Scalar turbulent behavior in the roughness sublayer of an Amazonian forest.

An important current problem in micrometeorology is the characterization of turbulence in the roughness sublayer (RSL), where most of the measurements above tall forests are made. There, scalar turbulent fluctuations display significant departures from the predictions of Monin?Obukhov similarity theory (MOST). In this work, we analyze turbulence data of virtual temperature, carbon dioxide, and water vapor in the RSL above an Amazonian forest (with a canopy height of 40 m), measured at 39.4 and 81.6 m above the ground under unstable conditions. We found that dimensionless statistics related to the rate of dissipation of turbulence kinetic energy (TKE) and the scalar variance display significant departures from MOST as expected, whereas the vertical velocity variance follows MOST much more closely. Much better agreement between the dimensionless statistics with the Obukhov similarity variable, however, was found for the subset of measurements made at a low zenith angle Z, in the range 0°  <  |Z|  <  20°. We conjecture that this improvement is due to the relationship between sunlight incidence and the ?activation?deactivation? of scalar sinks and sources vertically distributed in the forest. Finally, we evaluated the relaxation coefficient of relaxed eddy accumulation: it is also affected by zenith angle, with considerable improvement in the range 0°  <  |Z|  <  20°, and its values fall within the range reported in the literature for the unstable surface layer. In general, our results indicate the possibility of better stability-derived flux estimates for low zenith angle ranges.

Phytotoxic activity of compounds from Moutabea guianensis aubl. on Amazonian invasive species.

Este estudo teve como objetivo estabelecer as variações na atividade fitotóxica dos extratos hexânico, acetato de etila e metanólico das raízes de Moutabea guianensis, e das substâncias cafeato de metila e escopoletina isoladas do extrato acetato de etila, variando a concentração e as espécies receptores. Foram desenvolvidos bioensaios de atividades fitotóxicas de germinação (a 25 °C e 12 horas de fotoperíodo) e de desenvolvimento da radícula e do hipocótilo (25 °C e 24 horas de fotoperíodo). A germinação das sementes de Mimosa pudica foi sensível aos extratos hexânico, acetato de etila e metanólico a 1% (w/v), com efeitos de inibição em 92%, 100% e 100%, respectivamente. A análise comparativa da atividade fitotóxica das substâncias testadas revelou que a escopoletina apresentou um potencial de inibição mais elevado no bioensaio de germinação de sementes frente a Mimosa pudica. Senna obtusifolia não foi sensível às substâncias testadas. Cafeato de metila apresentou maior potencial de inibição no bioensaio de desenvolvimento da radícula e hipocótilo, e a intensidade dos efeitos alelopáticos variou com as concentrações.

Scalar turbulent behavior in the roughness sublayer of an Amazonian forest.

An important current problem in micrometeorology is the characterization of turbulence in the roughness sublayer (RSL), where most of the measurements above tall forests are made. There, scalar turbulent fluctuations display significant departures from the predictions of Monin?Obukhov similarity theory (MOST). In this work, we analyze turbulence data of virtual temperature, carbon dioxide, and water vapor in the RSL above an Amazonian forest (with a canopy height of 40?m), measured at 39.4 and 81.6?m above the ground under unstable conditions. We found that dimensionless statistics related to the rate of dissipation of turbulence kinetic energy (TKE) and the scalar variance display significant departures from MOST as expected, whereas the vertical velocity variance follows MOST much more closely. Much better agreement between the dimensionless statistics with the Obukhov similarity variable, however, was found for the subset of measurements made at a low zenith angle Z, in the range 0°??

The women role in the agroenvironmental activities of Amazon agroforeststry systems.

This paper presents the results of a research on the way which shows the role of the farmer women to contribute to overcome the life hindrances in the Amazonian agroforest environment, for food safety and familiar income. The sample was the women of the Associação de Produtores Alternativos - APA, Ouro Preto do Oeste, Rondônia, Brazil. Questionnaires were applied to 50 women of this community, in 2004/2005, with additional interviews in 2006, taking into account their role in the farms, and their several invisible activities. The role of APA?s women was compared to that of other Amazonian women, like rubber tappers and riverine people. The APA?s women perform tasks as field manpower - 78.0% of them, making decisions about what to plant - 18.0%, harvest destination - 32.0%, which animals to raise -14.0% and animal products destination -34.0%. Traditionally, in rural zone, the women with their children play a role as non-paid manpower, getting some monetary income with occasional commercialization of on-farm processed products as cheese, pickles, jellies and fruit liqueurs. They are responsible for the cultures practiced around the house. All these Amazonian women edaphoclimatic conditions, greatly contributing to the biodiversity, conservation, and to ecological, social and economic stability.are guardians, perpetuators and disseminators of a rich germplasm adapted to local.

