Comparison among allometric models for tree biomass estimation using non-destructive trees’ data

The non-destructive method—using allometric models—of forest biomass estimation is one of the most effective and efficient approaches, however, there is an ambiguity to choose a particular type of model for predicting biomass. The study aimed to compare 11 different allometric models generally employing in Nepal using empirical data of 4,942 individual standing trees of 36 species from 134 sample plots considering 20 environmental variables from five community forests belonging in two ecological regions. Akaike Information Criterion (AIC), coefficient of determination (R 2 ), and root mean square error (RMSE) of each model was estimated and compared. The biomass density predicted by different models differed significantly ( p