Fernando Pellon de Miranda

Metagenomics of the Water Column in the Pristine Upper Course of the Amazon River

River water is a small percentage of the total freshwater on Earth but represents an essential resource for mankind. Microbes in rivers perform essential ecosystem roles including the mineralization of significant quantities of organic matter originating from terrestrial habitats. The Amazon river in particular is famous for its size and importance in the mobilization of both water and carbon out of its enormous basin. Here we present the first metagenomic study on the microbiota of this river. It presents many features in common with the other freshwater metagenome available (Lake Gatun in Panama) and much less similarity with marine samples. Among the microbial taxa found, the cosmopolitan freshwater acI lineage of the actinobacteria was clearly dominant. Group I Crenarchaea and the freshwater sister group of the marine SAR11 clade, LD12, were found alongside more exclusive and well known freshwater taxa such as Polynucleobacter. A metabolism-centric analysis revealed a disproportionate representation of pathways involved in heterotrophic carbon processing, as compared to those found in marine samples. In particular, these river microbes appear to be specialized in taking up and mineralizing allochthonous carbon derived from plant material.

Application of the semivariogram textural classifier (STC) for vegetation discrimination using SIR-B data of Borneo

Abstract Classification of Shuttle Imaging Radar-B (SIR-B) data from a rainforest-covered portion of Borneo is performed using image texture. The algorithm used is the semivariogram textural classifier (STC). This is a deterministic, supervised parallelepiped type classifier which provides the option of combining textural and radiometric information. Textural information is expressed by the semivariogram function. Radiometric information is conveyed by the mean digital number (DN) value. Results of the classificaiion cmulale a previously published map obtained by visual interpretation of the same SIR-B data set.

Analysis of JERS-1 (Fuyo-1) SAR data for vegetation discrimination in northwestern Brazil using the semivariogram textural classifier (STC)

Abstract Classification of JERS-1 (Fuyo-1) SAR data from the northwestern portion of Brazil was performed using the semivariogram textural classifier (STC). This is a deterministic, supervised classifier which provides the option of combining textural and radiometric information. Textural information is expressed by the semivariogram function; radiometric information is conveyed by the mean digital number (DN) value. Results have shown that STC allows vegetation units and water bodies to be discriminated and tentatively mapped, suggesting that this is a promising approach for environmental monitoring of rainforest regions using SAR data.

Analysis of RADARSAT-1 data for offshore monitoring activities in the Cantarell Complex, Gulf of Mexico, using the unsupervised semivariogram textural classifier (USTC)

Understanding the temporal dynamics and spatial distribution of natural seepage phenomena in the Gulf of Mexico is fundamental for the definition of proper environmental management practices in this often cloud-covered region. RADARSAT-1 images analyzed in this paper were acquired using the wide 1 and wide 2 (W1, W2) and ScanSAR narrow 1 (SCN1) beam modes. Image processing was carried out using the unsupervised semivariogram textural classifier (USTC). In combination with RADARSAT-1 satellite images, and essential ancillary data, this technology enhances the detection of seepage slicks on the ocean surface based on radar texture. USTC classification of RADARSAT-1 data provided systematic evidence from space of the presence of prolific, present-day petroleum generation and migration in the Cantarell Complex of oil fields.

Remote detection of a tonal anomaly in an area of hydrocarbon microseepage, Tucano basin, north-eastern Brazil

Mapping of a tonal anomaly in an area of hydrocarbon microseepage was possible using a Landsat-Thematic Mapper false-colour composite consisting of TM2/3, TM4/3 and of the difference TM2/3-TM4/3, displayed as red, green and blue, respectively. In this false-colour composite, green and yellow express variations in the vegetation cover, whereas hues of magenta are related to terrain conditions representing bleached materials, which occur close to the centre of a soil gas anomaly. Simultaneous occurrence of anomalous soil gas values with magnetic and radioactive minerals suggests that a reducing environment associated with the microseepage phenomenon created the bleached materials, identified as a tonal anomaly in the enhanced TM image.

