ABSTRACT:The purpose of this study was to spatialize the chemical and physical attributes of the soil in an agroforestry system in Seropédica, Rio de Janeiro, Brazil. Thirtyone soil samples were collected from 0-10 cm, 10-20 cm, and 20-40 cm depths, and each sampling point was georeferenced. The pH (in H 2 O), potential acidity (H+Al), calcium (Ca ), sodium (Na + ), potassium (K + ), phosphorus (P), organic carbon (C), cation exchange capacity of the soil (T value), base saturation (V value), total clay, total sand, silt, and density of fine roots were measured. The software ArcGIS 10.2 was used to perform the semivariogram analysis and the fitting of the models, and spatial interpolation was performed using a first-order trend ordinary kriging process with spherical, exponential, and Gaussian spatial models. Based on the results, only the exponential and Gaussian models were fitted to the variables, except for the Mg 2+ and V value variables, which presented no spatial dependence, thus showing a pure nugget effect (PNE). Distribution maps were generated for the variables (except for those exhibiting PNE), which showed correlation between the variables pH and Al 3+, organic carbon and cations, phosphorus and total clay, and silt and sand. Overall, geostatistics could be applied to spatialize the chemical and physical attributes of the soil in the agroforestry system, except in the case of Mg 2+ and the V value. ), sódio (Na + ), potássio (K + ), fósforo (P), carbono orgânico (C), capacidade de troca catiônica do solo (Valor T), saturação por bases (Valor V), argila total, areia total, silte e densidade de raízes finas. O software ArcGIS 10.2 foi utilizado para fazer a análise semivariográfica e o ajuste dos modelos, e posteriormente, foi empregado a interpolação espacial através da Krigagem Ordinária de primeira ordem de três modelos espaciais, esférico, exponencial e gaussiano. De acordo com os resultados, apenas os modelos exponencial e gaussiano foram ajustados para as variáveis, exceto para as variáveis Mg 2+ e Valor V, pois não apresentaram dependência espacial, assim expressando efeito pepita puro (EPP). Foram gerados os mapas de distribuição para as variáveis (exceto para aquelas que exibiram EPP), onde ocorreu uma correlação entre as variáveis pH e Al 3+ , carbono orgânico e cátions, fósforo e argila total, e silte e areia. A geoestatística pode ser aplicada para espacializar os atributos químicos e físicos do solo no sistema agroflorestal, exceto no caso do Mg 2+ e Valor V. ESPACIALIZAÇÃO DOS ATRIBUTOS QUÍMICOS E FÍSICOS DO SOLO EM UM

Analog agroforestry system uses native tree species to improve soil conditions and the microclimate of degraded areas. This study aimed to assess the impact of analog agroforestry on physical, chemical, and biological soil attributes. We tested the hypothesis that some of these attributes can be used as indicators of soil quality improvement compared to a managed pasture area. Two experimental sites were selected, an analog agroforestry site and a pasture site. In October 2016 (end of the dry season), soil samples were collected from the 0–5 and 5–10 cm depths and the soil fauna community was sampled using pitfall traps. The analog agroforestry system led to increased total abundance, total richness, mean richness, evenness, and diversity of the soil fauna community as well as higher gravimetric soil moisture, sand content, pH, calcium, magnesium, and sum of exchangeable bases, which are good indicators of soil quality. Adults of Coleoptera, Diptera, Gastropoda, Hymenoptera, Isopoda, Lepidoptera, Poduromorpha, Symphypleona, Pseudoscorpionida, Lepidoptera and larvae of Coleoptera, Diptera, Lepidoptera, and Neuroptera were the most abundant taxonomic groups in the analog agroforestry system.

This study aimed to spatialize fractions of organic matter of soil in an agroforestry system (AFS) located in the Atlantic Forest in Brazil. Thirty-one soil samples were collected at depths of 0-10, 10-20 and 20-40 cm from georeferenced collection points. We determined total organic carbon (TOC), particulate carbon (COp), carbon associated with clay and silt (COam), carbon content in the fulvic acid fraction (C-FAF), humic acid fraction (C-HAF) and humin fraction (C-HUM). Semivariogram analysis and model adjustment were carried out using ArcGIS 10.2 software. Subsequently, spatial interpolation was performed using Ordinary Kriging. We observed spatial dependence for all variables except for TOC and COp at the 0-10 cm depth, which presented a pure nugget effect. It was possible to observe modifications in the distribution of humic substances in the study area. The results from this study are similar to those of other studies conducted in naive areas in the Atlantic Forest, demonstrating the benefits of using the agroforestry system. ESPACIALIZAÇÃO DAS FRAÇÕES DA MATÉRIA ORGÂNICA DO SOLO SOB UM SISTEMA AGROFLORESTAL, NA MATA ATLÂNTICA, BRASIL RESUMO: Este estudo teve como objetivo espacializar as frações da matéria orgânica do solo em um sistema agroflorestal (SAF) localizado na Mata Atlântica. Foram coletadas trinta e uma amostras de terra nas profundidades de 0-10, 10-20 e 20-40 cm, sendo cada ponto georeferenciado. Foram determinados os teores de carbono orgânico total (COT), carbono particulado (COp), carbono associado a argila e silte (COam), teor de carbono na fração de ácido fúlvico (C-FAF), fração de ácido húmico (C-FAH) e fração de humina (C-HUM). A análise dos semivariogramas e o ajuste do modelo foram realizados utilizando o software ArcGIS 10.2. Posteriormente foi realizada a interpolação espacial através de Krigagem Ordinária. Foi observada dependência espacial para todas as variáveis, com exceção do COT e COp na profundidade de 0-10 cm, visto que apresentaram efeito pepita puro. Foram verificadas modificações na distribuição das substâncias húmicas na área de estudo. Os resultados deste estudo são semelhantes aos de outros realizados em áreas de Mata Atlântica, demonstrando os benefícios do uso do sistema agroflorestal.

Geostatistics is a tool that can be used to produce maps with the distribution of nutrients essential for the development of plants. Therefore, the present study aimed to analyze the spatial variation in chemical attributes of soils under oil palm cultivation in agroforestry systems in the eastern Brazilian Amazon, and their spatial dependence pattern. Sixty spatially standardized and georeferenced soil samples were collected at each of three sampling sites (DU1, DU2, and DU3) at 0-20 cm depth. Evaluated soil chemical attributes were pH, Al3+, H+Al, K+, Ca2+, Mg2+, cation exchange capacity (CEC), P, and organic matter (OM). The spatial dependence of these variables was evaluated with a semivariogram analysis, adjusting three theoretical models (spherical, exponential, and Gaussian). Following analysis for spatial dependence structure, ordinary kriging was used to estimate the value of each attribute at non-sampled sites. Spatial correlation among the attributes was tested using cokriging of data spatial distribution. All variables showed spatial dependence, with the exception of pH, in one sampling site (DU3). Highest K+, Ca2+, Mg2+, and OM levels were found in the lower region of two sampling sites (DU1 and DU2). Highest levels of Al3+ and H+Al levels were observed in the lower region of sampling site DU3. Some variables were correlated, therefore cokriging proved to be efficient in estimating primary variables as a function of secondary variables. The evaluated attributes showed spatial dependence and correlation, indicating that geostatistics may contribute to the effective management of agroforestry systems with oil palm in the Amazon region.

No abstract