Abstract:

Based on the mensuration data of diameter at breast height(DBH)and tree height from 25 Plots of Cunninghamia lanceolata and 25 plots of Eucalyptus robusta in the annual monitoring and evaluation of national forest resources of Guangxi Zhuang Autonomous Region,the basic model with the highest simulation accuracy was selected from seven common tree height-DBH curve models,then stand dominant height and climate data were introduced to build generalized nonlinear models.The 10-fold cross-validation method was applied to test the models,and the estimation error of one-dimensional volume formula was evaluated.The results showed that:1)Among the traditional tree height-DBH curve models,Chapman-Richards model was the basic model with the highest accuracy;2)Compared with the basic model,the generalized nonlinear tree height-DBH model with stand dominant height and climate data had higher fitting accuracy.The determination coefficient(R²),mean prediction errors(MPE)and mean percent standard errors(MPSE)of Cunninghamia lanceolata model were 0.7976,0.58% and 13.91%,respectively,and those of Eucalyptus robusta model were 0.7207,0.62% and 11.58%,respectively;3)The volume calculated by the one-dimensional volume formula was quite different from the measured volume,especially the Eucalyptus robusta reach -13.51%,which exceeded the scope of forestry industry standards.It was worth noting that the relative error calculated by the binary volume formula and the generalized nonlinear tree height-DBH model is not above 0.5%.The generalized nonlinear tree height-DBH model of Cunninghamia lanceolata and Eucalyptus robusta can be well applied to practical production.

Key words: dominant height, Cunninghamia lanceolata, Eucalyptus robusta, generalized nonlinear model, tree height-DBH model