科尔沁沙地2种优势固沙灌木的相容性生物量模型
|
摘要
基于现有的灌木生物量模型存在各组分与总量不相容问题,以半干旱区科尔沁沙地2种优势固沙灌木小叶锦鸡儿(Caragana microphylla)和黄柳(Salix gordejevii)为对象,通过对大样本的相关形态指标及生物量实测数据进行非线性回归和非线性误差变量联立方程组的计算,建立了2种灌木叶片、新枝、老枝和地上生物量的独立模型及与各组分相容的生物量模型,并通过决定系数R~2\,估计值的标准差SEE\,总相对误差TRE\,平均系统误差MSE(ASE)\,平均预估误差MPE和平均百分标准误差MPSE对模型进行评价。结果表明:非线性加权回归使得两种灌木各组分的独立模型拟合效果优化,而生物量相容模型与独立模型相比,由于抽样误差的存在拟合效果不佳,相关评价指标较低。
Based on the existing shrub biomass model, there is a problem that the components are incompatible with the total amount. In this study, the independent model of new shoot, old shoot, aboveground biomass and the model which was compatible with each component were constructed after the nonlinear regression and nonlinear error variables simultaneous equations were calculated by comparing the relevant morphological indicators and biomass measured data of large samples about two dominant sand-fixing shrubs, Caragana microphylla and Salix gordejevii, were studied in Horqin Sandy Land. The model was evaluated by the largest determination coefficients(R~2), the smallest standard error of estimates(SEE), the total relative error(TRE), the average systematic error(MSE/ASE), the mean percent estimate error(MPE) and the average percentage standard error(MPSE). The results showed that the nonlinear weighted regression optimized the independent model fitting effect of the two shrubs, compared with the independent model, the biomass compatible model had poor fitting effect due to the existence of sampling error, and the relevant evaluation index was low.
Based on the existing shrub biomass model, there is a problem that the components are incompatible with the total amount. In this study, the independent model of new shoot, old shoot, aboveground biomass and the model which was compatible with each component were constructed after the nonlinear regression and nonlinear error variables simultaneous equations were calculated by comparing the relevant morphological indicators and biomass measured data of large samples about two dominant sand-fixing shrubs, Caragana microphylla and Salix gordejevii, were studied in Horqin Sandy Land. The model was evaluated by the largest determination coefficients(R~2), the smallest standard error of estimates(SEE), the total relative error(TRE), the average systematic error(MSE/ASE), the mean percent estimate error(MPE) and the average percentage standard error(MPSE). The results showed that the nonlinear weighted regression optimized the independent model fitting effect of the two shrubs, compared with the independent model, the biomass compatible model had poor fitting effect due to the existence of sampling error, and the relevant evaluation index was low.
引文
[1] 刘长成,魏雅芬,刘玉国,等.贵州普定喀斯特次生林乔灌层地上生物量[J].植物生态学报,2009,33(4):698-705.
[2] 杨星华.毛竹单株地上部分生物量相容性模型研究[D].北京:北京林业大学,2016.
[3] 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测方法研究[J].北京师范大学学报:自然科学版,2004,40(5):700-704.
[4] 蒋齐,李生宝,翟明普.我国的固沙型灌木林及其研究进展[J].干旱区资源与环境,1998,12(2):88-96.
[5] 童新风,杨红玲,宁志英,等.科尔沁沙地优势固沙灌木的生物量预测模型[J].中国沙漠,2018,38(3):553-559.
[6] 曾伟生,白锦贤,宋连城,等.内蒙古柠条和山杏单株生物量模型研建[J].林业科学研究,2015,28(3):311-316.
[7] 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.
[8] 曹萌,牛树奎,李连强.松山自然保护区5种灌木的地上生物量模型[J].福建农林大学学报:自然科学版,2018,47(4):435-438.
[9] 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(1):12-35.
[10] Rondeux J,Wagner M.National forest inventoriesl-pathways for common reporting[J].Hip Joint,2010,30(159):56-58.
