2017, VOLUME 4 ISSUE 2Pages: 274-285
Assessment of allometric models for leaf area index estimation of Tectona grandis
R. K. Chaturvedi*, Shivam Singh, Hema Singh and A. S. Raghubanshi
*Community Ecology and Conservation Group, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Mengla, Yunnan 666303, China
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We developed allometric models for accurate estimation of Tectona grandis (teak)leaf area index (LAI), for different stem diameter-classes (D-classes). In this study, we harvested teak trees in the tropical dry region of India in the ten stem diameter classes and measured LAI, and developed regression models for the non-destructive estimation of LAI with the help of wood density (ρ), diameter at breast height (D) and plant height (H). Models used for the prediction of biomass of tree components were of the form, linear, logistic, Gompertz and Chapman. Among the four models, non-linear models were more efficient compared to the linear model. We observed more than 60% variability in the LAI, explained by non-linear regression models. The models including ρ and D had greater R2 and lower standard error of estimate. Our study detected logistic models more appropriate for broad diameter range and Gompertz models for small D-classes. The regression models developed in our study can be applied separately for the ten D-classes, and this could minimize the error occurring during indirect estimation of teak LAI.
between the log transformed values of ρD2 and the log transformed values of LAI
estimated by harvest method for teak trees. For regression models, see Table 2.
ρ, wood specific gravity (g cm-3); D, stem diameter (cm); H, height (m). n = 100.