三个主要树种单木生物量及其器官分配模型

doi:10.31497/zrzyxb.20170684

自然资源学报 ›› 2018, Vol. 33 ›› Issue (8): 1390-1402.doi: 10.31497/zrzyxb.20170684

三个主要树种单木生物量及其器官分配模型

王冬至^1a,2, 张冬燕^1a,1b, 蒋凤玲^1a, 许中旗^1a, 张志东^1a,2, 黄选瑞^1a,2,*

1. 河北农业大学a. 林学院,b. 商学院,河北保定 071000;
2. 河北省林木种植资源创新与保护实验室,河北保定 071000

收稿日期:2017-07-10 修回日期:2017-09-25 出版日期:2018-08-20 发布日期:2018-08-20
通讯作者: 黄选瑞（1962- ）,男,博士,教授,研究方向为森林资源可持续经营与管理。E-mail: hxr1962@163.com
作者简介:王冬至（1984- ）,男,河北景县人,博士,讲师,研究方向为森林资源可持续经营与管理。E-mail: wangdz@126.com
基金资助:
国家重点研发计划（2017YFD0600403）;林业公益性行业科研专项（20150430304）;河北省教育厅资助科研项目（QN2018125）;国家科技支撑项目（2015BAD09B01）;国家重点研发计划（2016YFD060020303）

Models for Estimating Biomass and Its Distribution in Organs of Three Main Tree Species

WANG Dong-zhi^1a,2, ZHANG Dong-yan^1a,1b, JIANG Feng-ling^1a, XU Zhong-qi^1a, ZHANG Zhi-dong^1a,2, HUANG Xuan-rui^1a,2

1. a. College of Forestry, b. College of Business. Agricultural University of Hebei, Baoding 071000, China;
2. Forest Resources Innovation and Protection Laboratory of Hebei, Baoding 071000, China

Received:2017-07-10 Revised:2017-09-25 Online:2018-08-20 Published:2018-08-20
Supported by:
National Key Research and Development Plan, No. 2017YFD0600403;Forestry Public Welfare Industry Research Project, No. 20150430304;Hebei Education Department Funding Research Project, No. QN2018125;Science and Technology Support Project of China, No. 2015BAD09B01;National Key Research and Development Plan, No. 2016YFD060020303

摘要/Abstract

摘要： 目前已有不同方法构建生物量相容性模型,但基于非线性似乎不相关回归估计法实现不同树种生物量模型相容性及各器官生物量分配模型的研究较少。因此,论文以塞罕坝华北落叶松、油松、白桦3种林分为对象,基于非线性似乎不相关回归估计法和广义多项Logit模型,建立了包含哑变量的非线性可加生物量模型及各器官生物量分配模型。结果表明：不同树种树干生物量模型确定系数均大于0.90,树枝、树叶、树根生物量模型确定系数在0.77~0.93范围内,各器官生物量均方根误差和绝对误差分别在2.68~17.19 kg/株和0.83~1.39 kg/株范围内,经过检验不同树种各器官生物量模型均能满足精度需求。不同树种广义多项Logit分配模型,通过似然比检验、比分检验和Wald检验均达到显著水平（P<0.001）,各器官参数均表现为显著水平（P<0.05）。不同树种树干、树枝、树叶及树根生物量比例分别在0.76~0.87、0.07~0.11、0.02~0.07、0.04~0.07范围内。包含哑变量的非线性似乎不相关生物量模型及广义多项Logit各器官分配模型,实现了生物量模型在不同树种间的通用性,并对森林生物量器官分配格局研究提供了科学参考。