Direct nitrous oxide (N2O) fluxes from soils under different land use in Brazil: a critical review.

Brazil typifies the land use changes happening in South America, where natural vegetation is continuously converted into agriculturally used lands, such as cattle pastures and croplands. Such changes in land use are always associated with changes in the soil nutrient cycles and result in altered greenhouse gas fluxes from the soil to the atmosphere. In this study, we analyzed literature values to extract patterns of direct nitrous oxide (N2O) emissions from soils of different ecosystems in Brazil. Fluxes from natural ecosystems exhibited a wide range: whereas median annual flux rates were highest in Amazonian and Atlantic rainforests (2.42 and 0.88 kg N ha-1), emissions from cerrado soils were close to zero. The decrease in emissions from pastures with increasing time after conversion was associated with pasture degradation. We found comparatively low N2O-N fluxes from croplands (-0.07 to 4.26 kg N ha-1 yr-1 , median 0.80 kg N ha-1 yr-1) and a low response to N fertilization. Contrary to the assumptions, soil parameters, such as pH, Corg, and clay content emerged as poor predictors for N2O fluxes. This could be a result of the formation of micro-aggregates, which strongly affect the hydraulic properties of the soil, and consequently define nitrification and denitrification potentials. Since data from croplands mainly derived from areas that had been under natural cerrado vegetation before, it could explain the low emissions under agriculture. Measurements must be more frequent and regionally spread in order to enable sound national estimates.

Soil organic carbon, carbon stock and their relationships to physical attributes under forest soils in Central Amazonia.

The soil carbon under Amazonian forests has an important roles in global changing, making information on the soil content and depths of these stocks are considerable interest in efforts to quantify soil carbon emissions to the atmosphere.This study quantified the content and soil organic carbon stock under primary forest up to 2 m depth, at different topographic positions, at Cuieiras Biological Reserve, Manaus/ ZF2, km 34, in the Central Amazon, evaluating the soil attributes that may influence the permanence of soil carbon. Soil samples were collected along a transect of 850 m on topographic gradient Oxisol (plateau), Ultisol (slope) and Spodosol (valley). The stocks of soil carbon were obtained by multiplying the carbon content, soil bulk density and trickiness of soil layers. The watershed was delimited by using STRM and IKONOS images and the carbon contend obtained in the transects was extrapolated as a way to evaluate the potential for carbon stocks in an area of 2678.68 ha. The total SOC was greater in Oxisol followed by Spodosol and Ultisol. It was found direct correlations between the SOC and soil physical attributes. Among the clay soils (Oxisol and Ultisol), the largest stocks of carbon were observed in Oxisol at both the transect (90 to 175.5 Mg C ha-1) as the level of watershed (100.2 to 195.2 Mg C ha-1). The carbon stocks under sandy soil (Spodosol) was greater to clay soils along the transect (160-241 Mg C ha-1) and near them in the Watershed (96.90 to 146.01 Mg C ha-1).

Detecting outliers and asserting consistency in agriculture ground truth information by using temporal VI data from modis.

Collecting ground truth data is an important step to be accomplished before performing a supervised classification. However, its quality depends on human, financial and time ressources. It is then important to apply a validation process to assess the reliability of the acquired data. In this study, agricultural infomation was collected in the Brazilian Amazonian State of Mato Grosso in order to map crop expansion based on MODIS EVI temporal profiles. The field work was carried out through interviews for the years 2005-2006 and 2006-2007. This work presents a methodology to validate the training data quality and determine the optimal sample to be used according to the classifier employed. The technique is based on the detection of outlier pixels for each class and is carried out by computing Mahalanobis distances for each pixel. The higher the distance, the further the pixel is from the class centre. Preliminary observations through variation coefficent validate the efficiency of the technique to detect outliers. Then, various subsamples are defined by applying different thresholds to exclude outlier pixels from the classification process. The classification results prove the robustness of the Maximum Likelihood and Spectral Angle Mapper classifiers. Indeed, those classifiers were insensitive to outlier exclusion. On the contrary, the decision tree classifier showed better results when deleting 7.5% of pixels in the training data. The technique managed to detect outliers for all classes. In this study, few outliers were present in the training data, so that the classification quality was not deeply affected by the outliers.