云南松不同区域相容性生物量模型的构建
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摘要
【目的】探索云南松不同区域相容性生物量模型的构建方法,为云南松生物量建模工作提供技术支撑。【方法】以四川、西藏和云南150株云南松地上生物量实测数据为基础,选取基础生物量模型(一元、二元模型),引入以地理区域为特征的哑变量模型,建立不同省(自治区)云南松的地上总生物量及树干、干材、干皮、树冠、树枝和树叶各项生物量的通用模型;然后采用非线性度量误差联立方程组法,建立地上总生物量与各分项生物量的相容性生物量模型,根据方程构成的不同,该方法又分为比例总量直接控制及代数和控制2种方案;对上述模型的拟合效果进行评价。【结果】基础模型中,各项生物量的二元模型的拟合效果较一元模型明显提高。比例总量直接控制及代数和控制2种方案都能有效解决地上总生物量与各分项生物量间不相容的问题,其中二元模型优于一元模型,比例总量直接控制方案及代数和控制方案的拟合效果基本相当;引入哑变量可以有效地将不同地域的生物量模型融为一体。【结论】引入哑变量可减少工作量、增强模型稳定性;综合考虑模型精度和建模工作量,建议采用非线性度量误差联立方程组代数和控制方案构建相容性生物量模型。
【Objective】This study explored the method of constructing compatible biomass models for different regions to provide technical support for the biomass modeling of Pinus yunnanensis.【Method】Based on the measurement data of aboveground biomass of 150 P.yunnanensis trees in Sichuan,Xizang and Yunnan,the general models for total above ground biomass as well as stem,wood,bark,crown,branch and leaf biomasses for trees from different regions were established with basic biomass models(one or two predictor variables)and dummy variables characterized by geographic regions.Then,the compatible biomass models were built using the method of nonlinear simultaneous equations with measurement error.According to different equations,the method was divided into direct control under total tree biomass by proportions and sum control.At last,the fitting effect was evaluated and analyzed.【Result】In basic models,the fitting effect of models with two predictor variables was significantly higher than models with one predictor variable.Both the direct control under total tree biomass by proportions and sum control could efficientlyensure that the total biomass was equal to the summary of its components with high accuracy.The models with two predictor variables were better than models with one predictor variable and the direct control method was as effective as sum control method.The introduction of dummy variable could integrate different regional biomass models effectively.【Conclusion】Introducing dummy variable was helpful to reduce workload and enhance model stability.For balancing prediction accuracy and workload,it is suggested to adapt the nonlinear simultaneous equations with measurement error of sum control to build compatible biomass models.
【Objective】This study explored the method of constructing compatible biomass models for different regions to provide technical support for the biomass modeling of Pinus yunnanensis.【Method】Based on the measurement data of aboveground biomass of 150 P.yunnanensis trees in Sichuan,Xizang and Yunnan,the general models for total above ground biomass as well as stem,wood,bark,crown,branch and leaf biomasses for trees from different regions were established with basic biomass models(one or two predictor variables)and dummy variables characterized by geographic regions.Then,the compatible biomass models were built using the method of nonlinear simultaneous equations with measurement error.According to different equations,the method was divided into direct control under total tree biomass by proportions and sum control.At last,the fitting effect was evaluated and analyzed.【Result】In basic models,the fitting effect of models with two predictor variables was significantly higher than models with one predictor variable.Both the direct control under total tree biomass by proportions and sum control could efficientlyensure that the total biomass was equal to the summary of its components with high accuracy.The models with two predictor variables were better than models with one predictor variable and the direct control method was as effective as sum control method.The introduction of dummy variable could integrate different regional biomass models effectively.【Conclusion】Introducing dummy variable was helpful to reduce workload and enhance model stability.For balancing prediction accuracy and workload,it is suggested to adapt the nonlinear simultaneous equations with measurement error of sum control to build compatible biomass models.
引文
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[8]曾伟生,唐守正.利用度量误差模型方法建立相容性立木生物量方程系统[J].林业科学研究,2010,23(6):797-803.Zeng W S,Tang S Z.Using measurement error modeling method to establish compatible single tree biomass equations system[J].Forest Research,2010,23(6):797-803.