关键词: 多项Logit模型, 林分类型, 生物量, 似乎不相关回归, 哑变量

Abstract: At present, there are different methods to construct compatible models of biomass. However, there are few reports on the compatibility of models for different tree species and the allocation model of component-specific biomass based on the nonlinear seemingly unrelated regression method. In this paper, the research objects were Larix principis-rupprechtii, Pinus tabuliformis and Betula platyphylla forests in Saihanba National Forest Farm, Hebei Province, China. Based on the nonlinear seemingly unrelated method and the generalized multinomial Logit model, the nonlinear additive models of biomass with dummy variables and allocation models of biomass in organs were established. The results showed that the discriminant coefficients (R²) of stem biomass models for different tree species were all higher than 0.90, and the root mean square errors (RMSE) and absolute errors were in the range of 16.68-17.19 and 0.84-1.07; in the biomass models of branch, leaf and root, the discriminant coefficients (R²) were in the range of 0.77-0.93, and the root mean square errors (RMSE) and absolute errors were in the range of 2.58-12.18 and 0.83-1.39. After inspection, the biomass models of different tree species can meet the precision requirement. The generalized multinomial Logit allocation models of different species all reached a significant level (P< 0.001) after Likelihood ratio test, Score test and Wald test. The parameters of each organ were significant (P < 0.05). The proportions of biomass in trunks, branches, leaves and roots of different tree species were in the range of 0.76-0.87, 0.07-0.11, 0.02-0.07 and 0.04-0.07, respectively. The models of nonlinear seemingly unrelated regression with dummy variables and the generalized multinomial Logit model of biomass allocation in organs can be used universally among different tree species and provide scientific basis for the study of forest biomass allocation pattern.

Key words: biomass, dummy variable, forest type, multinomial Logit model, seemingly unrelated regression

中图分类号:

S718.5

王冬至, 张冬燕, 蒋凤玲, 许中旗, 张志东, 黄选瑞. 三个主要树种单木生物量及其器官分配模型[J]. 自然资源学报, 2018, 33(8): 1390-1402.

WANG Dong-zhi, ZHANG Dong-yan, JIANG Feng-ling, XU Zhong-qi, ZHANG Zhi-dong, HUANG Xuan-rui. Models for Estimating Biomass and Its Distribution in Organs of Three Main Tree Species[J]. JOURNAL OF NATURAL RESOURCES, 2018, 33(8): 1390-1402.

