Spatial variability of chemical indicators of Amazon agricultural soils through geomultivariate statistics, Brazil.

This work focuses on evaluating the spatial variability of chemical attributes of soils under different agricultural use and native forest, indicating which are the possible indicator attributes of changes in environmental, through the use and management of the soil. The study was carried out in the southern region of the Amazonas state, in an Argissolo Vermelho-Amarelo (Ultisol). Sampling grids were established measuring: 90 m × 70 m with regular soil collection spacing of 10 m for the guarana and forest areas; 90 m × 56 m spaced at 10 m × 8 m for annatto area; and 54 m × 42 m with spacing between points of 6 m for the cupuaçu area, totaling 80 sampling points in each area, with soil samples collected at depths of 0.0-0.05; 0.05-0.10 m and 0.10-0.20 m. The following attributes were determined: pH, Al3+, K+, Ca2+, Mg2+, P, H + Al, CEC, V% and m%. Descriptive, geostatistical and multivariate statistical analyzes were performed. The results show that it is possible to state that the descriptive, geostatistical and multivariate statistical techniques were able to identify the difference between the spatial variability of the attributes according to each specific use of individual soils. The multivariate analysis made it possible to select the attributes that most contribute to the variability of these soils, and with that, it was found that the forest showed less spatial variability in the surface layer, with higher reach values by scaled semivariograms.

Pedoenvironmental indicators of soil in Western Amazonia, Brazil.

This study aimed to ascertain what soil attributes may be an indicator of natural and anthropic pedogenic changes in top grassland (TG), low grassland (LG), ecotone zone (EZ), and forest (F) in Western Amazonia. Twenty samples of the diagnostic horizons were collected from the studied pedoenvironments: TG (A 0.0-14 and Bi 0.30-0.66 m); LG (A 0.0-0.15 and Cg1 0.27-0.80 m); EZ (A 0.0-0.15 and Bi 0.32-0.50 m); and forest (F) (A1 0.0-0.15 and Bt1 0.67-0.10 m). Sand, silt, clay, particle density (PD),soil bulk density (BD),saturated soil hydraulic conductivity, calcium (Ca), magnesium (Mg), exchangeable aluminum (Al3+), potassium (K), sodium (Na), phosphorus (P), pH in water and KCl, and organic matter (OM) contents were calculated and submitted to variance analysis. LG is more related to OM and clay than SHC value. These same attributes characterized TG. EZ is highlighted by its higher values and relationship with Al and K. It was concluded that for TG, LG, EZ, and F top soil layers, 28% of natural and anthropic changes can be identified based on sand, clay, pH in KCl, and OM data; on the other hand, subsurface 23% of determinations can be attributed to pH in H2O, Al, Na, and sand.