[9]符利勇,雷渊才,孙伟,等.不同林分起源的相容性生物量模型构建[J].生态学报,2014,34(6):1461-1470.Fu L Y,Lei Y C,Sun W,et al.Development of compatible biomass models for trees from different stand origin[J].Acta Ecologica Sinica,2014,34(6):1461-1470.
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[11]符利勇,曾伟生,唐守正.利用混合模型分析地域对国内马尾松生物量的影响[J].生态学报,2011,31(19):5797-5808.Fu L Y,Zeng W S,Tang S Z.Analysis the effect of region impacting on the biomass of domestic Masson pine using mixed model[J].Acta Ecologica Sinica,2011,31(19):5797-5808.
[12]李丽霞,郜艳晖,张瑛.哑变量在统计分析中的应用[J].数理医药学杂志,2006(1):51-53.Li L X,Gao Y H,Zhang Y.The application of dummy variable in statistics analysis[J].Journal of Mathematical Medicine,2006(1):51-53.
[13]郑冬梅,曾伟生.用哑变量方法构建东北落叶松和栎类分段地上生物量模型[J].北京林业大学学报,2013(6):23-27.Zheng D M,Zeng W S.Using dummy variable approach to construct segemented abovegroud biomass models for larch and oak in northeastern China[J].Journal of Beijing Forestry University,2013(6):23-27.
[14]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[J].Scientia Silvae Sinicae,2013,49(10):74-79.
[15]Parresol B R.Additivity of nonlinear biomass equations[J].Canadian Journal of Forest Research,2001,31(5):865-878.
[16]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(1/2/3):145-157.
[17]Bi H,Turner J,Lambert M J.Additive biomass equations for native eucalypt forest trees of temperale in Australia[J].Trees,2004,18(4):467-479.
[18]Fehrmann L,Lehtonen A,Kleinn C,et al.Comparison of linear and mixed-effect regression models and a k-nearest neighbor approach for estimation of single-tree biomass[J].Canadian Journal of Forest Research,2008,38(1):1-9.
[19]吕常笑.不同区域马尾松相容性生物量模型研究[D].北京:北京林业大学,2016.LüC X.Research on the comptaible biomass models of Pinus massonianain different regions[D].Beijing:Beijing Forestry University,2016.
[20]曾伟生.全国立木生物量方程建模方法研究[D].北京:中国林业科学研究院,2011.Zeng W S.Methodology on modeling of single-tree biomass equations for national biomass estimation in China[D].Beijing:Chinese Academy of Forestry,2011.
[21]Parresol B R.Assessing tree and stand biomass:a review with examples and critical comparisons[J].Forest Science,1999,45(4):573-593.
[22]唐守正,郎奎建,李海奎.统计与生物数学模型计算教程[M].北京:科学出版社,2009.Tang S Z,Lang K J,Li H K.Statistics and mathematical model calculation ForStat Course[M].Beijing:Science Press,2009.
[23]唐守正,李勇.一种多元非线性度量误差模型的参数估计及算法[J].生物数学学报,1996,11(1):23-27.Tang S Z,Li Y.An algorithm for estimating multivariate nonlinear error-in-measure models[J].Journal of Bioma the Matics,1996,11(1):23-27.
[24]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):42-55.Fu L Y,Lei Y C,Zeng W S.Comparison of several compatible biomass models and estimation approaches[J].Scientia Silvae Sinicae,2014,50(6):42-55.
[25]蔡兆炜,孙玉军,施鹏程.基于非线性度量误差的杉木相容性生物量模型[J].东北林业大学学报,2014,42(9):28-32.Cai Z W,Sun Y J,Shi P C.Compatible tree biomass models for Chinese Fir plantations based on nonlinear measurement error[J].Journal of Northeast Forestry University,2014,42(9):28-32.
[26]曾伟生,骆期邦,贺东北.论加权回归与建模[J].林业科学,1999,35(5):5-11.Zeng W S,Luo Q B,He D B.Research on weighting regression and modeling[J].Scientia Silae Sinicae,1999,35(5):5-11.
[27]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.Zeng W S,Tang S Z.Bias correction in logarithmic regression and comparison with weighted regression for non_linear models[J].Forest Research,2011,24(2):137-143.
