Timber stock inventory in Amazon: simulations of cross-malt conglomerates sampling intensities

Abstract

A high diversity of tree species and a fact that only a few they have commercial value makes it difficult to establish appropriate sampling to characterize the timber stocks of tropical forests. In contrast, large inventories are needed to subsidize the identification, description, and bidding of public forests for concession. The aim of this study was to evaluate the effectiveness of the cross-malt conglomerate in different sampling intensities to estimate the commercial volume of tree species and their susceptible to exploitation in an Amazon forest under concession. For this, a sampling process in cross-malt conglomerates was simulated with intensities of 20 (0.5%), 40 (1%), 60 (1.5%), 80 (2%), and 100 (2,5%) sampling units from a forest census. The intensity of 100 sampling units was adequate to sampling the timber stock in natural forests, since it generated sampling errors close to or less than 10% established by law. The detection of species susceptible for exploration and the characterization of floristic composition of the tree stratum were other advantages observed. Thus, sampling by cross-malt conglomerates with first random stage is recommended for inventories of production forests in Amazon.