文献类型：期刊文献

中文题名：西南桦人工林树皮厚度模型模拟

英文题名：Simulating Bark Thickness for Betula alnoides Plantations

作者：唐诚[1,2] 王春胜[1] 庞圣江[3] 黄日逸[3] 曾杰[1]

第一作者：唐诚

通信作者：Zeng, Jie

机构：[1]中国林业科学研究院热带林业研究所;[2]石河子大学农学院;[3]中国林业科学研究院热带林业实验中心

年份：2017

卷号：53

期号：7

起止页码：85-93

中文期刊名：林业科学

外文期刊名：Scientia Silvae Sinicae

收录：CSTPCD;;EI(收录号：20174304296437);Scopus(收录号：2-s2.0-85031813506);北大核心:【北大核心2014】；CSCD:【CSCD2017_2018】；

基金："十二五"国家科技支撑专题"西南桦珍贵用材林定向培育技术研究"(2102BAD21B0102)

语种：中文

中文关键词：西南桦;树皮因子;相对排序法;残差分析

外文关键词：Betula alnoides; bark regimes; relative ranking system; residual analysis

分类号：S758

摘要：【目的】开展西南桦人工林树皮厚度模型模拟,为估算西南桦材积、出材量以及树皮蓄积量奠定基础。【方法】通过树干解析获取各区分段的带皮直径、去皮直径和树皮厚度等信息,按照约75%和25%的比例随机分为建模和检验数据集。选取13个模型,运用最小二乘法进行拟合,并对模型参数进行显著性检验(显著性水平0.05)。对于参数检验显著的模型,依据偏差、绝对偏差、均方误差和决定系数4个统计指标,应用相对排序法评价模型拟合优度。采用配对t检验方法检验模型的有效性,剔除预估值和实测值差异显著的模型,进一步诊断保留模型的共线性以及异方差性,最终筛选出适于拟合西南桦人工林树皮厚度的模型。【结果】模型参数显著性检验结果表明,在13个模型中,模型(2)和(5)有参数与零差异不显著(P≥0.05),其余模型的所有参数均显著(P<0.05)。依据统计指标对11个模型进行综合排序,模型(3)和(4)拟合胸高处树皮厚度的效果相近,优于模型(1);模型(7)对于任意高度处树皮厚度的拟合效果优于模型(6);模型(8)拟合相对树皮厚度的效果优于模型(9);模型(11)和(13)对去皮直径的拟合效果优于模型(10)和(12)。t检验结果表明,模型(9)、(12)和(13)的预估值与实测值差异显著,予以剔除。剩余8个模型中,模型(4)存在较弱共线性,其他模型均不存在共线性问题。由残差图分析和怀特检验可知,模型(1)、(3)和(4)不存在异方差性,模型(6)、(7)、(8)、(10)和(11)均存在明显的异方差性,通过变量变换其异方差性得到较好修正。【结论】拟合西南桦胸高处树皮厚度、任意高度处树皮厚度、相对树皮厚度和去皮直径4个树皮因子,宜分别选用模型(3)、(7)、(8)和(11)。林业调查工作中胸径容易测定,且人工林年龄数据容易获取,任意高度处直径可用林分速测镜快速测定,这些模型的应用简单可行。树皮厚度除受年龄、树高、胸径等林木因子影响外,还可能受立地因子影响,未来需综合考虑以提高模型拟合精度。
【Objective】Simulating bark thickness for Betula alnoides plantations can help to estimate its wood volume,timber outturn and bark volume.【Method】The datasets including diameters of outside and inside bark and bark thickness at each stem segment were obtained through stem analysis of B. alnoides trees,and were randomly divided into two parts,about 75% for modeling and 25% for validating. Thirteen models were selected to fit with the above datasets,the least squaresmethod was used to estimate values of parameters,and significances（ deviation from zero） of these parameters were examined by student＇s t test at the 0. 05 level. Four statistics indexes such as bias（ B）,absolute bias（ AB）,mean square error（ MSE） and determination coefficient（ R2） were used to evaluate the goodness of fit for those models in which all parameters were significant. Student＇s paired t test was applied with the validation dataset to check the validity of these functions,and the models were discarded if the estimated values differed significantly from observed values. The presences of multicollinearity and heteroscedasticity were then detected for the remaining models,and the best bark models were ultimately selected for B. alnoides plantations.【Result】Among 13 models,Models（ 2） and（ 5） had at least one parameter without significant difference from zero at the 0. 05 level,and should not be considered in the further analysis. The fourstatistical criteria and their relative ranking values were calculated for the remaining 11 models. For modeling bark thickness at breast height,the performances of Model（ 3） and（ 4） were almost the same and were better than that of Model（ 1）; Model（ 7） did better than Model（ 6） for modeling bark thickness at any height; Model（ 8） showed better than Model（ 9） for fitting relative bark thickness; and compared to Models（ 10） and（ 12）,Models（ 11） and（ 13） exhibited better in simulating diameter inside bark. The result of student ＇s paired t test showed that Models（ 9）,（ 12） and（ 13） had significant difference between observed and estimated values and should be excluded. Among the remaining 8 models,only Model（ 4） showed weak multicollinearity,while no multicollinearity existed in the other models. The results of analysis on residual plots and White test indicated that no heteroskedasticity exist in Models（ 1）,（ 3） and（ 4）,however,the Models（ 6）,（ 7）,（ 8）,（ 10） and（ 11） had the heteroskedasticity,which were improved through variable transformation.【Conclusion】Models（ 3）,（ 7）,（ 8） and（ 11） were suitable for fitting bark thickness at breast height,bark thickness at any height,relative bark thickness and diameter inside bark,respectively. Due to the easily obtain of diameters at breast height,plantations ages and bark thickness at any height,these models are applicable in the practice of forest survey.Meanwhile,besides tree age,diameter at breast height and height,site factors also affect bark thickness,therefore,these factors should be considered so as to promote accuracy of the simulation on bark thickness for Betula alnoides.