[28]曾伟生.加权回归估计中不同权函数的对比分析[J].林业资源管理,2013,10(5):55-61.Zeng W S.Comparison of different weight functions in weighted regression[J].Forest Resources Management,2013,10(5):55-61.
[29]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.Zeng W S,Tang S Z.Goodness evaluation and precision analysis of tree biomass equations[J].Scientia Silvae Sinicae,2011,47(11):106-113.
[30]陈飞,王健敏,孙宝刚,等.云南松的地理分布与气候关系[J].林业科学研究,2012,25(2):163-168.Chen F,Wang J M,Sun B G,et al.Relationship between geographical distribution of Pinus yunnanensis and climate[J].Forest Research,2012,25(2):163-168.
[31]戴开结,何方,沈有信,等.云南松研究综述[J].中南林学院学报,2006,26(2):138-142.Dai K J,He F,Shen Y X,et al.Advances in the research on Pinus yunnanensis forest[J].Journal of Central South for Restry University,2006,26(2):138-142.
[32]皮文林,罗方书,万国华.云南松生长的早晚期相关初探[J].云南植物研究,1994,16(1):90-92.Pi W L,Luo F S,Wan G H.The earlier-later period correlation of increment of Pinus yunnanensis[J].Acta Botanica Yunnanica,1994,16(1):90-92.
[2]Tatarinov F A,Cienciala E,Vopenka P.Effect of climate change and nitrogen deposition on central-European forests:regionalscale simulation for South Bohemia[J].Forest Ecology and Management,2011,262(10):1919-1927.
[3]Mugasha W A,Eid T.Allometric models for prediction of above-and belowground biomass of trees in the miombo woodlands of Tanzania[J].Forest Ecology and Management,2013,310(5):87-101.
[4]Ene L T,Naesset E,Gobakken T.Large-scale estimation of aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data[J].Remote Sensing of Environment,2016,186(10):626-636.
[5]Waring R H,Runing S W.Forest ecosystems:analusis at mulitiple scales[M].2nd ed.San Diego,Calif:Academic Press,1998.
[6]胥辉.立木生物量模型的构建及估计方法的研究[D].北京:北京林业大学,1998.Xu H.Studies on staanding tree biomass models and corresponding parameter estimation[D].Beijing:Beijing Forestry University,1998.
[7]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.Luo Q B,Zeng W S,He D B,et al.Establishment and application of compatible tree above-ground biomass models[J].Journal of Natural Resources,1999,14(3):271-277.
[8]曾伟生,唐守正.利用度量误差模型方法建立相容性立木生物量方程系统[J].林业科学研究,2010,23(6):797-803.Zeng W S,Tang S Z.Using measurement error modeling method to establish compatible single tree biomass equations system[J].Forest Research,2010,23(6):797-803.
[9]符利勇,雷渊才,孙伟,等.不同林分起源的相容性生物量模型构建[J].生态学报,2014,34(6):1461-1470.Fu L Y,Lei Y C,Sun W,et al.Development of compatible biomass models for trees from different stand origin[J].Acta Ecologica Sinica,2014,34(6):1461-1470.
[10]Parreso I B R.Additivity of nonlinear biomass equations[J].Can J For Res,2001,31:865-878.
[11]符利勇,曾伟生,唐守正.利用混合模型分析地域对国内马尾松生物量的影响[J].生态学报,2011,31(19):5797-5808.Fu L Y,Zeng W S,Tang S Z.Analysis the effect of region impacting on the biomass of domestic Masson pine using mixed model[J].Acta Ecologica Sinica,2011,31(19):5797-5808.
[12]李丽霞,郜艳晖,张瑛.哑变量在统计分析中的应用[J].数理医药学杂志,2006(1):51-53.Li L X,Gao Y H,Zhang Y.The application of dummy variable in statistics analysis[J].Journal of Mathematical Medicine,2006(1):51-53.
[13]郑冬梅,曾伟生.用哑变量方法构建东北落叶松和栎类分段地上生物量模型[J].北京林业大学学报,2013(6):23-27.Zheng D M,Zeng W S.Using dummy variable approach to construct segemented abovegroud biomass models for larch and oak in northeastern China[J].Journal of Beijing Forestry University,2013(6):23-27.
