Abstract
Leaf area (<TEX>$A_0$</TEX>) and leaf biomass (<TEX>$M_0$</TEX>) estimation are significant prerequisites to studying tree physiological processes and modeling in the forest ecosystem. The objective of this study was to develop allometric models for estimating <TEX>$A_0$</TEX> and <TEX>$M_0$</TEX> of Swietenia mahagoni L. from different tree parameters such as DBH and tree height of mahogany plantations in the northeastern region of Bangladesh. A total of 850 healthy and well formed trees were selected randomly for sampling in the five study sites. Then, twenty two models were developed based on different statistical criteria that propose reliable and accurate models for estimating the <TEX>$A_0$</TEX> and <TEX>$M_0$</TEX> using non-destructive measurements. The results exposed that model iv and xv were selected on a single predictor of DBH and showed more statistically accuracy than other models. The selected models were also validated with an additional test data set on the basis of linear regression and t-test for mean difference between observed and predicted values. After that, a comparison between the best logarithmic and non-linear allometric model shows that the non-linear model produces systematic biases and underestimates <TEX>$A_0$</TEX> and <TEX>$M_0$</TEX> for larger trees. As a result, it showed that the bias-corrected logarithmic model iv and xv can be used to help quantify forest structure and functions, particularly valuable in future research for estimating <TEX>$A_0$</TEX> and <TEX>$M_0$</TEX> of S. mahagoni in this region.
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