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Indian Black Earths (IBEs) are distributed throughout the Amazon. They are characterized by their high chemical fertility and agricultural potential. IBEs have high organic carbon, favouring the improvement of soil structure. This work aimed to evaluate the aggregates and organic carbon (OC) spatial variability in different IBEs in southern Amazonas. We evaluated the organic carbon spatial variability, mean weight diameter (MWD), soil bulk density (Ïb) and aggregate classes under three uses of soil: pasture, cocoa, and coffee. We collected 528 soil samples in a point grid according to its use at two depths: 0.0-0.05 m and 0.10-0.20 m. Results were subjected to variance, descriptive, and geostatistical analyses. We concluded that the soil use influenced the IBEs physical attributes soil behavior, concentrating the higher values of CO, aggregates > 2.00 mm, and MWD at 0.0-0.05 m in relation to Ïb and aggregates < 2.00 mm where the higher values were the ones at 0.10-0.20 m. Aggregates< 2.00 mm (0.10-0.20 m) and OC (0.0-0.05 m) did not show spatial dependence, while the class of aggregates > 2.00 mm was the only attribute which represented to be a natural characteristic of the soil, with a strong spatial dependence, independently the land use and depth. There was no spatial relationship between the attributes studied and the geomorphic diversity.

Natural grasslands with savannah-like characteristics associated to forest mosaics are found within Southern and Eastern Amazonas, Western Rondônia and Northern Roraima, being conditioned to local edaphic factors. The aim of this study was to assess both physical and geospatial attributes of an Cambisol under natural grasslands and an Ultisol under a forest fragment in Humaitá - AM, Brazil. In each area, we established a sampling grid in the dimensions of 70 × 70 m, with regular sampling spacing of 10 m and three collection depths: 0.0-0.05, 0.05-0.10 and 0.10-0.20 m, totaling 192 sampling points. Macroporosity (MaP), microporosity (MiP), bulk density (Ds) and total porosity (TP) were determined by soil samples with preserved structure, using a volumetric ring. Soil resistance to penetration (SRP) was measured by an automatic penetrometer after being subjected to a 0.006 MPa tension. Data were submitted to descriptive statistics and geostatistics analysis. The soil under natural grasslands showed values considered critical of Ds, SRP, MaP at all evaluated depths, with significant values at 0.10-0.20 m layer of 1.54 kg dm-3; 2.08 MPa and 0.05 m3 m-3, respectively. Ultisol under the forest fragments showed higher range values and consequently greater geospatial continuity due to the assessed physical attributes, since this soil has a greater stability of its physical structure. Based on the physical properties of the soil, structural function ineffectiveness of the Ultisol is a key factor for the occurrence of grassland in this region.

Studies on the spatial behavior of soil attributes in the Amazon region are still very incipient. In this sense, the objective of this work was to evaluate the chemical attributes through multivariate techniques and geoestatistics in the area with agroforestry and sugarcane in Humaitá, AM, Brazil. The study was carried out in a farm in Humaitá city, Amazonas State. The studied area was divided into 70.00 m x 70.00 mmeshes with a regular spacing of 10 m, totaling 64 points and then, soil samples were collected at 0.0-0.2 m and 0.4-0.6 m depths. We performed chemical analyses of the attributes of soil. Then, it was applied descriptive statistics, multivariate and geostatistics. In conclusion, our findings suggest that for most of the chemical attributes was observed spatial dependence in both areas, with DSD varying from weak to moderate, with prevalence of the weak one. The multivariate analysis was efficient in the selection of chemical soil attributes that best represented the agroforestry environments and sugarcane. The results of this study will serve as a basis for further studies on these environments and other systems within the region; moreover serving as a basis for agricultural planning aiming a better environmental sustainability.