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思茅松天然林林分生物量混合效应模型构建

欧光龙 胥辉 王俊峰 肖义发 陈科屹 郑海妹

欧光龙, 胥辉, 王俊峰, 肖义发, 陈科屹, 郑海妹. 思茅松天然林林分生物量混合效应模型构建[J]. 北京林业大学学报, 2015, 37(3): 101-110. doi: 10.13332/j.1000-1522.20140316
引用本文: 欧光龙, 胥辉, 王俊峰, 肖义发, 陈科屹, 郑海妹. 思茅松天然林林分生物量混合效应模型构建[J]. 北京林业大学学报, 2015, 37(3): 101-110. doi: 10.13332/j.1000-1522.20140316
OU Guang-long, XU Hui, WANG Jun-feng, XIAO Yi-fa, CHEN Ke-yi, ZHENG Hai-mei. Building mixed effect models of stand biomass for Simao pine (Pinus kesiya var. langbianensis) natural forest[J]. Journal of Beijing Forestry University, 2015, 37(3): 101-110. doi: 10.13332/j.1000-1522.20140316
Citation: OU Guang-long, XU Hui, WANG Jun-feng, XIAO Yi-fa, CHEN Ke-yi, ZHENG Hai-mei. Building mixed effect models of stand biomass for Simao pine (Pinus kesiya var. langbianensis) natural forest[J]. Journal of Beijing Forestry University, 2015, 37(3): 101-110. doi: 10.13332/j.1000-1522.20140316

思茅松天然林林分生物量混合效应模型构建

doi: 10.13332/j.1000-1522.20140316
基金项目: 

国家自然科学基金项目(31160157)

详细信息
    作者简介:

    第一作者: 欧光龙,博士,实验师。主要研究方向:森林测计学。Email:olg2007621@126.com 地址: 650224云南省昆明市白龙寺300号西南林业大学西南地区生物多样性保育国家林业局重点实验室。责任作者: 胥辉,教授,博士生导师。主要研究方向:森林测计学。Email: zyxy213@126.com 地址:同上。

    第一作者: 欧光龙,博士,实验师。主要研究方向:森林测计学。Email:olg2007621@126.com 地址: 650224云南省昆明市白龙寺300号西南林业大学西南地区生物多样性保育国家林业局重点实验室。责任作者: 胥辉,教授,博士生导师。主要研究方向:森林测计学。Email: zyxy213@126.com 地址:同上。

Building mixed effect models of stand biomass for Simao pine (Pinus kesiya var. langbianensis) natural forest

  • 摘要: 本研究以云南省普洱市的思茅松天然林为对象,调查了3个位点45块样地的林分地上、根系和总生物量。以幂函数模型为基础构建林分生物量的基本模型;采用混合效应模型技术,考虑区域效应随机效应,选择基本混合效应模型,并分析模型的方差和协方差结构,分别构建3个维量的区域效应随机效应的混合效应模型;考虑林分因子、地形因子和气象因子固定效应,构建含环境因子固定效应和区域效应随机效应的林分生物量混合效应模型。所有模型均采用拟合指标和独立检验指标进行评价。结果表明:1) 从模型拟合情况看,考虑区域效应的随机效应模型均能显著提高一般回归模型的精度;在3类含环境因子固定效应模型中,含地形因子固定效应的区域混合效应模型均具有最低的AIC和BIC值,表现最好;2) 就模型独立性检验看,除地形因子固定效应的林分根系混合效应模型外,其余模型均优于一般回归模型;考虑环境因子固定效应的混合效应模型与普通区域效应混合模型相比,各个维量模型的独立性检验指标表现不一,但总体上差异不大;3) 综合考虑模型拟合和独立性检验结果,除林分根系生物量选择普通区域效应混合模型外,另2个维量均选择含地形因子固定效应和区域效应随机效应的混合效应模型。

     

