Tree volume modeling for forest types in the Atlantic Forest: generic and specific models

Abstract

National Forest Inventories are important primary data sources for large-scale forest resource surveys, in which volume estimates of sampled trees are essential for quantitative analysis. Volume prediction models in natural forests are scarce in Brazil due to legal restrictions for cutting trees, especially in the Atlantic Forest. This study aimed to fit volume models for the main forest types and timber species of the Atlantic Forest in Rio de Janeiro state, considering two hypotheses: (I) generic volume models provide greater generalizability of estimates; however, (II) they may reduce the accuracy of forest typeand species-specific predictions. Four linear models with logarithmic transformation of variables were evaluated to fit volume models for generic and specific datasets, which correspond to the main forest types and timber species. Goodness-of-fit statistics were calculated to compare the accuracy and efficiency of the models, and selected models were validated through leave-oneout cross-validation procedures. The estimates obtained by generic and specific models were compared by non-parametric hypothesis tests. Generic models showed similar predictions to the specific models for forest types and timber species, with similar potential for stem and total volume predictions. Therefore, generic models can be used for Atlantic Forests in Rio de Janeiro state, while specific models are recommended to obtain more detailed local estimates.

Form Factors and Volume Models for Estimating Tree Bole Volume of Mahogany at Community Forests in Central Java

“…was the most reliable model for estimating tree bole volumes of mahogany, especially when the D and H data were available. The reliability of Schumacher-Hall model (VDH3) was also reported by Cysneiros et al (2020) who developed tree volume models for the main forest types of the Atlantic Forest region.…”

“…To estimate the model parameters (b 0 , b 1 , and b 2 ), generalized linear and non-linear least square (GLS/GNLS) methods from the nlme package of R software 3.6.3 was used (Pinheiro, Bates, DebRoy, & Sarkar, 2020; R Core Team, 2020), which are more effective than the ordinary least square (OLS) methods in eliminating heteroscedasticity (nonconstant variance) of the model residuals. The performance of regression models was assessed using the goodness-of-fit statistics: Root Mean Squared Error (RMSE; Equation (4a)), Akaike's Information Criterion (AIC; Equation (4b)), and adjusted coefficient of determination (R 2 adj ; Equation (4c)) as follows (Burnham & Anderson, 2002;Cysneiros et al, 2020;Rawlings, Pantula, & Dickey, 1998) Two preferred models were selected: one that uses only the D as a predictor (Equation 3a to 3c) and another one that uses both D and H t as predictors (Equation 3d to 3f) for further analyses.…”

Development of Stem Volume Equation for Urban Trees of Abomey-Calavi in Southern Benin (West Africa)

“…A non-destructive method was used to measure all living tree species during the inventory process [24,32]. It is an alternative method for obtaining tree volume data without cutting down or cause physical damage to the trees [33,34].…”

“…At the base segment of the tree (from ground level to 0.3 m), the first three measurements were of the constant length of 0.1 m. In the following segment (0.3-1.3 m height), five measurements were made at 0.20 m interval. The upper section started at 1.30 m above the ground, here, the diameter outside bark was measured at 1 m interval up to the maximum height measurable using a ladder and climbing techniques [32]. These measurements were considered to describe tree profile in the lower section in which taper changes so rapidly low on the bole [36].…”

“…However, quantile-quantile plots was used to compare residuals to theoretical quartiles. Cross-validation approach was used as an additional criterion for validating the selected model [32,53,54]. All field data were randomly split into two subsets (calibrating set and validating set).…”