140 resultados para Zooplankton spatial distribution patterns


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Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

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The aquatic humic substances (AHS) investigated in this study were conventionally isolated from Rio Negro waters - Amazonas State/Brazil by means of the collector XAD 8. A special five-stage tangential-flow ultrafiltration device was used for analytical fractionation of AHS. The fractionation patterns (6 fractions each) showed that metal traces remaining in AHS after their XAD 8 isolation have different size distributions. For instance, the major percentage of traces of Ni, Cu, Zn, Cd and Pb (determined using ICP-AES) was preferably complexed by molecules with relatively high molecular size (30-100 kDa) and the following complexation order was characterized: F2 >> F1 = F4 = F5 > F3 > F6. Moreover, the species formed between AHS and metals prepared by spiking, showed distribution patterns changing as a function of the complexation time (ageing process), indicating a slow transformation process and an inner rearrangements in the binding sites within the AHS molecules.

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In this work we propose a new approach for the determination of the mobility of mercury in sediments based on spatial distribution of concentrations. We chose the Tainheiros Cove, located in the Todos os Santos Bay, Brazil, as the study area, for it has a history of mercury contamination due to a chloro-alkali plant that was active during 12 years. Twenty-six surface sediment samples were collected from the area and mercury concentrations were measured by cold vapour atomic absorption spectrophotometry. A contour map was constructed from the results, indicating that mercury accumulated in a "hot spot" where concentrations reach more than 1 µg g-1. The model is able to estimate mobility of mercury in the sediments based on the distances between iso-concentration contours that determines an attenuation of concentrations factor. Values of attenuation ranged between 0.0729 (East of the hot spot, indicating higher mobility) to 0.7727 (North of the hot spot, indicating lower mobility).

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Heavy-metal concentration in sediment is an important parameter for identifying pollution sources and assessing pollution levels in aquatic ecosystems. In this context, the present study aimed at determining concentrations of heavy metals in sediments from the Vitória estuarine system, Brazil. Twenty nine stations were surveyed to assess the spatial distribution of heavy metals. The metals for silt-clay fractions (<63 µm) were analyzed through atomic absorption spectrometry. A discriminant analysis segregated the stations in four groups representing four areas within the estuarine system. The Espírito Santo Bay showed the lowest metal concentrations, while the Vitória harbor canal showed the highest. We concluded that concentrations of heavy metals reflect natural conditions and the contribution of human activities from sewage and industrial effluents. It was not possible to directly associate metal concentrations to specific pollution sources.

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The alteration in the quality of groundwater in the industrial zone of Brazil's southernmost state was assessed by a hydrogeochemical study. In 70-85% of the studied area, fluoride, nitrate and phosphate in groundwater surpass the maximum limits for human consumption according to Brazilian environmental legislation. The chemical spectrum of contaminants and their spatial distribution show that fertilizer production processes are responsible for groundwater pollution. The natural conditions of the region are not favorable for minimal protection against infiltration of pollutants into the aquifer.

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Nickel and vanadium were tested as tracers of oil refinery emission distribution in populated area of Rio Grande-RS. The anomalies of these elements in surface soil are considered a long-term reflection of the emissions in low atmosphere. The spatial distribution of Ni and V in the soil corresponded to the pattern of local winds. The threshold of 1.5 backgrounds of these metals markedly outlined the area of petrochemical emissions. Anomalies of Ni and V in surface soil have a rather different configuration in comparison with other metal tracers of urban impact: Cd, Cu, Pb and Zn.

