Physical properties and organic carbon content of a Rhodic Kandiudox fertilized with pig slurry and poultry litter

The impact of pig slurry and poultry litter fertilization on soils depends on the conditions of use and the amounts applied. This study evaluated the effect of organic fertilizers after different application periods in different areas on the physical properties and organic carbon contents of a Rhodic Kandiudox, in Concordia, Santa Catarina, in Southern Brazil. The treatments consisted of different land uses and periods of pig and poultry litter fertilization: silage maize (M7 years), silage maize (M20 years), annual ryegrass pasture (P3 years), annual ryegrass pasture (P15 years), perennial pasture (PP20 years), yerba mate tea (Mt20 years), native forest (NF), and native pasture without manure application (P0). The 0-5, 5-10 and 10-20 cm soil layers were sampled and analyzed for total organic carbon, total nitrogen and soil physical properties such as density, porosity, aggregation, degree of flocculation, and penetration resistance. The organic carbon levels in the cultivated areas treated with organic fertilizer were even lower than in native forest soil. The organic fertilizers and studied management systems reduced the flocculation degree of the clay particles, and low macroporosity was observed in some areas. Despite these changes, a good soil physical structure was maintained, e.g., soil density and resistance to penetration were below the critical limits, whereas aggregate stability was high, which is important to reduce water erosion in these areas with rugged terrain in western Santa Catarina, used for pig and poultry farming.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Building predictive models of soil particle-size distribution

Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex geology.

Comparison between detailed digital and conventional soil maps of an area with complex geology

Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Soil water erosion under different cultivation systems and different fertilization rates and forms over 10 years

The action of rain and surface runoff together are the active agents of water erosion, and further influences are the soil type, terrain, soil cover, soil management, and conservation practices. Soil water erosion is low in the no-tillage management system, being influenced by the amount and form of lime and fertilizer application to the soil, among other factors. The aim was to evaluate the effect of the form of liming, the quantity and management of fertilizer application on the soil and water losses by erosion under natural rainfall. The study was carried out between 2003 and 2013 on a Humic Dystrupept soil, with the following treatments: T1 - cultivation with liming and corrective fertilizer incorporated into the soil in the first year, and with 100 % annual maintenance fertilization of P and K; T2 - surface liming and corrective fertilization distributed over five years, and with 75 % annual maintenance fertilization of P and K; T3 - surface liming and corrective fertilization distributed over three years, and with 50 % annual maintenance fertilization of P and K; T4 - surface liming and corrective fertilization distributed over two years, and with 25 % annual maintenance fertilization of P and K; T5 - fallow soil, without liming or fertilization. In the rotation the crops black oat (Avena strigosa ), soybean (Glycine max ), common vetch (Vicia sativa ), maize (Zea mays ), fodder radish (Raphanus sativus ), and black beans (Phaseolus vulgaris ). The split application of lime and mineral fertilizer to the soil surface in a no-tillage system over three and five years, results in better control of soil losses than when split in two years. The increase in the amount of fertilizer applied to the soil surface under no-tillage cultivation increases phytomass production and reduces soil loss by water erosion. Water losses in treatments under no-tillage cultivation were low in all crop cycles, with a similar behavior as soil losses.

SPATIAL DEPENDENCE OF ELECTRICAL CONDUCTIVITY AND CHEMICAL PROPERTIES OF THE SOIL BY ELECTROMAGNETIC INDUCTION

Brazilian soils have natural high chemical variability; thus, apparent electrical conductivity (ECa) can assist interpretation of crop yield variations. We aimed to select soil chemical properties with the best linear and spatial correlations to explain ECa variation in the soil using a Profiler sensor (EMP-400). The study was carried out in Sidrolândia, MS, Brazil. We analyzed the following variables: electrical conductivity - EC (2, 7, and 15 kHz), organic matter, available K, base saturation, and cation exchange capacity (CEC). Soil ECa was measured with the aid of an all-terrain vehicle, which crossed the entire area in strips spaced at 0.45 m. Soil samples were collected at the 0-20 cm depth with a total of 36 samples within about 70 ha. Classical descriptive analysis was applied to each property via SAS software, and GS+ for spatial dependence analysis. The equipment was able to simultaneously detect ECa at the different frequencies. It was also possible to establish site-specific management zones through analysis of correlation with chemical properties. We observed that CEC was the property that had the best correlation with ECa at 15 kHz.

Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils

ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).

Diversity of springtails (Hexapoda) according to a altitudinal gradient

The objective of this work was to elevate gradient effect on diversity of Collembola, in a temperate forest on the northeast slope of Iztaccíhuatl Volcano, Mexico. Four expeditions were organized from November 2003 to August 2004, at four altitudes (2,753, 3,015, 3,250 and 3,687 m a.s.l.). In each site, air temperature, CO2 concentration, humidity, and terrain inclination were measured. The influence of abiotic factors on faunal composition was evaluated, at the four collecting sites, with canonical correspondence analyses (CCA). A total of 24,028 specimens were obtained, representing 12 families, 44 genera and 76 species. Mesaphorura phlorae, Proisotoma ca. tenella and Parisotoma ca. notabilis were the most abundant species. The highest diversity and evenness were recorded at 3,250 m (H' = 2.85; J' = 0.73). Canonical analyses axes 1 and 2 of the CCA explained 67.4% of the variance in species composition, with CO2 and altitude best explaining axis 1, while slope and humidity were better correlated to axis 2. The results showed that CO2 is an important factor to explain Collembola species assemblage, together with slope and humidity.

Polarizabilidades e primeira hiperpolarizabilidades elétricas dipolares de ésteres E-4-amino-trans-1,3-butadienil-(1',2'-di-hidroxibenzeno) de boro, alumínio e gálio

Static electric dipole polarizabilities and first hyperpolarizabilites have been calculated for the title molecules and their 3' and 4'-nitro derivatives at ab-initio Hartree- Fock/6-31G(d, p) level. The influence of the pivotal p vacant 3A elements (B, Al or Ga) substitution on the electrical properties of these molecules is detailed. The axial vector components of the first hyperpolarizabilities β(0) of the push-pull 4'-nitro derivatives, -18.2×10-32 esu (B), -21.1×10-32 esu (Al) and -20.8×10-32 esu (Ga) are calculated to be as much as fourfold larger then that calculated for the p-nitroaniline, a reference organic molecule for comparison for this type of molecular property.

Hobbes et Gassendi: la psychologie dans le projet mécaniste

L'amitié et l'affinité intellectuelle qui caractérisèrent les rapports de Hobbes avec Gassendi forment un tissu ténu dont il n'est point aisé de démêler la trame. Aux côtés de points de convergence clairement définis, telle la commune aversion envers le dualisme et l'innéisme cartésiens, et par-delà des divergences non moins nettes dans leurs orientations philosophiques particulières, le sens des parcours maintes fois parallèles doit encore être éclairé de façon circonstanciée. Le terrain privilégié sur lequel élever une confrontation étroite entre deux auteurs est sans doute la construction d'une psychologie profondément marquée par des prémisses empiriques et dont l'orientation vise à établir une relation très étroite entre les processus de la perception, du désir (appetitus) et de la volonté avec ce qui les détermine matériellement et mécaniquement. On peut même affirmer que les écrits de Gassendi rédigés au tout début des années 1640 définissent une série d'hypothèses innovatrices sur lesquelles s'inscrit une certaine convergence avec les élaborations de Hobbes à elles contemporaines. Sous ce profil, le groupe de textes remontant aux années 1640-41, et où le philosophe d'Aix s'interroge sur la nature des phénomènes lumineux, est emblématique. L'explication du comportement des corps lumineux en terme de systole et de diastole, l'interprétation de la propagation de la lumière s'inspirant de la pure actualité cinématique (en polémique ouverte et explicite envers les thèses de la Dioptrique de Descartes sur la luminosité comme simple inclinaison au mouvement), le vacuisme (qui est propre à Gassendi, servant justement à rendre compte des phénomènes d'expansion et de contraction des sources lumineuses et qui, à cette époque, n'était pas encore exclu par Hobbes), la représentation, enfin, tout à fait matérielle et mécanique des phénomènes d'irradiation, voilà autant d'aspects de la recherche de Gassendi qui peuvent facilement être confrontés aux écrits de Hobbes.