Data integration for a geologic model of hydrocarbon microseepage areas in the Tonã Plateau region, North Tucano basin, Brazil

A diversified database was used for investigating the major factors controlling the distribution of hydrocarbon microseepage in the region of the Tonã Plateau, North Tucano sedimentary basin, Brazil. Visual analysis of this database suggested the existence of spatial relationships between anomalous geochemical soil gas data with rift faults, lithologic contact, and groundwater discharge areas. As a result, a geologic model was proposed. According to this model, rift faults constitute the primary pathways for the upward migration of gaseous hydrocarbons from a deep-seated source rock in the depocenter of the basin. Cherty limestone layers in the Tonã Plateau act as a seal to prevent the escape of the hydrocarbons to the surface. As a result, hydrocarbon microseepage occurs preferentially in the contact zone of the cherty limestones of the Tonã Sequence with porous sandstones of the Marizal Formation, mainly in areas of groundwater discharge. The importance of these three patterns for controlling the near-surface distribution of the anomalous soil gas samples was estimated through Bayesian probability analysis. According to this interpretation, lithologic contact is the spatial pattern more strongly associated with the anomalous soil gas samples, followed by groundwater discharge areas. Rift faults show the weaker spatial correlation with the anomalous near-surface areas of hydrocarbon microseepage.

Metagenomics Analysis of Microorganisms in Freshwater Lakes of the Amazon Basin

ABSTRACT The Amazon Basin is the largest hydrographic basin on the planet, and the dynamics of its aquatic microorganisms strongly impact global biogeochemical cycles. However, it remains poorly studied. This metagenome project was performed to obtain a snapshot of prokaryotic microbiota from four important lakes in the Amazon Basin.

Environmental sensitivity index (ESI) mapping of oil spill in the amazon coastal zone: the PIATAM Mar project

The importance of environmental monitoring is clear from the many oil spills that have occurred over the past three decades. This has encouraged both companies and the public sector involved in the prevention and response to these accidents to develop efficient procedures to minimize the damage caused by accidents involving oil spill. This study reviews the history of oil spill accidents in Brazil and examines how these events have contributed to the development of technological research through partnerships involving oil companies, government, universities and research institutes, with the emphasis on the Amazon coastal zone. As a result, environmental sensitivity indexes (ESIs) for oil spill have been developed specifically for the Amazon coast, where fluvial and marine processes take place in the estuary of the worlds largest river system. Perspectives on research and emergency response procedures are presented, with the primary objective of conserving the social-environmental diversity of the planets most important tropical region.

RADARSAT-1 images in support of petroleum exploration: the offshore Amazon River mouth example

RADARSAT-1 images were used as an attempt to identify seepage slicks in the Foz do Amazonas Basin, one of the most promising oil and gas exploration frontiers in the Brazilian equatorial margin, a region that is cloud-covered for most of the year. An unsupervised semivariogram textural classifier algorithm was used to enhance areas of smooth texture and low radar backscatter, indicative of these seepage slick targets. Complementary information related to sea surface temperature, cloud top temperature, wind velocity, and modelling for the tidal regime (all obtained as close as possible to the RADARSAT-1 acquisition) was used to support image interpretation and to exclude false targets also characterized by low radar backscatter (e.g., local upwelling, heavy rain cells). Twenty-one target areas were interpreted as seepage slicks. Considering the influence of the oceanographic and environmental conditions on drifting of the interpreted seepage slicks, they were spatially compared with available geological information, including seismically derived structural and isopach maps, and bathymetric data. Most of the interpreted seepage slicks occur in an extensional structural domain of growth faults. These structures are related to Cenozoic gravity tectonics that result from tensional stress in the continental slope due to the huge load of fluvial sediments transported by the Amazon River. Together with previously discovered subcommercial shallow water oil accumulations, the remote detection of seepage slicks is additional evidence of present-day generation and migration phenomena. The results indicate that the use of a remote, swift method to identify offshore natural oil seepage related to active petroleum systems may constitute a well-accepted approach to support exploration in frontier areas like the Foz do Amazonas Basin.

MAPSAR Image Simulation Based on L-band Polarimetric Data from the SAR-R99B Airborne Sensor (SIVAM System)

This paper describes the methodology applied to generate simulated multipolarized L-band SAR images of the MAPSAR (Multi-Application Purpose SAR) satellite from the airborne SAR R99B sensor (SIVAM System). MAPSAR is a feasibility study conducted by INPE (National Institute for Space Research) and DLR (German Aerospace Center) targeting a satellite L-band SAR innovative mission for assessment, management and monitoring of natural resources. Examples of simulated products and their applications are briefly discussed.