Girth-volume based allometric model for biomass estimation of Magnolia champaca (L.) Baill. ex Pierre in Manipur, Northeast India

In this study, a best fit allometric equation was established for aboveground biomass estimation of Magnolia champaca (L.) Baill. ex Pierre using non-destruction method. Regression analysis was performed by assessing the statistical relationships of aboveground biomass (AGB) and dendrometric variables (e.g. DBH and tree height). The formulated equations were then subjected to statistics test to select the best fit model. Equations with the higher coefficient of determination (adjusted R 2 ), lower value of root mean square error (RMSE), sum of square error (SSE), mean absolute deviation (MAD) and Akaike’s information criterion (AIC) were found best fitted. The relative errors of the observed and predicted AGB of the selected best fit models were used to determine the accuracy of the equations. The best fit allometric equation developed for magnolia species was ln AGB = − 2.1868 + 0.9145 ( ln D 2 *H*WD) found as the most suitable with adjusted R 2 of 0.884, RMSE of 0.2558, MAD of 0.175141, AIC of − 88.7259, and having low relative error (− 1.25%) compared to other equations. The developed regression model is highly significant (p < 0.001) and can be applied as a species-specific equation to estimate the biomass of Magnolia champaca for northeast India.