With regards to sampling sufficiency, it is known that larger sampling sizes increase the probability of obtaining the same inferential conclusions in new samples within the same population (PILLAR, 1999).
Results based on the distribution of sample means are traditionally used to determine sampling sizes (ISRAEL, 2012) according to procedures indicated by the 'Pan American Standards Commission' (COPANT, 1974).
Determining accurate confidence levels and ideal sampling sizes could be performed based on empiric distribution of population parameters of interest, as verified in Pillar (1998, 1999).
Therefore, the versatility and the precision of the Bootstrap method (EDWARDS et al., 2011) enables the evaluation of sampling sufficiency to infer anatomical characteristics of forest species, since these sampling sizes still have not been clearly defined.
Determining accurate sampling sizes is essential because an insufficient number of measurements can cause results that do not significantly represent the real anatomical characteristics of a population.