Sampling procedures for inventory of commercial volume tree species in Amazon Forest

Abstract

The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.

Spatial patterns and interactions of dominant tree species in an Amazon tropical forest

“…In these forests, the decline in associations for mature trees is expected due to local competition (Lan et al, 2012). Therefore, as a mature forest with high species diversity (Péllico Netto et al, 2017), the relationship between adult trees in the study area is less evident, confirming the results found.…”

“…Flona do Jamari was the first public forest in Brazil to adopt the governments's system of forest concession for lumber production through Sustainable Forest Management (Bauch, Sills, Rodríguez, Mcginley, & Cubbage, 2009). The said forest is characterized by large diversity and richness of species with commercial size which occupy the upper levels and clear dominance of some lumber species (Péllico Netto, Pelissari, Cysneiros, Bonazza, & Sanquetta, 2017).…”

“…The selected species are dominant on studying area, presenting the highest values of importance in the forest (Péllico Netto et al, 2017). These species are widely traded in Amazon region due to characteristics that suit the tropical timber market (IBAMA, 1997;Ferreira & Hopkins, 2004; Rivera-Martín, Peñuela-Mora, Rojas, & Jaramillo, 2013).…”

Evaluation of forest inventory processes in a forest under concession in the southwestern Brazilian Amazon

“…the enumeration of all trees in the target area, is not always feasible due to operational limitations (Scolforo and Mello 1993). Such survey processes involve a number of statistical techniques and methods used to estimate important forest parameters with well-delimited errors (Scolforo and Mello 1993;Sanquetta et al 2014;Péllico Netto et al 2017). In this scenario, a commendable forest inventory is reached through a good sampling process choice.…”

“…The Maltese cross unit technique, which is a case of the two-stage cluster sampling, introduced by Péllico Netto and Brena (1997), has become a cornerstone in Brazilian national forest inventory methodology (Sanquetta et al 2014). Studies focusing on the comparison of different sampling techniques are scarce (Ubialli et al 2009;Motz et al 2010;Dalla Corte et al 2013;Baraloto et al 2013;Péllico Netto et al 2017), yet they are paramount to the identification of techniques best suited for data exploitation in tropical forests, with far-reaching consequences for the efficacy of public policies and strategies for forest stock management, as well as for ecological research of species of interest (Péllico Netto et al 2017).…”