2013•Zhongnan Linye Keji Daxue xuebaoRequires access

Characteristics of wood density variation of Pinus massomiana in Yongshun County, Hunan province

Zhang Li-yun

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Abstract

By combining standard investigation method,variance analysis and statistical hypothesis test,the wood density of Pinus massoniana plantation in Yongshun county,Hunan province was investigated from two aspects,i.e.,whole-tree and relative height.The suppressed trees had the largest wood density,following with the mean trees,while that of the dominant trees was the smallest.The stem wood densities with different height varied from 364.73 kg.m-3 to 516.39 kg.m-3,the variation coefficients of sample trees with different height changed from 1.96% to 13.36%,the average coefficient was 7.24%,and the relative height had not significant effects on the wood density.The absolute values of t-test on the height of 0.2 H to 0.8 H were bigger than the critical value,and that on the height of 0.1 H was-0.740,which was the smallest.When there is a need to estimate wood density in outdoor investigation,the trunk base wood density could be used to replace the wood density of the whole tree.The paired two sample t-test indicated that the density of DBH was not equal to whole tree wood density.Thus,a regression model was established to help us figure out the relationship between the density of DBH and wood density.Three different linear regression models were applied to find out the relationship between tree age and wood density.By adding DBH as the independent variable,the binary regression model used highly increases the accuracy of model simulation.

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What this paper is about

By combining standard investigation method,variance analysis and statistical hypothesis test,the wood density of Pinus massoniana plantation in Yongshun county,Hunan province was investigated from two aspects,i.e.,whole-tree and relative height.The suppressed trees had the largest wood density,following with the mean trees,while that of the dominant trees was the smallest.The stem wood densities with different height varied from 364.73 kg.m-3 to 516.39 kg.m-3,the variation coefficients of sample trees with different height changed from 1.96% to 13.36%,the average coefficient was 7.24%,and the relative height had not significant effects on the wood density.The absolute values of t-test on the height of 0.2 H to 0.8 H were bigger than the critical value,and that on the height of 0.1 H was-0.740,which was the smallest.When there is a need to estimate wood density in outdoor investigation,the trunk base wood density could be used to replace the wood density of the whole tree.The paired two sample t-test indicated that the density of DBH was not equal to whole tree wood density.Thus,a regression model was established to help us figure out the relationship between the density of DBH and wood density.Three different linear regression models were applied to find out the relationship between tree age and wood density.By adding DBH as the independent variable,the binary regression model used highly increases the accuracy of model simulation.

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Available abstract

By combining standard investigation method,variance analysis and statistical hypothesis test,the wood density of Pinus massoniana plantation in Yongshun county,Hunan province was investigated from two aspects,i.e.,whole-tree and relative height.The suppressed trees had the largest wood density,following with the mean trees,while that of the dominant trees was the smallest.The stem wood densities with different height varied from 364.73 kg.m-3 to 516.39 kg.m-3,the variation coefficients of sample trees with different height changed from 1.96% to 13.36%,the average coefficient was 7.24%,and the relative height had not significant effects on the wood density.The absolute values of t-test on the height of 0.2 H to 0.8 H were bigger than the critical value,and that on the height of 0.1 H was-0.740,which was the smallest.When there is a need to estimate wood density in outdoor investigation,the trunk base wood density could be used to replace the wood density of the whole tree.The paired two sample t-test indicated that the density of DBH was not equal to whole tree wood density.Thus,a regression model was established to help us figure out the relationship between the density of DBH and wood density.Three different linear regression models were applied to find out the relationship between tree age and wood density.By adding DBH as the independent variable,the binary regression model used highly increases the accuracy of model simulation.

Key concepts: Pinus massoniana, Mathematics, Linear regression, Statistics, Coefficient of variation, Forestry, Coefficient of determination, Regression analysis

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