  • [1] LUO Q B, ZENG W S, HE D B, et al. Establishment and application of compatible tree abovegound biomass models[J]. Journal of Natural Resources, 1999, 14(3):271-277.
    [1] LIETH H, WHITTAKER R H. Primary productivity of biosphere[M]. New York:Springer Verlag, 1975.
    [2] WEST P W. Tree and forest measurement[M]. 2nd ed. Berlin:Springer Verlag, 2009.
    [2] TANG S Z, ZHANG H R, XU H. Study on establish and estimate method of compatible biomass model[J]. Scientia Silvae Sinicae, 2000,36(Suppl.1):19-27.
    [3] CHOJNACKY D C. Allometric scaling theory applied to FIA biomass estimation: GTR NC-230[R]∥Washington: Forester, Forest Inventory Research, Enterprise Unit, USDA Forest Service, 2002:96-102.
    [3] TANG S Z, LANG K J, LI H K. Statistics and biology mathematics model computation (ForStat tutorial)[M]. Beijing: Science Press, 2009.
    [4] LI C M. Application of mixed effects models in forest growth model [J]. Scientia Silvae Sinicae, 2009,45(4):19-27.
    [4] JENKINS J C, CHOJNACKY D C, HEATH L S, et al. National-scale biomass estimators for United States tree species[J]. Forest Science, 2003,49: 12-35.
    [5] JENKINS J C, CHOJNACKY D C, HEATH L S, et al. Comprehensive database of diameter-based biomass regressions for North American tree species[R]. Newtown Square: Northeastern Research Station, USDA Forest Service, 2004.
    [5] FU L Y. Nonlinear mixed effects model and its application in forestry [D]. Beijing: Chinese Academy of Forestry, 2012.
    [6] TER-MIKAELIAN M T, KORZUKHIN M D. Biomass equations for sixty-five North American tree species[J]. Forest Ecology and Management, 1997,97: 1-24.
    [6] LI C M. Application of mixed effects models in forest growth models[D]. Beijing: Chinese Academy of Forestry, 2010.
    [7] ZIANIS D, MUUKKONEN P, MAKIPAA R, et al. Biomass and stem volume equations for tree species in Europe[M]. Tampere: Tammer-Paino Oy, 2005.
    [7] 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[J]. Forest Research, 2011,24(3):285-291.
    [8] Compilation Commitiee of Yunnan Forest. Yunnan Forest[M]. Kunming: Yunnan Science and Technology Press, Beijing: China Forestry Publishing House, 1986.
    [8] MUUKKONEN P. Forest inventory-based large-scale forest biomass and carbon budget assessment: new enhanced methods and use of remote sensing for verification[D]. Helsinki: University of Helsinki, 2007.
    [9] 骆期邦, 曾伟生, 贺东北,等. 立木地上部分生物量模型的建立及其应用研究[J]. 自然资源学报, 1999, 14(3):271-277.
    [9] Southwest Forestry College, Forestry Department of Yunnan Province. Iconographia arbororum yunnanicorum[M]. Kunming:Yunnan Science and Technology Press, 1988.
    [10] 唐守正, 张会儒, 胥辉. 相容性生物量模型的建立及其估计方法研究[J]. 林业科学研究, 2000,36(专刊1):19-27.
    [10] WU Z L, DANG C L. The biomass of Pinus kesiya var. langbianensis stands in Pu-er district,Yunnan[J]. Journal of Yunnan University:Natural Science Edition,1992,14(2):161-167.
    [11] WEN Q Z, ZHAO Y F, CHEN X M, et al. Dynamic study on the values for ecological service function of Pinus kesiya forest in China[J]. Forest Research,2010,23(5):671-677.
    [11] 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, 2009.
    [12] YUE F, YANG B. Study on carbon sink of Pinus kesiya forests[J]. Jiangsu Agricultural Sciences, 2011,39(5): 467-469.
    [12] PARRESOL B R. Additivity of nonlinear biomass equations[J]. Canadian Journal of Forest Research, 2001,31:865-878.
    [13] BI H, TUMER J, LAMBERT M J. Additive biomass equations for native eucalypt forest trees of temperate Australia[J].Trees, 2004,18(4):467-479.
    [13] LI J. Dynamics of biomass and carbon stock for young and middle aged plantation of Simao pine (Pinus kesiya var. langbianensis)[D]. Beijing : Beijing Forestry University, 2011.
