Spatial variability of forage yield and soil physical attributes of a Brachiaria decumbens pasture in the Brazilian Cerrado

The objective of this study was to analyze variability, linear and spatial correlations of forage dry mass yield (FDM) and dry matter percentage (DM%) of Brachiaria decumbens with the bulk density (BD), gravimetric (GM) and volumetric (VM) moisture, mechanical resistance to penetration (RP) and organic matter content (OM), at depths 1 (0-0.10 m) and 2 (0.10-0.20 m), in a Red Latosol (Oxisol), in order to select an indicator of soil physical quality and identify possible causes of pasture degradation. The geostatistical grid was installed to collect soil and plant data, with 121 sampling points, over an area of 2.56 ha. The linear correlation between FDM × DM% and FDM × BD2 was low, but highly significant. Spatial correlations varied inversely and positively, respectively. Except for DM% and BD, at both depths, the other attributes showed average to high variability, indicating a heterogeneous environment. Thus, geostatistics emerges as an important tool in understanding the interactions in pasture ecosystems, in order to minimize possible causes of degradation and indicate better alternatives for soil-plant-animal management. The decrease in FDM and increased BD1 are indicators of physical degradation (compaction) of Red Latosol (Oxisol), particularly in the places with the highest concentration of animals and excessive trampling, in Cerrado conditions, in the municipality of Selvíria, Mato Grosso do Sul State, Brazil.

Spatial variability of the physical and mineralogical properties of the soil from the areas with variation in landscape shapes

Este trabalho teve como objetivo avaliar a influência das formas do relevo na variabilidade espacial de atributos físicos e suas relações com a mineralogia da argila de um Latossolo Vermelho eutroférrico, utilizando a técnica da geoestatística. Os solos foram amostrados nos pontos de cruzamento de uma malha, com intervalos regulares de 10 m, nas profundidades de 0,0-0,2 m, 0,2-0,4 m e 0,4-0,6 m para os atributos físicos e 0,6-0,8 m para os atributos mineralógicos. Os valores médios para a densidade do solo e resistência do solo à penetração são maiores no compartimento I onde a relação Ct/Ct+Gb é relativamente maior, indicando a presença de maior teor de caulinita. No compartimento II a condutividade hidráulica e a macroporsidade são maiores, influenciados provavelmente pelo predomínio da gibbsita. Portanto, conclui-se que a identificação das pedoformas é muito eficiente para compreender a variabilidade espacial de propriedades do solo. Sendo que, as variações na forma da paisagem promovem variabilidade espacial diferenciada das propriedades físicas e mineralógicas do solo.

Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

A emissão de CO2 do solo apresenta alta variabilidade espacial, devido à grande dependência espacial observada nas propriedades do solo que a influenciam. Neste estudo, objetivou-se: caracterizar e relacionar a variabilidade espacial da respiração do solo e propriedades relacionadas; avaliar a acurácia dos resultados fornecidos pelo método da krigagem ordinária e simulação sequencial gaussiana; e avaliar a incerteza na predição da variabilidade espacial da emissão de CO2 do solo e demais propriedades utilizando a simulação sequencial gaussiana. O estudo foi conduzido em uma malha amostral irregular com 141 pontos, instalada sobre a cultura de cana-de-açúcar. Nesses pontos foram avaliados a emissão de CO2 do solo, a temperatura do solo, a porosidade livre de água, o teor de matéria orgânica e a densidade do solo. Todas as variáveis apresentaram estrutura de dependência espacial. A emissão de CO2 do solo mostrou correlações positivas com a matéria orgânica (r = 0,25, p < 0,05) e a porosidade livre de água (r = 0,27, p <0,01) e negativa com a densidade do solo (r = -0,41, p < 0,01). No entanto, quando os valores estimados espacialmente (N=8833) são considerados, a porosidade livre de água passa a ser a principal variável responsável pelas características espaciais da respiração do solo, apresentando correlação de 0,26 (p < 0,01). As simulações individuais propiciaram, para todas as variáveis analisadas, melhor reprodução das funções de distribuição acumuladas e dos variogramas, em comparação à krigagem e estimativa E-type. As maiores incertezas na predição da emissão de CO2 estiveram associadas às regiões da área estudada com maiores valores observados e estimados, produzindo estimativas, ao longo do período estudado, de 0,18 a 1,85 t CO2 ha-1, dependendo dos diferentes cenários simulados. O conhecimento das incertezas gerado por meio dos diferentes cenários de estimativa pode ser incluído em inventários de gases do efeito estufa, resultando em estimativas mais conservadoras do potencial de emissão desses gases.

