生物量转换因子连续函数的拟合方法比较  

Comparison of fitting approaches with biomass expansion factor equations

作　　者：黄兴召[1] 王泽夫[1] 徐小牛[1] 

机构地区：[1]安徽农业大学林学与园林学院,安徽合肥230036

出　　处：《浙江农林大学学报》2017年第5期775-781,共7页Journal of Zhejiang A&F University

基　　金：国家重点研发计划资助项目(2016YFD0600304-03)

摘　　要：利用生物量转换因子连续函数估算森林生物量已成为普遍使用的方法,使用不同的拟合方法提升生物量转换因子连续函数的计算精度成为当前的研究热点之一。以安徽省和福建省2个区域的杉木Cunninghamia lanceolata人工林为研究对象,选择不同年龄序列的典型杉木人工林,分别在2个区域设置0.06 hm2的样地53块,得出每个样地杉木林分生物量、林分蓄积量和生物量转换因子(fBEF)均存在显著差异(P<0.01)。使用最小二乘法、非线性混合模型法和贝叶斯分层法分别拟合生物量转换因子连续函数,决定系数(R2)分别为0.643,0.802和0.804;平均偏差(dMD)分别为0.376,0.233和0.228。通过F检验比较3种方法的拟合效果,最小二乘法的拟合效果与非线性混合模型法和贝叶斯分层法之间有显著差异;非线性混合模型法的拟合效果和贝叶斯分层法之间无显著差异。估算林分生物量时,使用非线性混合模型和贝叶斯分层方法可以显著提升林分生物量的估算精度。Biomass equations for the biomass expansion factor（fBEF） have been widely applied for accurate stand biomass estimations.The question here is how to improve the fitting precision of these biomass expansion factor（fBEF） equations by using different methodologies.Stand biomass data were obtained from 53 permanent sample plots located in Cunninghamia lanceolata plantations of Anhui and Fujian Provinces across China.The least squares approach,the nonlinear mixed model approach,and the hierarchical Bayesian approach were applied to establish BEF equations so as to test the effect of regions.Split-plot design with regions of Anhui and Fujian Provence and sample plots as replications.Results showed significant differences between Fujian and Anhui Provinces for stand biomass,volume,and fBEFat different ages.The R^2 and mean deviation（dMD） values for the least squares approach was R^2=0.643,dMD=0.376;for the nonlinear mixed model approach was R^2=0.802,dMD=0.233;and for the hierarchical Bayesian approach was R^2=0.804,dMD=0.228.Also,there were highly significant differences in fitted results between the least squares and the nonlinear mixed model approaches,as well as between the least squares and the hierarchical Bayesian approaches（P0.01）.However,no significant differences were found between the nonlinear mixed model approach and the hierarchical Bayesian approach（P=0.547）.Thus,both the mixed model approach and the Bayesian hierarchical approach were effective methods for estimating stand biomass at the regional scale.

关 键 词：森林经理学 杉木 最小二乘法 非线性混合模型法 贝叶斯分层法 

分 类 号：S718.5[农业科学—林学]