[11] Li Y Q,Zhou X H,Brandle J R,et al.Temporal progress in improving carbon and nitrogen storage by grazing exclosure practice in a degraded land area of China’s Horqin Sandy Grassland[J].Agriculture Ecosystems & Environment,2012,159:55-61.
[12] 赵哈林,周瑞莲,张铜会,等.科尔沁沙地植被的统计学特征与土地沙漠化[J].中国沙漠,2004,24(3):20-24.
[13] 李玉霖,孟庆涛,赵学勇,等.科尔沁沙地流动沙丘植被恢复过程中群落组成及植物多样性演变特征[J].草业学报,2007,16(6):54-61.
[14] 李玉霖,崔建垣,苏永中.不同沙丘生境主要植物比叶面积和叶干物质含量的比较[J].生态学报,2005,25(2):304-311.
[15] 左小安,赵哈林,赵学勇,等.科尔沁沙地不同尺度上沙丘景观格局动态变化分析[J].中国沙漠,2009,29(5):785-795.
[16] 王少昆,赵学勇,张铜会,等.科尔沁沙地几种灌木对根际微生物的影响[J].干旱区资源与环境,2012,26(5):140-144.
[17] 宁志英,李玉霖,杨红玲,等.沙化草地土壤碳氮磷化学计量特征及其对植被生产力与多样性的影响[J].生态学报,2019,39(10):1-9.
[18] 曹磊,李海奎.两种相容性生物量模型的比较——以广东省3个阔叶树种为例[J].生态学杂志,2019(6):1916-1925.
[19] 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.
[20] 张会儒,唐守正,胥辉.关于生物量模型中的异方差问题[J].林业资源管理,1999,28(1):47-50.
[21] 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.
[22] 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,2013.42(5):55-61.
[23] 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,2009:75-283.
[24] 曾伟生,唐守正.立木生物量方程的优度评价和精度分析[J].林业科学,2011,47(11):106-113.
[25] Berk K N.Validating regression procedures with new data[J].Technometrics,1984,26(4):331-338.
[26] Ketterings Q M,Coe R,Noordwijk M V,et al.Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests[J].Forest Ecology and Management,2001,146(1/2/3):200-209.
[27] Kozak A,Kozak R.Does cross validation provide additional information in the evaluation of regression models[J].Canadian Journal of Forest Research,2003,33:976-987.
[28] 李亚藏,冯仲科.气候敏感的马尾松生物量相容性方程系统研建[J].林业科学,2019,55(5):65-73.
[29] 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,2000,36(增刊1):19-27.
[30] 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):80-86.
[31] 胥辉,刘伟平.相容性生物量模型研究[J].福建林学院学报,2001,142(1):18-23.
[32] Tang S Z,Li Y,Wang Y H.Simultaneous equations,error-in-variable models,and model integration in systems ecology[J].Ecological Modelling,2001,142(3):285-294.
[33] 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.
[34] 曹磊,李海奎.广东省樟树相容性生物量模型的构建[J].森林与环境学报,2018,38(4):458-465.
[35] 宁虎森,罗青红,吉小敏,等.3种沙地植物光合碳同化对环境因子的生理响应[J].林业科学,2014,50(9):173-179.
[36] Fu L,Lei X,Hu Z,et al.Integrating regional climate change into allometric equations for estimating tree aboveground biomass of Masson pine in China[J].Annals of Forest Science,2017,74(2):42.
[2] 杨星华.毛竹单株地上部分生物量相容性模型研究[D].北京:北京林业大学,2016.
[3] 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测方法研究[J].北京师范大学学报:自然科学版,2004,40(5):700-704.
[4] 蒋齐,李生宝,翟明普.我国的固沙型灌木林及其研究进展[J].干旱区资源与环境,1998,12(2):88-96.
[5] 童新风,杨红玲,宁志英,等.科尔沁沙地优势固沙灌木的生物量预测模型[J].中国沙漠,2018,38(3):553-559.