Prediction and spatial variability of soil dynamic properties in sugar cane fields of São Paulo State Brazil

The objective of this work was to model and diagnose the spatial variability of soil load support capacity (SLSC) in sugar cane crop fields, as well as to evaluate the management impact on São Paulo State soil structure. The investigated variables were: pressure preconsolidation (sigma(p)), apparent cohesion () and internal friction angle (). The conclusions from the results were that the models and spatial dependence maps constitute important tools in the prediction and location of the mechanical internal strength of soils cultivated with sugar cane. They will help future soil management decisions so that soil structure sustainability will not be compromised.

Short-term temporal changes in the spatial variability model of CO2 emissions from a Brazilian bare soil

In this work, the spatial variability model of CO2 emissions and soil properties of a Brazilian bare soil were investigated. Carbon dioxide emissions were measured on three different days at contrasted soil temperature and soil moisture conditions, and soil properties were investigated at the same points where emissions were measured. One spatial variability model of soil CO2 emissions was found for each measurement day, and these models are similar to the ones of soil properties studied in an area of 100 x 100 m. (C) 2000 Elsevier B.V. Ltd. All rights reserved.

Spatial variability of soil attributes and sugarcane yield in relation to topographic location

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial and temporal variability of soil CO2 emission in a sugarcane area under green and slash-and-burn managements

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The use of landforms to predict the variability of soil and orange attributes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial and temporal variability in soil CO2-C emissions and relation to soil temperature at King George Island, maritime Antarctica

Few studies have examined the effects of temperature on spatial and temporal trends in soil CO2-C emissions in Antarctica. In this work, we present in situ measurements of CO2-C emissions and assess their relation with soil temperature, using dynamic chambers. We found an exponential relation between CO2 emissions and soil temperature, with the value of Q10 being close to 2.1. Mean emission rates were as low as 0.026 and 0.072 g of CO2-C m-2 h-1 for bare soil and soil covered with moss, respectively, and as high as 0.162 g of CO2-C m-2 h-1 for soil covered with grass, Deschampsia antarctica Desv. (Poaceae). A spatial variability analysis conducted using a 60-point grid, for an area with mosses (Sannionia uncianata) and D. antarctica, yielded a spherical semivariogram model for CO2-C emissions with a range of 1 m. The results suggest that soil temperature is a controlling factor on temporal variations in soil CO2-C emissions, although spatial variations appear to be more strongly related to the distribution of vegetation types. © 2010 Elsevier B.V. and NIPR.

Quantification of uncertainties associated with space-time estimates of short-term soil CO2 emissions in a sugar cane area

The characterization of soil CO2 emissions (FCO2) is important for the study of the global carbon cycle. This phenomenon presents great variability in space and time, a characteristic that makes attempts at modeling and forecasting FCO2 challenging. Although spatial estimates have been performed in several studies, the association of these estimates with the uncertainties inherent in the estimation procedures is not considered. This study aimed to evaluate the local, spatial, local-temporal and spatial-temporal uncertainties of short-term FCO2 after harvest period in a sugar cane area. The FCO2 was featured in a sampling grid of 60m×60m containing 127 points with minimum separation distances from 0.5 to 10m between points. The FCO2 was evaluated 7 times within a total period of 10 days. The variability of FCO2 was described by descriptive statistics and variogram modeling. To calculate the uncertainties, 300 realizations made by sequential Gaussian simulation were considered. Local uncertainties were evaluated using the probability values exceeding certain critical thresholds, while the spatial uncertainties considering the probability of regions with high probability values together exceed the adopted limits. Using the daily uncertainties, the local-spatial and spatial-temporal uncertainty (Ftemp) was obtained. The daily and mean emissions showed a variability structure that was described by spherical and Gaussian models. The differences between the daily maps were related to variations in the magnitude of FCO2, covering mean values ranging from 1.28±0.11μmolm-2s-1 (F197) to 1.82±0.07μmolm-2s-1 (F195). The Ftemp showed low spatial uncertainty coupled with high local uncertainty estimates. The average emission showed great spatial uncertainty of the simulated values. The evaluation of uncertainties associated with the knowledge of temporal and spatial variability is an important tool for understanding many phenomena over time, such as the quantification of greenhouse gases or the identification of areas with high crop productivity. © 2013 Elsevier B.V.

