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Although stand age affects biomass partitioning and allometric equations, the size of these effects and whether it is worth incorporating stand age into allometric equations, requires further attention. We sampled a total of 90 trees for 10 Chinese fir (Cunninghamia lanceolata) plantations at seven stand age classes to obtain the data of tree component biomass using destructive harvesting. A multilevel modeling approach was applied to examine how stand age effects differ among tree components and predictor variables (diameter at breast height, DBH and tree height, H). Age class-specific allometric equations and the best fitting generalized equation that included stand age as a complementary variable were developed for each tree component. Large differences in both the intercept and slope for different stand age classes indicated that stand age affected allometric models. Branch and leaves were more sensitive to the environment and were the tree components most affected by stand age. Age class-specific allometric equations fitted well (R2 > 0.65, p < 0.001) using DBH and the combined form DBH2H as predictor variables. Including stand age as a complementary variable improved the fit of generalized allometric equations. Stem, aboveground and total tree biomass predicted by the multilevel model and generalized equation were comparable to the observed data. However, the multilevel model and generalized equations had a relatively low predictive capacity for branch, leaf and root biomass. These results could improve our capacity to evaluate carbon sequestration and other ecosystem functions in plantations. [ABSTRACT FROM AUTHOR]

Chinese subtropical forests contain a diversity of tree species and exhibit a high carbon (C) sequestration capacity, but biomass and C stock assessments in subtropical secondary forests remain uncertain because of a limited availability of allometric equations and an uncertain applicability of existing allometric equations that have not been tested for these forests. We developed allometric equations for important coniferous ( Pinus massoniana), deciduous broadleaved ( Alniphyllum fortunei, Choerospondias axillaris, Liquidambar formosana) and evergreen broadleaved ( Cyclobalanopsis glauca, Litsea rotundifolia, Schima superba) species. A total of 70 trees (10 trees for each species) with diameters at breast height ( D) ranging from 2.6 to 50.9 cm were destructively harvested and dissected into tree components (stem, branch, leaf and coarse root). Species-specific equations using D alone as the predictor variable fitted the data well ( p < 0.0053 and R > 0.72) for each tree component. Including height ( H) in the form of D H only improved the regression fit for A. fortunei and L. rotundifolia. The relationships of branch, leaf and root biomass against D varied among tree species. General equations for functional groups and all species combined showed comparable bias for stem, aboveground and total tree biomass to species-specific equations. We recommend the general equations of multiple species to estimate forest biomass at regional scales and also to estimate stem, aboveground and total tree biomass for each species when species-specific allometric equations are not available at a given site. For branch, leaf and root biomass, species-specific equations are preferred, even though this requires biomass data for additional tree species. [ABSTRACT FROM AUTHOR]