参考文献

[1] PAN Y, BIRDSEY R A, PHILLIPS O L, et al.The structure, distribution, and biomass of the world’s forests[J]. Annual Review of Ecology, Evolution and Systematics, 2013, 44: 593-622.
[2] 陶冶, 张元明. 荒漠灌木生物量多尺度估测——以梭梭为例[J]. 草业学报, 2013, 22(6): 1-10.
[TAO Y, ZHANG Y M.Multi-scale biomass estimation of desert shrubs: A case study of Haloxylon ammodendron in the Gurbantunggut Desert, China. Acta Partaculturae Sinica, 2013, 22(6): 1-10. ]
[3] BROWM S L, SCHROEDER P, KEM J S.Spatial distribution of biomass in forests of the eastern USA[J]. Forest Ecology and Management, 1999, 123(1): 81-90.
[4] MOKANY K, RAISON R J, PROKUSHKIN A.Critical analysis of root: Shoot ratios in terrestrial biomes[J]. Global Change Biology, 2006, 12(1): 84-96.
[5] RIZVI R H, DHYANI S K, YADAV R S, et al.Biomass production and carbon stock of poplar agroforestry systems in Yamunanagar and Saharanpur districts of northwestern India[J]. Current Science, 2011, 100(5): 736-742.
[6] 符利勇, 雷渊才, 曾伟生. 几种相容性生物量模型及估计方法的比较[J]. 林业科学, 2014, 50(6): 42-54.
[FU L Y, LEI Y C, ZENG W S.Comparison of several compatible biomass models and estimation approaches. Scientia Silvae Sinicae, 2014, 50(6): 42-54. ]
[7] LI X, YI M J, SON Y, et al.Biomass and carbon storage in an age-sequence of Korean pine (Pinus koraiensis) plantation forests in central Korea[J]. Journal of Plant Biology, 2011, 54(1): 33-42.
[8] NVAR J.Biomass component equations for Latin American species and groups of species[J]. Annals of Forest Science, 2009, 66(2): 208-216.
[9] ZIANIS D, MUUKKONEN P, MAKIPAA R, et al.Biomass and stem volume equations for tree species in Europe[J]. Silva Fennica Monographs, 2005, 4: 1-63.
[10] 黄兴召, 陈东升, 孙晓梅, 等. 基于异速参数概率分布的立木地上生物量估算[J]. 林业科学, 2014, 50(6): 34-41.
[HUANG X S, CHEN D S, SUN X M, et al.Estimation of above-ground tree biomass based on probability distribution of allometric parameters. Scientia Silvae Sinicae, 2014, 50(6): 34-41. ]
[11] 罗永开, 方精云, 胡会峰. 山西芦芽山14种常见灌木生物量模型及生物量分配[J]. 植物生态学报, 2017, 41(1): 115-125.
[LUO Y K, FANG J Y, HU H F.Biomass estimation models and allocation patterns of 14 shrub species in Mountain Luya, Shanxi, China. Chinese Journal of Plant Ecology, 2017, 41(1): 115-125. ]
[12] POUDEL K P, TEMESGEN H.Methods for estimating aboveground biomass and its components for Douglas-fir and Lodgepole pine trees[J]. Canadian Journal of Forest Research, 2016, 46: 77-87.
[13] 汪珍川, 杜虎, 宋同清, 等. 广西主要树种(组)异速生长模型及森林生物量特征[J]. 生态学报, 2015, 35(13): 4462-4472.
[WANG Z C, DU H, SONG T Q, et al.Allometric models of major tree species and forest biomass in Guangxi. Acta Ecologica Sinica, 2015, 35(13): 4462-4472. ]
[14] 付甜, 朱建华, 肖文发, 等. 八种亚热带森林类型乔木层地上生物量分配模型[J]. 林业科学, 2014, 50(9): 1-9.
[FU T, ZHU J H, XIAO W F, et al.Above-ground biomass distribution models for arbor layer of eight subtropical forest types. Scientia Silvae Sinicae, 2014, 50(9): 1-9. ]
[15] ZHAO D H, KANE M, MARKEWITZ D, et al.Additive tree biomass equations for midrotation Loblolly pine plantations[J]. Forest Science, 2015, 61(4): 613-623.
[16] 李海奎, 赵鹏祥, 雷渊才, 等. 基于森林清查资料的乔木林生物量估算方法的比较[J]. 林业科学, 2012, 48(5): 44-52.
