948 resultados para RIO NEGRO (PROVINCIA)
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Pós-graduação em Geografia - IGCE
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Mode of access: Internet.
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Mode of access: Internet.
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Translation of: At home with the Patagonians.
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Reprinted from Revista del Museo de La Plata, v.9.
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Two mounted photographs on cover.
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Mode of access: Internet.
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This paper characterizes humic substances (HS) extracted from soil samples collected in the Rio Negro basin in the state of Amazonas, Brazil, particularly investigating their reduction capabilities towards Hg(II) in order to elucidate potential mercury cycling/volatilization in this environment. For this reason, a multimethod approach was used, consisting of both instrumental methods (elemental analysis, EPR, solid-state NMR, FIA combined with cold-vapor AAS of Hg(0)) and statistical methods such as principal component analysis (PCA) and a central composite factorial planning method. The HS under study were divided into groups, complexing and reducing ones, owing to different distribution of their functionalities. The main functionalities (cor)related with reduction of Hg(II) were phenolic, carboxylic and amide groups, while the groups related with complexation of Hg(II) were ethers, hydroxyls, aldehydes and ketones. The HS extracted from floodable regions of the Rio Negro basin presented a greater capacity to retain (to complex, to adsorb physically and/or chemically) Hg(II), while nonfloodable regions showed a greater capacity to reduce Hg(II), indicating that HS extracted from different types of regions contribute in different ways to the biogeochemical mercury cycle in the basin of the mid-Rio Negro, AM, Brazil. (c) 2007 Published by Elsevier B.V.
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In this work humic substances (HS) extracted from non-flooded (Araca) and flooded (Iara) soils were characterized through the calculation of stability and activation energies associated with the dehydration and thermal decomposition of HS using TGA and DTA, electronic paramagnetic resonance and C/H, C/N and C/O atomic ratios. For HS extracted from flooded soils, there was evidence for the influence of humidity on the organic matter humification process. Observations of thermal behaviour, with elemental analysis, indicated the presence of fossilized organic carbon within clay particles, which only decomposed above 800 C. This characteristic could explain the different thermal stability and pyrolysis activation energies for Iara HS compared to Araca HS.
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This paper aimed to study and compare the hematology of newborns, young, subadults, adult males, adult females and pregnant females of Potamotrygon wallacei (cururu stingray), Potamotrygon motoro and Paratrygon aiereba. Newborn cururu stingrays had lower red blood parameters than those of other development stages. Thrombograms and leukograms showed a conservative pattern between development stage, sexual dimorphism and pregnancy. In P. motoro and P. aiereba, variables relating to red blood parameters, biochemistry and leukograms showed little variation between the species' biological characteristics, thus showing that these variables are not good criteria for differentiating them within the same species. In conclusion, the development stage is an important factor for differentiating hematological properties in the cururu stingray, while this has not been observed in P. motoro and P. aiereba stingrays.
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A degradação das pastagens pode ser definida como um processo evolutivo de perda de vigor, produtividade e capacidade de recuperação natural, e é atualmente um dos maiores problemas para a pecuária brasileira. Estudos recentes com imagens de satélites de sensoriamento remoto apresentam resultados promissores para identificar e mapear diferentes níveis de degradação em pastagens. Estas imagens também permitem monitor ao longo dos anos o processo de degradação em escala local ou regional. O objetivo do presente estudo consiste em avaliar o uso de imagens fusionadas dos sensores HRC e CCD do satélite CBERS-2B, para identificar e caracterizar áreas com pastagens degradadas nos municípios de Corguinho e Rio Negro no Estado de Mato Grosso do Sul. As imagens foram processadas utilizando o aplicativo SPRING. A classificação foi baseada na segmentação, no MAXVER e na Bhattacharya gerando um mapa temático das áreas de pastagens degradadas na escala de 1:50.000.