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

• Published in: Environmental monitoring and assessment 2023-10, Vol.195 (10), p.1167-1167, Article 1167
• Main Authors: Martins, Thalita Silva, de Souza, Fernando Gomes, Campos, Milton César Costa, da Cunha, José Maurício, Brito, Wildson Benedito Mendes, de Lima, Alan Ferreira Leite, de Assis, Juliana Malta, Oliveira, Ivanildo Amorim, de Oliveira, Flávio Pereira, de Brito Filho, Elilson Gomes
• Format: Article
• Language: English
• Subjects: Agricultural land; Agriculture; Aluminum; Atmospheric Protection/Air Quality Control/Air Pollution; Calcium ions; Chemical indicators; Cupuacu; Earth and Environmental Science; Ecology; Ecotoxicology; Environment; Environmental changes; Environmental Management; Environmental monitoring; Forests; Geostatistics; Magnesium; Monitoring/Environmental Analysis; Multivariate analysis; Sampling; Soil; Soil analysis; Soil chemistry; Soil fertility; Soils; Spatial variability; Spatial variations; Statistical analysis; Surface boundary layer; Surface layers; Variability
• ISSN: 0167-6369; 1573-2959
• DOI: 10.1007/s10661-023-11735-3

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, Al 3+ , K + , Ca 2+ , Mg 2+ , 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.