The Brazil nut is considered one of the noblest trees of the Amazon biome and contains social, ecologic and economic importance to this region. The study of the spatial variance of the edaphic properties in native nut trees can direct future researches about more efficient samplings. The Geostatistics is the methodology utilized for this type of study, once that it considers the structural and random characteristics of a variable spatially distributed. This work sought to get a higher knowledge about the distribution of the nutrients in the soil, verifying the relationship with the occurrence of this species, to thereby provide subsidies to future forest management and maintenance/enlargement of the productivity in these areas. The soil samples were collected from 30 × 30 m on the line, in all of the lines in part of the study, totaling 60 samples. All of the points were georeferenced. The preparation of the samples for the sample preparation for the chemical analysis and the methods and calculations to determine the physicochemical variables studied were described by Nogueira and Souza (2005). The statistical and geostatistical analysis were conducted using the R computational environment, version 3.2.2. Most of the studied variables presented defined level. For the physical variables, there was predominance of the adjustment to the model of the gaussian variogram, follower by the spherical model. In the case of the chemical variables, there were two occurrences for each adjustment model (spherical, exponential and gaussian). The variables that best presented spatial relation with the occurrence of Brazil nut trees were the silt, clay, macroporosity, pH, phosphorus, zinc and copper.

This research estimated litter production and analyzed its relation to environmental variables such as maximum temperature, insolation, and rainfall. The study was conducted on a 300 × 300 m experiment as part of the project titled mapping of native Brazil nut stands and socio-environmental and economic characterization of Brazil nut production systems (MapCast), in the Tapajós National Forest (FLONA Tapajós). Every 30 days for one full year (August 2015 to July 2016), litterfall was collected and stored in a laboratory. After drying, the material was separated into leaves, wood, flowers and fruits, and miscellaneous and weighed. Statistical tests conducted were Shapiro-Wilk (5%), Principal coordinate analysis, t-test, Pearson's linear correlation, cross-correlation, and canonical redundancy analysis. Rainfall and temperature data were inferior and superior, respectively, to normal climate conditions in the region, and data for solar insolation had an abnormal pattern compared to normal climate conditions. Leaf production varied between 169.9 and 965.6 kg ha . The greatest leaf production was measured during the months with the lowest amount of rainfall and highest temperatures, and variation in leaf production and total litterfall was partially explained by temperature and insolation.