    [14] 李春明. 混合效应模型在森林生长模型中的应用[J].林业科学, 2009,45(4):131-138.
    [14] DANG C L, WU Z L. Studies on the biomass for Castanopsis echidnocarpa community of monsoon evergreen broad-leaved forest[J]. Journal of Yunnan University:Natural Science Edition, 1992,14(2):95-107.
    [15] LAIRD N M, WARE J H. Random effeets models for longitudinal data [J]. Biometries,1982, 38: 963-974.
    [15] LI G X, MENG G T, FANG X J, et al. Characteristics of Alnus cremastogyne plantation community and its biomass in central Yunnan Plateau[J]. Journal of Zhejiang Forestry College, 2006,23(4):362-366.
    [16] LI H K, LEI Y C. Evaluation on biomass and carbon storage of forest vegetation in China[M]. Beijing: China Forestry Publishing House,2010.
    [16] 符利勇. 非线性混合效应模型及其在林业上的应用[D]. 北京:中国林业科学研究院,2012.
    [17] LIU Y C, JIANG Y B, CHEN H W, et al. Regression equations for individual tree of Betula alnoides plantation[J]. Journal of Fujian Forestry Science and Technology, 2008,35(2):42-46.
    [17] 李春明. 混合效应模型在森林生长模拟研究中的应用[D]. 北京:中国林业科学研究院,2010.
    [18] LI D. Study on carbon storage and allocation of the monsoonal evergreen broad-leaved forests in Xishuangbanna[D]. Menglun: Xishuangbanna Tropical Botanical Garden, Chinese Academy Sciences, 2006.
    [18] ZHANG Y J, BORDERS B E. Using a system mixed effects modeling method to estimate tree compartment biomass for intensively managed Loblolly pines-an allometric approach[J]. Forest Ecology and Management, 2004,194:145-157.
    [19] FEHRMANN L, LEHTONEN A, KLEINN C, et al. Comparison of linear and mixed-effect regression models and a K-nearest neighbour approach for estimation of single-tree biomass[J]. Canadian Journal of Forest Research, 2008, 38(1):1-9.
    [19] XU H, ZHANG H R. Study on tree biomass models[M]. Kunming:Yunnan Science and Technology Press, 2002.
    [20] PEARCE H G, ANDERSON W R, FOGARTY L G, et al. Linear mixed-effects models for estimation biomass and fuel loads in shrublands[J]. Canadian Journal of Forest Research, 2010, 40(10):2015-2026.
    [21] 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.
    [22] FU L Y, ZENG W S, TANG S Z, et al. Using linear mixed model and dummy variable model approaches to construct compatible single-tree biomass equations at different scales: a case study for Masson pine in Southern China [J]. Journal of Forest Science, 2012, 58(3):101-115.
    [23] FU L Y, ZENG W, ZHANG H, et al. Generic linear mixed-effects invidual-tree biomass models for Pinus massoniana in southern China[J]. Southern Forests, 2014, 76(1):47-56.
    [24] 云南森林编写委员会. 云南森林[M]. 昆明: 云南科技出版社, 北京 :中国林业出版社, 1986.
    [25] 西南林学院, 云南省林业厅.云南树木图志[M]. 昆明: 云南科技出版社, 1988.
    [26] 吴兆录,党承林.云南普洱地区思茅松林的生物量[J].云南大学学报:自然科学版,1992,14(2):161-167.
    [27] 温庆忠,赵远藩,陈晓鸣,等.中国思茅松林生态服务功能价值动态研究[J]. 林业科学研究, 2010,23(5):671-677.
    [28] 岳锋,杨斌.思茅松林碳汇功能研究[J].江苏农业科学, 2011,39(5): 467-469.
    [29] 李江.思茅松中幼林人工林生物量和碳储量动态研究[D].北京:北京林业大学, 2011.
    [30] 党承林,吴兆录. 季风常绿阔叶林短刺栲群落的生物量研究[J]. 云南大学学报:自然科学版, 1992,14(2):95-107.
    [31] 李贵祥,孟广涛,方向京,等. 滇中高原桤木人工林群落特征及生物量分析[J]. 浙江林学院学报,2006,23(4):362-366.
    [32] 李海奎, 雷渊才. 中国森林植被生物量和碳储量评估[M]. 北京:中国林业出版社, 2010.
    [33] 刘云彩,姜远标,陈宏伟,等. 西南桦人工林单株生物量的回归模型[J]. 福建林业科技, 2008,35(2):42-46.
    [34] 李东. 西双版纳季风常绿阔叶林的碳贮量及其分配特征研究[D]. 勐仑: 中国科学院西双版纳热带植物园, 2006.
    [35] 胥辉,张会儒. 林木生物量模型研究[M]. 昆明:云南科技出版社, 2002.
    [36] PINHEIRO J C, BATES D M. Mixed effects models in S and S-plus[M]. New York: Springer Verlag, 2000.
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出版历程
  • 收稿日期:  2014-06-10
  • 修回日期:  2014-11-23
  • 刊出日期:  2015-03-31

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