[LI H K, ZHAO P X, LEI Y C, et al.Comparison on estimation of wood biomass using forest inventory data. Scientia Silvae Sinicae, 2012, 48(5): 44-52. ]
[17] 李巍, 王传宽, 张全智. 林木分化对兴安落叶松异速生长方程和生物量分配的影响[J]. 生态学报, 2015, 35(6): 1679-1687.
[LI W, WANG C K, ZHANG Q Z.Differentiation of stand individuals impacts allometry and biomass allocation of Larix gmelinii trees. Acta Ecologica Sinica, 2015, 35(6): 1679-1687. ]
[18] PARRESOL B R.Additivity of nonlinear biomass equations[J]. Canadian Journal of Forest Research, 2001, 31(5): 865-878.
[19] 董利虎, 李凤日. 大兴安岭东部天然落叶松林可加性林分生物量估算模型[J]. 林业科学, 2016, 52(7): 13-21.
[DONG L H, LI F R.Additive stand-level biomass models for natural larch forest in the east of Daxing’an Mountains. Scientia Silvae Sinicae, 2016, 52(7): 13-21. ]
[20] 董利虎, 李凤日. 三种林分生物量估算方法的比较[J]. 应用生态学报, 2016, 27(12): 3862-3870.
[DONG L H, LI F R.Comparison of three stand-level biomass estimation methods. Chinese Journal of Applied Ecology, 2016, 27(12): 3862-3870. ]
[21] 董利虎, 张连军, 李凤日. 立木生物量模型的误差结构和可加性[J]. 林业科学, 2015, 51(2): 28-36.
[DONG L H, ZHANG L J, LI F R.Error structure and additivity of individual tree biomass model. Scientia Silvae Sinicae, 2015, 51(2): 28-36. ]
[22] BI H, TURNER J, LAMBERT M J.Additive biomass equations for native eucalypt forest trees of temperate Australia[J]. Trees, 2004, 18(4): 467-479.
[23] 肖生苓, 杨嘉龙. 大兴安岭北部兴安落叶松天然林单木地上生物量[J]. 林业科学, 2014, 50(8): 22-29.
[XIAO S L, YANG J L.Individual tree aboveground biomass of Larix gmelinii natural forest in the northern Greater Khingan Mountains. Scientia Silvae Sinicae, 2014, 50(8): 22-29. ]
[24] 曾鸣, 聂祥永, 曾伟生. 中国杉木相容性立木材积和地上生物量方程[J]. 林业科学, 2013, 49(10): 74-79.
[ZENG M, NIE X Y, ZENG W S.Compatible tree volume and aboveground biomass equations of Chinese fir in China. Scientia Silvae Sinicae, 2013, 49(10): 74-79. ]
[25] 符利勇, 唐守正, 张会儒, 等. 东北地区两个主要树种地上生物量通用方程构建[J]. 生态学报, 2015, 35(1): 150-157.
[FU L Y, TANG S Z, ZHANG H R, et al.Generalized above-ground biomass equations for two main species in Northeast China. Acta Ecologica Sinica, 2015, 35(1): 150-157. ]
[26] 曾伟生, 唐守正, 夏忠胜, 等. 利用线性混合模型和哑变量模型方法建立贵州省通用性生物量方程[J]. 林业科学研究, 2011, 24(3): 285-291.
[ZENG W S, TANG S Z, XIA Z S, et al.Using linear mixed model and dummy variable model approaches to construct generalized single-tree biomass equations in Guizhou. Forest Research, 2011, 24(3): 285-291. ]
[27] 王冬至, 张冬燕, 张志东, 等. 塞罕坝华北落叶松人工林断面积预测模型[J]. 北京林业大学学报, 2017, 39(7): 30-36.
[WANG D Z, ZHANG D Y, ZHANG Z D, et al.Prediction model for basal area of Larix principis-rupprechtii plantation in Saihanba of Hebei Province,northern China. Journal of Beijing Forestry University, 2016, 52(1): 30-36. ]
[28] SUZANNE M S, RUTISHAUSER E, CHAVE J, et al.Estimating the aboveground biomass in an old secondary forest on limestone in the Moluccas, indonesia: Comparing locally developed versus existing allometric models[J]. Forest Ecology and Management, 2017, 389: 27-34.
[29] KORHONEN L, KORHONEN K T, STENBERG P, et al.Local models for forest canopy cover with beta regression[J]. Silva Fennica, 2007, 41(4): 671-685.
[30] ESKELSON B N, MADSEN L, HAGAR J C, et al.Estimating riparian understory vegetation cover with beta regression and copula models[J]. Forest Science, 2011, 57: 212-221.