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The marine environment is certainly one of the most complex systems to study, not only because of the challenges posed by the nature of the waters, but especially due to the interactions of physical, chemical and biological processes that control the cycles of the elements. Together with analytical chemists, oceanographers have been making a great effort in the advancement of knowledge of the distribution patterns of trace elements and processes that determine their biogeochemical cycles and influences on the climate of the planet. The international academic community is now in prime position to perform the first study on a global scale for observation of trace elements and their isotopes in the marine environment (GEOTRACES) and to evaluate the effects of major global changes associated with the influences of megacities distributed around the globe. This action can only be performed due to the development of highly sensitive detection methods and the use of clean sampling and handling techniques, together with a joint international program working toward the clear objective of expanding the frontiers of the biogeochemistry of the oceans and related topics, including climate change issues and ocean acidification associated with alterations in the carbon cycle. It is expected that the oceanographic data produced this coming decade will allow a better understanding of biogeochemical cycles, and especially the assessment of changes in trace elements and contaminants in the oceans due to anthropogenic influences, as well as its effects on ecosystems and climate. Computational models are to be constructed to simulate the conditions and processes of the modern oceans and to allow predictions. The environmental changes arising from human activity since the 18th century (also called the Anthropocene) have made the Earth System even more complex. Anthropogenic activities have altered both terrestrial and marine ecosystems, and the legacy of these impacts in the oceans include: a) pollution of the marine environment by solid waste, including plastics; b) pollution by chemical and medical (including those for veterinary use) substances such as hormones, antibiotics, legal and illegal drugs, leading to possible endocrine disruption of marine organisms; and c) ocean acidification, the collateral effect of anthropogenic emissions of CO2 into the atmosphere, irreversible in the human life time scale. Unfortunately, the anthropogenic alteration of the hydrosphere due to inputs of plastics, metal, hydrocarbons, contaminants of emerging concern and even with formerly "exotic" trace elements, such us rare earth elements is likely to accelerate in the near future. These emerging contaminants would likely soon present difficulties for studies in pristine environments. All this knowledge brings with it a great responsibility: helping to envisage viable adaptation and mitigation solutions to the problems identified. The greatest challenge faced by Brazil is currently to create a framework project to develop education, science and technology applied to oceanography and related areas. This framework would strengthen the present working groups and enhance capacity building, allowing a broader Brazilian participation in joint international actions and scientific programs. Recently, the establishment of the National Institutes of Science and Technology (INCTs) for marine science, and the creation of the National Institute of Oceanographic and Hydrological Research represent an exemplary start. However, the participation of the Brazilian academic community in the latest assaults on the frontier of chemical oceanography is extremely limited, largely due to: i. absence of physical infrastructure for the preparation and processing of field samples at ultra-trace level; ii. limited access to oceanographic cruises, due to the small number of Brazilian vessels and/or absence of "clean" laboratories on board; iii. restricted international cooperation; iv. limited analytical capacity of Brazilian institutions for the analysis of trace elements in seawater; v. high cost of ultrapure reagents associated with processing a large number of samples, and vi. lack of qualified technical staff. Advances in knowledge, analytic capabilities and the increasing availability of analytical resources available today offer favorable conditions for chemical oceanography to grow. The Brazilian academic community is maturing and willing to play a role in strengthening the marine science research programs by connecting them with educational and technological initiatives in order to preserve the oceans and to promote the development of society.

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This paper aims to assess the effectiveness of ASTER imagery to support the mapping of Pittosporum undulatum, an invasive woody species, in Pico da Vara Natural Reserve (S. Miguel Island, Archipelago of the Azores, Portugal). This assessment was done by applying K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Maximum Likelihood (MLC) pixel-based supervised classifications to 4 different geographic and remote sensing datasets constituted by the Visible, Near-Infrared (VNIR) and Short Wave Infrared (SWIR) of the ASTER sensor and by digital cartography associated to orography (altitude and "distance to water streams") of which the spatial distribution of Pittosporum undulatum directly depends. Overall, most performed classifications showed a strong agreement and high accuracy. At targeted species level, the two higher classification accuracies were obtained when applying MLC and KNN to the VNIR bands coupled with auxiliary geographic information use. Results improved significantly by including ecology and occurrence information of species (altitude and distance to water streams) in the classification scheme. These results show that the use of ASTER sensor VNIR spectral bands, when coupled to relevant ancillary GIS data, can constitute an effective and low cost approach for the evaluation and continuous assessment of Pittosporum undulatum woodland propagation and distribution within Protected Areas of the Azores Islands.

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The penetration resistance (PR) is a soil attribute that allows identifies areas with restrictions due to compaction, which results in mechanical impedance for root growth and reduced crop yield. The aim of this study was to characterize the PR of an agricultural soil by geostatistical and multivariate analysis. Sampling was done randomly in 90 points up to 0.60 m depth. It was determined spatial distribution models of PR, and defined areas with mechanical impedance for roots growth. The PR showed a random distribution to 0.55 and 0.60 m depth. PR in other depths analyzed showed spatial dependence, with adjustments to exponential and spherical models. The cluster analysis that considered sampling points allowed establishing areas with compaction problem identified in the maps by kriging interpolation. The analysis with main components identified three soil layers, where the middle layer showed the highest values of PR.

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The spatial distribution of illuminance and the electric consumption of artificial lighting system is one of the main problems related to broiler production. Therefore, the aim of this study was to evaluate the spatial distribution of luminance level and energy efficiency of different lighting systems for broiler houses. Six types of lamps were tested in two different configurations to find the minimum illuminance of 20 and 5 lux. The tested lamps were incandescent (IL) 100 W, compact fluorescent (CFL) 34 W, mixed (ML) 160 W, sodium vapor (SVL) 70 W, T8 fluorescent tube (T8 FTL) 40 W and T5 fluorescent tube (T5 FTL) 28 W. The first four were evaluated with and without reflective light fixture and the latter two without light fixture. It was observed that the tested system with light fixtures negatively affected the spatial distribution of illuminance inside the house. The systems composed by IL and ML without light fixture led to better results in meeting the minimum illuminance of 20 lux and 5 lux, respectively. T5 FTL presented the lowest energy demand.

