. 亚热带常绿阔叶林幼树与灌木的地上生物量模型[J]. 南京林业大学学报(自然科学版),2017,41(6):79-86.