[31] WANG T H, ZHOU D W, WANG P, et al.Size-dependent reproductive effort in amaranthus retroflexus: The influence of planting density and sowing data[J]. Canadian journal of botany, 2006, 84(3): 485-492.
[32] 董利虎, 李凤日, 宋玉文. 东北林区4 个天然针叶树种单木生物量模型误差结构及可加性模型[J]. 应用生态学报, 2015, 26(3): 704-714.
[DONG L H, LI F R, SONG Y W.Error structure and additivity of individual tree biomass model for four natural conifer species in Northeast China. Chinese Journal of Applied Ecology, 2015, 26(3): 704-714. ]
[33] 巨文珍, 王新杰, 孙玉军. 长白落叶松林龄序列上的生物量及碳储量分配规律[J]. 生态学报, 2011, 31(4): 1139-1148.
[JU W Z, WANG X J, SUN Y J.Age structure effects on stand biomass and carbon storage distribution of Larix olgensis plantation. Acta Ecologica Sinica, 2011, 31(4): 1139-1148. ]
[34] 黄从德, 张健, 杨万勤, 等. 四川省及重庆地区森林植被碳储量动态[J]. 生态学报, 2008, 28(3): 966-975.
[HUANG C D, ZHANG J, YANG W Q, et al.Dynamics on forest carbon stock in Sichuan Province and Chongqing City. Acta Ecologica Sinica, 2008, 28(3): 966-975. ]
[35] POORTER H, NIKLAS K J, REICH P B, et al.Biomass allocation to leaves, stems and roots: Meta-analyses of interspecific variation and environmental control[J]. The New Phytologist, 2012, 193(1): 30-50.
[36] 王平, 王天慧, 周道玮, 等. 植物地上竞争与地下竞争研究进展[J]. 生态学报, 2007, 27(8): 3489-3499.
[WANG P, WANG T H, ZHOU D J, et al.A literature review on the above-and below-ground competition. Acta Ecologica Sinica, 2007, 27(8): 3489-3499. ]
[37] 黎磊, 周道玮, 盛连喜. 植物种群自疏过程中构件生物量与密度的关系[J]. 生态学报, 2012, 32(13): 3987-3997.
[LI L, ZHOU D W, SHENG L X.Allometric relationship between mean component biomass and density during the course of self-thinning for fagopyrum esculentum populations. Acta Ecologica Sinica, 2012, 32(13): 3987-3997. ]
[38] SHIPLEY B, MEZIANE D.The balanced-growth hypothesis and the allometry of leaf and root biomass allocation[J]. Functional Ecology, 2002, 16(3): 326-331.
[39] OSONE Y, TATENO M.Applicability and limitations of optimal biomass allocation models: A test of two species from fertile and infertile habitats[J]. Annals of Botany, 2005, 95(7): 1211-1220.
[40] 仇瑶,常顺利, 张毓涛, 等. 天山林区六种灌木生物量的建模及其器官分配的适应性[J].生态学报, 2015, 35(23): 7842-7851.
[QIU Y, CHANG S L, ZHANG Y T, et al.Biomass estimation modeling and adaptability analysis of organ allocation in six common shrub species in Tianshan Mountains forests, China. Acta Ecologica Sinica, 2015, 35(23): 7842-7851. ]
[41] 朱桂丽, 李杰, 魏学红, 等. 青藏高寒草地植被生产力与生物多样性的经度格局[J]. 自然资源学报, 2017, 32(2): 210-222.
[ZHU G L, LI J, WEI X H, et al.Longitudinal patterns of productivity and plant diversity in Tibetan alpine grasslands. Journal of Natural Resources, 2017, 32(2): 210-222. ]
[42] 安慧, 上官周平. 密度对刺槐幼苗生物量及异速生长模式的影响[J]. 林业科学, 2008, 44(3): 151-155.
[AN H, SHANGGUAN Z P.Effects of density on biomass and allometric pattern of Robinia pseudoacacia seedling. Scientia Silvae Sinicae, 2008, 44(3): 151-155. ]
[43] 黄迎新, 赵学勇, 张洪轩, 等. 沙米表型可塑性对土壤养分、水分和种群密度变化的响应[J]. 应用生态学报, 2008, 19(12): 2593-2598.
[HUANG Y X, ZHAO X Y, ZHANG H X, et al.Responses of agriophyllum squarrosum phenotypic plasticity to the changes of soil nutrient and moisture content sand population density. Chinese Journal of Applied Ecology, 2008, 19(12): 2593-2598. ]