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ABSTRACT This study aimed to compare thematic maps of soybean yield for different sampling grids, using geostatistical methods (semivariance function and kriging). The analysis was performed with soybean yield data in t ha-1 in a commercial area with regular grids with distances between points of 25x25 m, 50x50 m, 75x75 m, 100x100 m, with 549, 188, 66 and 44 sampling points respectively; and data obtained by yield monitors. Optimized sampling schemes were also generated with the algorithm called Simulated Annealing, using maximization of the overall accuracy measure as a criterion for optimization. The results showed that sample size and sample density influenced the description of the spatial distribution of soybean yield. When the sample size was increased, there was an increased efficiency of thematic maps used to describe the spatial variability of soybean yield (higher values of accuracy indices and lower values for the sum of squared estimation error). In addition, more accurate maps were obtained, especially considering the optimized sample configurations with 188 and 549 sample points.

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Brazil has high climate, soil and environmental diversity, as well as distinct socioeconomic and political realities, what results in differences among the political administrative regions of the country. The objective of this study was to determine spatial distribution of the physical, climatic and socioeconomic aspects that best characterize the production of dairy goats in Brazil. Production indices of milk per goat, goat production, milk production, as well as temperature range, mean temperature, precipitation, normalized difference vegetation index, relative humidity, altitude, agricultural farms; farms with native pasture, farms with good quality pasture, farms with water resources, farms that receive technical guidance, family farming properties, non-familiar farms and the human development index were evaluated. The multivariate analyses were carried out to spatialize climatic, physical and socioeconomic variables and so differenciate the Brazilian States and Regions. The highest yields of milk and goat production were observed in the Northeast. The Southeast Region had the second highest production of milk, followed by the South, Midwest and North. Multivariate analysis revealed distinctions between clusters of political-administrative regions of Brazil. The climatic variables were most important to discriminate between regions of Brazil. Therefore, it is necessary to implement animal breeding programs to meet the needs of each region.

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Understanding spatial distribution of weeds in the crop enables to perform localized herbicide applications, increasing the technical and economic efficiency of operations and reducing environmental impacts. This work aimed to characterize the spatial and phytosociological variability of weeds occurring in soybean commercial field. It was conducted in an agricultural area located at the municipality of Boa Vista das Missões - RS, during the 2010/2011 harvest season. The area, that had been managed under no-tillage with soybean monoculture (summer) for five years, was divided in regular squares of 50 x 50 m (0.25 ha), totalizing 356 points. For species identification, 0.5 x 0.5 m sample squares were used. During the survey, 1,739 individuals were identified, distributed in 19 species of 13 families. The weed species Cardiospermum halicacabum, Digitaria horizontalis, Urochloa plantaginea and Raphanus raphanistrum showed the highest population variation in the area; however, only C. halicacabum, U. plantaginea and R. raphanistrum stood out based on the Importance Index Value (IVI). Localized management strategies considering the spatial variability of weed species placed in the Magnoliopsidas and Liliopsidas group show a high potential for use in soybean crop. The results show that the sampling method through regular grid was capable of characterizing the occurrence, population density and spatial variability of weed species in soybean crop.

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The aim of this study was to identify and map the weed population in a no-tillage area. Geostatistical techniques were used in the mapping in order to assess this information as a tool for the localized application of herbicides. The area of study is 58.08 hectares wide and was sampled in a fixed square grid (which point spaced 50 m, 232 points) using a GPS receiver. In each point the weeds species and population were analyzed in a square with a 0.25 m2 fixed area. The species Ipomoea grandifolia, Gnaphalium spicatum, Richardia spp. and Emilia sonchifolia have presented no spatial dependence. However, the species Conyza spp., C. echinatus and E. indica have shown a spatial correlation. Among the models tested, the spherical model has shown had a better fit for Conyza spp. and Eleusine indica and the Gaussian model for Cenchrus echinatus. The three species have a clumped spatial distribution. The mapping of weeds can be a tool for localized control, making herbicide use more rational, effective and economical.

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ABSTRACT - (Climate, soil and tree flora relationships in forests in the state of São Paulo, southteastern Brasil). With the aim of verifying possible influences of abiotic features on the spatial distribution of forest tree species and families, thirteen surveys in the state of São Paulo were selected, representing different conditions (localization at the extreme coordenates and altitudes, succesional stages, surveying methods). By applying Jaccard's Index to the binary matrices of 806 synonymized specific binomina and 79 families (Cronquist's system) phenograms were constructed using the method of the unweighted pair grouping by mathematical average (UPGMA). The species formed two floristic blocks: hygrophyllous (yearly rainfall greater than 2000 mm without dry season) and mesophyllous (yearly rainfall about 1400 mm with variable dry season). The latter was divided in two other groups: the high-altitudinal (median altitudes higher than 750 m, frost average frequency greater than 3 days/year) and low-altitudinal. Both mesophyllous floristic blocks were subdivided according to soil conditions (texture, eutrophism, acid or allic dystrophism, iron content). At the family level the relations were weak, but also showed the soil nutritional status as a possible constraint to the spatial partition of families.