111 resultados para Spatial Density Dependence
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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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.
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Density of binary solutions and combinations of sucrose, glucose, fructose, citric acid, malic acid, pectin, and inorganic salts were measured with an oscillating tube density meter in the temperature range from 10degrees to 60degreesC, at varying concentrations. Density can be predicted with accuracy better than 5 x 10(-5) g cm(-3) using predictive equations obtained by fitting the experimental data. Available literature values agreed well with experimental data. Relations for the excess molar volume of these solutions were derived in terms of mole fraction and temperature. A thermodynamic model for the volumetric analysis of multicomponent aqueous solutions containing electrolyte and non-electrolyte compounds was also proposed. These models can be used for prediction of density of liquid food systems, specially fruit juices and beverages, based on composition and temperature, with high accuracy and without elaborate experimental work.
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Half-fresh apples were immersed in sucrose solution (50% w/w, 27 degrees C) during different times of exposition (2, 4, and 8 h). Then each fruit was sliced from the transversal exposed surface. Density, water, and sugar content were determined for each slice. A mathematical model was fitted to experimental data of water and sucrose content considering the global flux and the tissue shrinkage. By numerical analysis, the binary effective diffusion coefficients as a function of concentration were calculated, using material coordinates and integrating simultaneously two differential equations (for water and sucrose). The coefficients obtained are one or even two orders of magnitude lower than the ones for pure solutions and present an unusual concentration dependence. This comparison shows the influence of the tissue resistance to the diffusion.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Water infiltration into soil is one of the basic factors for estimating irrigation intensity according to the plants' requirements; this is aimed at avoiding problems of surface run-off and degradation. The purpose of the present investigation was to determine the spatial variation of infiltration and its relationship to some physical properties of soil by means of geostatistical techniques in Typic Plinthaquult soils having average texture and flat relief. A 113 point mesh was designned, having a regular distance of 10 m between points, samples being taken from 0 to 0.20 meters depth. Sand, silt and clay content, bulk density, macroporosity, microporosity and total porosity were determined. Infiltration tests were carried out in the field by means of a 15 cm diameter ring. Descriptive statistics and geostatistics were used for analysing the data. Infiltration, silt and microporosity data did not fit a normal distribution curve. Infiltration had high variability, having an average 36.03 mm h(-1). Total porosity was 56.73%, this being the only property that did not show spatial dependency. The smallest ranges were observed for bulk density, macroporosity and microporosity, having values of less than 40 m. The smallest degrees of spatial dependence were observed for infiltration, silt and clay, evidence also being shown of the influence of silt and clay on infiltration rate. Contour maps were constructed; fitting them to the semivariogram models, together with studying the correlations, led to establishing relationships between the properties.
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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.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The bubble crab Dotilla fenestrata forms very dense populations on the sand flats of the eastern coast of Inhaca Island, Mozambique, making it an interesting biological model to examine spatial distribution patterns and test the relative efficiency of common sampling methods. Due to its apparent ecological importance within the sandy intertidal community, understanding the factors ruling the dynamics of Dotilla populations is also a key issue. In this study, different techniques of estimating crab density are described, and the trends of spatial distribution of the different population categories are shown. The studied populations are arranged in discrete patches located at the well-drained crests of nearly parallel mega sand ripples. For a given sample size, there was an obvious gain in precision by using a stratified random sampling technique, considering discrete patches as strata, compared to the simple random design. Density average and variance differed considerably among patches since juveniles and ovigerous females were found clumped, with higher densities at the lower and upper shore levels, respectively. Burrow counting was found to be an adequate method for large-scale sampling, although consistently underestimating actual crab density by nearly half. Regression analyses suggested that crabs smaller than 2.9 mm carapace width tend to be undetected in visual burrow counts. A visual survey of sampling plots over several patches of a large Dotilla population showed that crab density varied in an interesting oscillating pattern, apparently following the topography of the sand flat. Patches extending to the lower shore contained higher densities than those mostly covering the higher shore. Within-patch density variability also pointed to the same trend, but the density increment towards the lowest shore level varied greatly among the patches compared.
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The variation of soil textural characteristics is a function of the relief and parent materials. The objective of this work was to study soil texture spatial variability from different parent material in Pereira Barreto, SP. An area of 530.67 hectares was mapped through the use of Global Positioning System receivers and obtaining of Digital Elevation Models. A set of 201 soil samples was collected from every seven hectares, at three depths: 0 - 0.25 m; 0.25 - 0.50 m; and 0.80 - 1.00 m. The amounts of sand, silt and clay were obtained by the pipette method and analyzed by both descriptive statistics and geostatistics. Soil textures varied as a function of parent materials and topography.