Biomass models for three species with different growth forms and geographic distribution in the Brazilian Atlantic forest

Allometric models embedding independent variables such as diameter at breast height (d) and total height (h) are useful tools to predict the biomass of individual trees. Models for tropical forests are often constructed based on datasets composed of species with different morphological features and architectural models. It is reasonable to expect, however, that species-specific models may reduce uncertainties in biomass predictions, especially for palms, tree ferns, and trees with peculiar morphological features, such as stilt roots and hollow trunks. In this sense, three species with wide geographical distribution in the Brazilian Atlantic Forest were sampled, namely Euterpe edulis Mart., Cyathea deIgadii Sternb., and Cecropia glaziovii Snethl., with the aim to (i) quantify their aboveground biomass (AGB), (ii) evaluate the AGB distribution in different plant compartments, (iii) fit species-specific models for predicting AGB at the individual level, and (iv) assess the performance of specific and generic models available in the literature to predict the AGB of individuals of these species. The compartment stem represented, on average, similar to 74% of the total AGB of E. edulis individuals; in turn, the caudex compartment of C. delgadii represented, on average, similar to 87% of the total AGB, while the trunk compartment of C. glaziovii represented, on average, similar to 74%. Among the fitted models, the power model AGB = beta(0) x d(beta 1) x h(beta 2) + epsilon showed the best performance for E. edulis and C. delgadii. In turn, the asymptotic logistic model AGB - alpha/ [1 + exp(beta(0) + beta(1) x d(c) + beta(2) x h)] + epsilon, where d(c) is the diameter above the upper stilt root, presented the best performance for C. glaziovii. The variable h appeared as the most important predictor of AGB of E. edulis and C. delgadii; in contrast, the stem and caudex mean basic specific gravities were not suitable predictors. The fitted species-specific models outperformed the specific and generic models selected from the literature. They may, therefore, contribute to the reduction of uncertainties in AGB estimates. In addition, the results support evidence that specific models may be necessary for species with different growth forms and (or) peculiar morphological features, especially those with great abundance and wide geographic distribution.