[14]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[J].Scientia Silvae Sinicae,2013,49(10):74-79.
[15]Parresol B R.Additivity of nonlinear biomass equations[J].Canadian Journal of Forest Research,2001,31(5):865-878.
[16]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(1/2/3):145-157.
[17]Bi H,Turner J,Lambert M J.Additive biomass equations for native eucalypt forest trees of temperale in Australia[J].Trees,2004,18(4):467-479.
[18]Fehrmann L,Lehtonen A,Kleinn C,et al.Comparison of linear and mixed-effect regression models and a k-nearest neighbor approach for estimation of single-tree biomass[J].Canadian Journal of Forest Research,2008,38(1):1-9.
[19]吕常笑.不同区域马尾松相容性生物量模型研究[D].北京:北京林业大学,2016.LüC X.Research on the comptaible biomass models of Pinus massonianain different regions[D].Beijing:Beijing Forestry University,2016.
[20]曾伟生.全国立木生物量方程建模方法研究[D].北京:中国林业科学研究院,2011.Zeng W S.Methodology on modeling of single-tree biomass equations for national biomass estimation in China[D].Beijing:Chinese Academy of Forestry,2011.
[21]Parresol B R.Assessing tree and stand biomass:a review with examples and critical comparisons[J].Forest Science,1999,45(4):573-593.
[22]唐守正,郎奎建,李海奎.统计与生物数学模型计算教程[M].北京:科学出版社,2009.Tang S Z,Lang K J,Li H K.Statistics and mathematical model calculation ForStat Course[M].Beijing:Science Press,2009.
[23]唐守正,李勇.一种多元非线性度量误差模型的参数估计及算法[J].生物数学学报,1996,11(1):23-27.Tang S Z,Li Y.An algorithm for estimating multivariate nonlinear error-in-measure models[J].Journal of Bioma the Matics,1996,11(1):23-27.
[24]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):42-55.Fu L Y,Lei Y C,Zeng W S.Comparison of several compatible biomass models and estimation approaches[J].Scientia Silvae Sinicae,2014,50(6):42-55.
[25]蔡兆炜,孙玉军,施鹏程.基于非线性度量误差的杉木相容性生物量模型[J].东北林业大学学报,2014,42(9):28-32.Cai Z W,Sun Y J,Shi P C.Compatible tree biomass models for Chinese Fir plantations based on nonlinear measurement error[J].Journal of Northeast Forestry University,2014,42(9):28-32.
[26]曾伟生,骆期邦,贺东北.论加权回归与建模[J].林业科学,1999,35(5):5-11.Zeng W S,Luo Q B,He D B.Research on weighting regression and modeling[J].Scientia Silae Sinicae,1999,35(5):5-11.
[27]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.Zeng W S,Tang S Z.Bias correction in logarithmic regression and comparison with weighted regression for non_linear models[J].Forest Research,2011,24(2):137-143.
[28]曾伟生.加权回归估计中不同权函数的对比分析[J].林业资源管理,2013,10(5):55-61.Zeng W S.Comparison of different weight functions in weighted regression[J].Forest Resources Management,2013,10(5):55-61.
[29]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.Zeng W S,Tang S Z.Goodness evaluation and precision analysis of tree biomass equations[J].Scientia Silvae Sinicae,2011,47(11):106-113.
[30]陈飞,王健敏,孙宝刚,等.云南松的地理分布与气候关系[J].林业科学研究,2012,25(2):163-168.Chen F,Wang J M,Sun B G,et al.Relationship between geographical distribution of Pinus yunnanensis and climate[J].Forest Research,2012,25(2):163-168.
[31]戴开结,何方,沈有信,等.云南松研究综述[J].中南林学院学报,2006,26(2):138-142.Dai K J,He F,Shen Y X,et al.Advances in the research on Pinus yunnanensis forest[J].Journal of Central South for Restry University,2006,26(2):138-142.
[32]皮文林,罗方书,万国华.云南松生长的早晚期相关初探[J].云南植物研究,1994,16(1):90-92.Pi W L,Luo F S,Wan G H.The earlier-later period correlation of increment of Pinus yunnanensis[J].Acta Botanica Yunnanica,1994,16(1):90-92.