Iron oxides as proxies for characterizing anisotropy in soil CO2 emission in sugarcane areas under green harvest

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Magnetic susceptibility and diffuse reflectance spectroscopy to characterize the spatial variability of soil properties in a Brazilian Haplustalf

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial variability structure of soil CO2 emission and soil attributes in a sugarcane area

Soil CO2 emission (F-CO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere. F-CO2 varies in time and space depending on environmental conditions, including the management of the agricultural area. The aim of this study was to investigate the spatial variability structure of F-CO2 and soil attributes in a mechanically harvested sugarcane area (green harvest) using fractal dimension (D-F) derived from isotropic variograms at different scales (fractograms). F-CO2 showed an overall average of 1.51 mu mol CO2 m(-2) s(-1) and correlated significantly (P < 0.05) with soil physical attributes, such as soil bulk density, air-filled pore space, macroporosity and microporosity. Topologically significant DF values were obtained from the characterization of F-CO2 at medium and large scales (above 20 m), with values of 2.92 and 2.90, respectively. The variations in D-F with scales indicate that the spatial variability structure of F-CO2 was similar to that observed for soil temperature and total pore volume and was the inverse of that observed for other soil attributes, such as soil moisture, soil bulk density, microporosity, air-filled pore space, silt and clay content, pH, available phosphorus and the sum of bases. Thus, the spatial variability structure of F-CO2 presented a significant relationship with the spatial variability structure for most soil attributes, indicating the possibility of using fractograms as a tool to better describe the spatial dependence of variables along the scale. (C) 2014 Elsevier B.V. All rights reserved.

Spatial variability of soil fertility and its relationship with seed physiological potential in a soybean production area

The correlation of soil fertility x seed physiological potential is very important in the area of seed technology but results published with that theme are contradictory. For this reason, this study to evaluate the correlations between soil chemical properties and physiological potential of soybean seeds. On georeferenced points, both soil and seeds were sampled for analysis of soil fertility and seed physiological potential. Data were assessed by the following analyses: descriptive statistics; Pearson's linear correlation; and geostatistics. The adjusted parameters of the semivariograms were used to produce maps of spatial distribution for each variable. Organic matter content, Mn and Cu showed significant effects on seed germination. Most variables studied presented moderate to high spatial dependence. Germination and accelerated aging of seeds, and P, Ca, Mg, Mn, Cu and Zn showed a better fit to spherical semivariogram: organic matter, pH and K had a better fit to Gaussian model; and V% and Fe showed a better fit to the linear model. The values for range of spatial dependence varied from 89.9 m for P until 651.4 m for Fe. These values should be considered when new samples are collected for assessing soil fertility in this production area.

Mapping variability of soil water content and flux across 1¿1000 m scales using the actively heated fiber optic method

The Actively Heated Fiber Optic (AHFO) method is shown to be capable of measuring soil water content several times per hour at 0.25 m spacing along cables of multiple kilometers in length. AHFO is based on distributed temperature sensing (DTS) observation of the heating and cooling of a buried fiber-optic cable resulting from an electrical impulse of energy delivered from the steel cable jacket. The results presented were collected from 750 m of cable buried in three 240 m colocated transects at 30, 60, and 90 cm depths in an agricultural field under center pivot irrigation. The calibration curve relating soil water content to the thermal response of the soil to a heat pulse of 10 W m−1 for 1 min duration was developed in the lab. This calibration was found applicable to the 30 and 60 cm depth cables, while the 90 cm depth cable illustrated the challenges presented by soil heterogeneity for this technique. This method was used to map with high resolution the variability of soil water content and fluxes induced by the nonuniformity of water application at the surface.