Otimização da intensidade de amostragem em conglomerados para estimar volume de madeira em floresta amazônica

Abstract

Sample units (UAs) of reduced sizes, as well as in smaller quantities, are generally desirable in forest inventories, mainly because the number of obligators in the parcels is smaller, making the field work less onerous. This research explores resampling techniques for a set of clusters standardized by the Brazilian National Forest Inventory (NFI). The aim was twofold: to identify (1) the smallest cluster and (2) the smallest sample size that provides the same accuracy and precision as the original sample. Data from 22 0,80 ha clusters were installed in the National Forest of Bom Futuro, Brazil. Three products were considered: (1) volume of the trees with the diameter at breast height (DBH) ≥ 20 cm, (2) volume of the trees with DBH ≥ 50 cm, and (3) volume of the trees with DBH ≥ 50 cm, with stem quality 1 and 2. In Chapter 1, consecutive reductions from 0.80 to 0.08 ha were carried out in two directions (distal and proximal), giving rise to 20 scenarios. In Chapter 2, the sampling intensity with full-size (0.80 ha each) and small size (0.56 ha each) clusters was reduced from 22 to 4 clusters. The Monte Carlo method was used as the resampling technique needed to compute the accuracy and precision of the wood volume for every scenario. In Chapter 1, for the three products, findings revealed that 0.56-ha clusters reduced in the proximal direction can accurately and accurately estimate the variable of interest. In Chapter 2, also for the three products, all sample size reductions yielded less accuracy and precision than the original sample (22 SUs). This survey presents two main scientific contributions. The first is that, for the same sampling intensity, it is preferable to reduce the size of the AU rather than the number of AUs. This relation has been verified in many variable and sampling spaces, being reported in Cochran (1977). This research confirms, therefore, that same relation for the variable ‘wood volume’ in an Amazonian Forest remnant.The second scientific contribution suggests that the conglomerate installed in the Amazon could have its size reduced, for purposes of volumetry. The size reduction could even make the IFN less costly in financial terms.