[6] 曾伟生,白锦贤,宋连城,等.内蒙古柠条和山杏单株生物量模型研建[J].林业科学研究,2015,28(3):311-316.
[7] 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.
[8] 曹萌,牛树奎,李连强.松山自然保护区5种灌木的地上生物量模型[J].福建农林大学学报:自然科学版,2018,47(4):435-438.
[9] 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(1):12-35.
[10] Rondeux J,Wagner M.National forest inventoriesl-pathways for common reporting[J].Hip Joint,2010,30(159):56-58.
[11] Li Y Q,Zhou X H,Brandle J R,et al.Temporal progress in improving carbon and nitrogen storage by grazing exclosure practice in a degraded land area of China’s Horqin Sandy Grassland[J].Agriculture Ecosystems & Environment,2012,159:55-61.
[12] 赵哈林,周瑞莲,张铜会,等.科尔沁沙地植被的统计学特征与土地沙漠化[J].中国沙漠,2004,24(3):20-24.
[13] 李玉霖,孟庆涛,赵学勇,等.科尔沁沙地流动沙丘植被恢复过程中群落组成及植物多样性演变特征[J].草业学报,2007,16(6):54-61.
[14] 李玉霖,崔建垣,苏永中.不同沙丘生境主要植物比叶面积和叶干物质含量的比较[J].生态学报,2005,25(2):304-311.
[15] 左小安,赵哈林,赵学勇,等.科尔沁沙地不同尺度上沙丘景观格局动态变化分析[J].中国沙漠,2009,29(5):785-795.
[16] 王少昆,赵学勇,张铜会,等.科尔沁沙地几种灌木对根际微生物的影响[J].干旱区资源与环境,2012,26(5):140-144.
[17] 宁志英,李玉霖,杨红玲,等.沙化草地土壤碳氮磷化学计量特征及其对植被生产力与多样性的影响[J].生态学报,2019,39(10):1-9.
[18] 曹磊,李海奎.两种相容性生物量模型的比较——以广东省3个阔叶树种为例[J].生态学杂志,2019(6):1916-1925.
[19] 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.
[20] 张会儒,唐守正,胥辉.关于生物量模型中的异方差问题[J].林业资源管理,1999,28(1):47-50.
[21] 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.
[22] 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,2013.42(5):55-61.
[23] 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,2009:75-283.
[24] 曾伟生,唐守正.立木生物量方程的优度评价和精度分析[J].林业科学,2011,47(11):106-113.
[25] Berk K N.Validating regression procedures with new data[J].Technometrics,1984,26(4):331-338.
[26] Ketterings Q M,Coe R,Noordwijk M V,et al.Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests[J].Forest Ecology and Management,2001,146(1/2/3):200-209.
[27] Kozak A,Kozak R.Does cross validation provide additional information in the evaluation of regression models[J].Canadian Journal of Forest Research,2003,33:976-987.
[28] 李亚藏,冯仲科.气候敏感的马尾松生物量相容性方程系统研建[J].林业科学,2019,55(5):65-73.
[29] 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,2000,36(增刊1):19-27.
[30] 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):80-86.
[31] 胥辉,刘伟平.相容性生物量模型研究[J].福建林学院学报,2001,142(1):18-23.
[32] Tang S Z,Li Y,Wang Y H.Simultaneous equations,error-in-variable models,and model integration in systems ecology[J].Ecological Modelling,2001,142(3):285-294.
[33] 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.
[34] 曹磊,李海奎.广东省樟树相容性生物量模型的构建[J].森林与环境学报,2018,38(4):458-465.
[35] 宁虎森,罗青红,吉小敏,等.3种沙地植物光合碳同化对环境因子的生理响应[J].林业科学,2014,50(9):173-179.
[36] Fu L,Lei X,Hu Z,et al.Integrating regional climate change into allometric equations for estimating tree aboveground biomass of Masson pine in China[J].Annals of Forest Science,2017,74(2):42.