三个主要树种单木生物量及其器官分配模型

Models for Estimating Biomass and Its Distribution in Organs of Three Main Tree Species

RichHTML

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	戴尔阜, 汪晓帆, 朱建佳, 王晓莉. 采伐与人工更新对红壤丘陵区森林面积和地上生物量的影响模拟——以会同县磨哨林场为例[J]. 自然资源学报, 2020, 35(12): 2995-3006.
[2]	饶滴滴, 于秀波, 李鹏, 夏少霞, 孟竹剑, 刘影. 鄱阳湖碟形湖泊（常湖池）春季苔草生物量遥感估算[J]. 自然资源学报, 2019, 34(9): 2001-2011.
[3]	张蕊, 李飞, 王媛, 马丽娜, 桑潮, 王力, 郭瑞英, 赵学勇, 尚占环. 三江源区退化天然草地和人工草地生物量碳密度特征[J]. 自然资源学报, 2018, 33(2): 185-194.
[4]	徐伟义, 金晓斌, 杨绪红, 王志强, 刘晶, 王丹, 单薇, 周寅康. 中国森林植被生物量空间网格化估计[J]. 自然资源学报, 2018, 33(10): 1725-1741.
[5]	张福平, 王虎威, 朱艺文, 张枝枝, 李肖娟. 祁连县天然草地地上生物量及草畜平衡研究[J]. 自然资源学报, 2017, 32(7): 1183-1192.
[6]	朱桂丽, 李杰, 魏学红, 何念鹏. 青藏高寒草地植被生产力与生物多样性的经度格局[J]. 自然资源学报, 2017, 32(2): 210-222.
[7]	郑拴丽, 许文强, 杨辽, 高亚琪, 李建军, 王蕾. 新疆阿尔泰山森林生态系统碳密度与碳储量估算[J]. 自然资源学报, 2016, 31(9): 1553-1563.
[8]	金远亮, 王忠, 张林. 西藏当雄县高寒草地NDVI的海拔分异特征及其指示[J]. 自然资源学报, 2015, 30(6): 928-937.
[9]	欧江, 张捷, 崔宁洁, 陈亚梅, 张健, 杨万勤, 刘洋. 采伐林窗对马尾松人工林土壤微生物生物量的初期影响[J]. 自然资源学报, 2014, 29(12): 2036-2047.
[10]	周义贵, 郝凯婕, 李贤伟, 范川, 陈栎霖, 王谢, 王晓红. 川西亚高山不同土地利用类型对土壤微生物量碳动态特征的影响[J]. 自然资源学报, 2014, 29(11): 1944-1956.
[11]	谭清梅, 刘红玉, 张华兵, 王聪, 侯明行. 盐城海滨湿地植被地上生物量遥感估算研究[J]. 自然资源学报, 2013, 28(12): 2044-2055.
[12]	章文龙, 曾从盛, 仝川, 王维奇, 林贤彪, 张子川. 闽江口沼泽植被地上鲜生物量与植株密度高光谱遥感估算[J]. 自然资源学报, 2013, 28(12): 2056-2067.
[13]	除多, 德吉央宗, 普布次仁, 姬秋梅, 唐红. 藏北草地地上生物量及遥感监测模型研究[J]. 自然资源学报, 2013, 28(11): 2000-2011.
[14]	高丽倩, 赵允格, 秦宁强, 张国秀, 杨凯. 黄土丘陵区生物结皮对土壤物理属性的影响[J]. 自然资源学报, 2012, 27(8): 1316-1326.
[15]	贾彦龙, 许中旗, 纪晓林, 徐学华, 黄选瑞. 燕山北部山地人工林和天然次生林的生物碳贮量[J]. 自然资源学报, 2012, (7): 1241-1251.