MODELING AND SIMULATION OF RELIEF INFLUENCE ON EUCALYPTUS FORESTS: INTERACTION BETWEEN SOLAR IRRADIANCE AND PRODUCTIVITY

ABSTRACT This study aimed to verify the differences in radiation intensity as a function of distinct relief exposure surfaces and to quantify these effects on the leaf area index (LAI) and other variables expressing eucalyptus forest productivity for simulations in a process-based growth model. The study was carried out at two contrasting edaphoclimatic locations in the Rio Doce basin in Minas Gerais, Brazil. Two stands with 32-year-old plantations were used, allocating fixed plots in locations with northern and southern exposure surfaces. The meteorological data were obtained from two automated weather stations located near the study sites. Solar radiation was corrected for terrain inclination and exposure surfaces, as it is measured based on the plane, perpendicularly to the vertical location. The LAI values collected in the field were used. For the comparative simulations in productivity variation, the mechanistic 3PG model was used, considering the relief exposure surfaces. It was verified that during most of the year, the southern surfaces showed lower availability of incident solar radiation, resulting in up to 66% losses, compared to the same surface considered plane, probably related to its geographical location and higher declivity. Higher values were obtained for the plantings located on the northern surface for the variables LAI, volume and mean annual wood increase, with this tendency being repeated in the 3PG model simulations.

Comparison between hydrographically conditioned digital elevation models in the morphometric charaterization of watersheds

The aim of this study was to compare the hydrographically conditioned digital elevation models (HCDEMs) generated from data of VNIR (Visible Near Infrared) sensor of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), of SRTM (Shuttle Radar Topography Mission) and topographical maps from IBGE in a scale of 1:50,000, processed in the Geographical Information System (GIS), aiming the morphometric characterization of watersheds. It was taken as basis the Sub-basin of São Bartolomeu River, obtaining morphometric characteristics from HCDEMs. Root Mean Square Error (RMSE) and cross validation were the statistics indexes used to evaluate the quality of HCDEMs. The percentage differences in the morphometric parameters obtained from these three different data sets were less than 10%, except for the mean slope (21%). In general, it was observed a good agreement between HCDEMs generated from remote sensing data and IBGE maps. The result of HCDEM ASTER was slightly higher than that from HCDEM SRTM. The HCDEM ASTER was more accurate than the HCDEM SRTM in basins with high altitudes and rugged terrain, by presenting frequency altimetry nearest to HCDEM IBGE, considered standard in this study.

Application of a non isotropic turbulence model to stable atmospheric flows and dispersion over 3D topography

A non isotropic turbulence model is extended and applied to three dimensional stably stratified flows and dispersion calculations. The model is derived from the algebraic stress model (including wall proximity effects), but it retains the simplicity of the "eddy viscosity" concept of first order models. The "modified k-epsilon" is implemented in a three dimensional numerical code. Once the flow is resolved, the predicted velocity and turbulence fields are interpolated into a second grid and used to solve the concentration equation. To evaluate the model, various steady state numerical solutions are compared with small scale dispersion experiments which were conducted at the wind tunnel of Mitsubishi Heavy Industries, in Japan. Stably stratified flows and plume dispersion over three distinct idealized complex topographies (flat and hilly terrain) are studied. Vertical profiles of velocity and pollutant concentration are shown and discussed. Also, comparisons are made against the results obtained with the standard k-epsilon model.