Spatial distribution of disseminated histoplasmosis and AIDS co-infection in an endemic area of Northeastern Brazil

Abstract: INTRODUCTION: The spatial distribution of disseminated histoplasmosis (DH) and acquired immunodeficiency syndrome (AIDS) co-infection in adult residents of Fortaleza, Ceará, Brazil was evaluated. METHODS: Socio-demographic data for the DH/AIDS cases were obtained from a reference hospital, and socio-environmental indicators were obtained from an official Brazilian institute. Kernel analysis and local indicators of spatial autocorrelation (LISA) cluster maps were used to estimate the case density within the city. RESULTS: DH/AIDS cases were concentrated in the Northwestern and Southwestern peripheral areas of the city, related with low human development indices, but different from AIDS cases distribution. CONCLUSION: Risk factors other than AIDS infection must affect histoplasmosis development in this area.

Assemblage of immature Odonata (Insecta, Anisoptera) in streams of the Mato Grosso do Sul State: spatial implications

ABSTRACT This study investigated the assemblages attributes (composition, abundance, richness, diversity and evenness) and the most representative genera of Odonata, Anisoptera at Água Boa and Perobão Streams, Iguatemi River basin, Brazil. Both are first order streams with similar length that are impacted by riparian forest removal and silting. Quarterly samplings were conducted from March to December 2008 in the upper, intermediate and lower stretch of each stream. The Mantel test was used to check the influence of spatial autocorrelation on the Odonata composition. Spatial variations in the composition were summarized by the Principal Coordinates Analysis (PCoA) using Mantel test residuals. The effects of spatial correlation on richness and abundance were investigated by the spatial correlogram of Moranʼs I coefficients. The most representative genera in each stream were identified by the Indicator Value Method. The spatial variations in the attributes of the assemblages were assessed using analysis of variance of null models. We collected 500 immature individuals of 23 genera and three families. Among the attributes analyzed only the composition and abundance showed significant spatial differences, with the highest mean abundance found in the Perobão Stream. Miathyria and Zenithoptera were the indicator genera of the Água Boa Stream and Erythrodiplax, Libellula, Macrothemis, Progomphus and Tramea were the indicator genera of the Perobão Stream.

Analysis and estimative of schistosomiasis prevalence for the state of Minas Gerais, Brazil, using multiple regression with social and environmental spatial data

The aim of this work is to establish a relationship between schistosomiasis prevalence and social-environmental variables, in the state of Minas Gerais, Brazil, through multiple linear regression. The final regression model was established, after a variables selection phase, with a set of spatial variables which contains the summer minimum temperature, human development index, and vegetation type variables. Based on this model, a schistosomiasis risk map was built for Minas Gerais.

Spatial distribution of Schistosoma mansoni infection before and after chemotherapy with two praziquantel doses in a community of Pernambuco, Brazil

Praziquantel chemotherapy has been the focus of the Schistosomiasis Control Program in Brazil for the past two decades. Nevertheless, information on the impact of selective chemotherapy against Schistosoma mansoni infection under the conditions confronted by the health teams in endemic municipalities remains scarce. This paper compares the spatial pattern of infection before and after treatment with either a 40 mg/kg or 60 mg/kg dose of praziquantel by determining the intensity of spatial cluster among patients at 180 and 360 days after treatment. The spatial-temporal distribution of egg-positive patients was analysed in a Geographic Information System using the kernel smoothing technique. While all patients became egg-negative after 21 days, 17.9% and 30.9% reverted to an egg-positive condition after 180 and 360 days, respectively. Both the prevalence and intensity of infection after treatment were significantly lower in the 60 mg/kg than in the 40 mg/kg treatment group. The higher intensity of the kernel in the 40 mg/kg group compared to the 60 mg/kg group, at both 180 and 360 days, reflects the higher number of reverted cases in the lower dose group. Auxiliary, preventive measures to control transmission should be integrated with chemotherapy to achieve a more enduring impact.

Spatial variability of the chemical, physical and biological properties in lowland cultivated with irrigated rice

In the areas where irrigated rice is grown in the south of Brazil, few studies have been carried out to investigate the spatial variability structure of soil properties and to establish new forms of soil management as well as determine soil corrective and fertilizer applications. In this sense, this study had the objective of evaluating the spatial variability of chemical, physical and biological soil properties in a lowland area under irrigated rice cultivation in the conventional till system. For this purpose, a 10 x 10 m grid of 100 points was established, in an experimental field of the Embrapa Clima Temperado, in the County of Capão do Leão, State of Rio Grande do Sul. The spatial variability structure was evaluated by geostatistical tools and the number of subsamples required to represent each soil property in future studies was calculated using classical statistics. Results showed that the spatial variability structure of sand, silt, SMP index, cation exchange capacity (pH 7.0), Al3+ and total N properties could be detected by geostatistical analysis. A pure nugget effect was observed for the nutrients K, S and B, as well as macroporosity, mean weighted diameter of aggregates, and soil water storage. The cross validation procedure, based on linear regression and the determination coefficient, was more efficient to evaluate the quality of the adjusted mathematical model than the degree of spatial dependence. It was also concluded that the combination of classical with geostatistics can in many cases simplify the soil sampling process without losing information quality.

Spatial variability of soil chemical properties after coffee tree removal

Assessing the spatial variability of soil chemical properties has become an important aspect of soil management strategies with a view to higher crop yields with minimal environmental degradation. This study was carried out at the Centro Experimental of the Instituto Agronomico, in Campinas, São Paulo, Brazil. The aim was to characterize the spatial variability of chemical properties of a Rhodic Hapludox on a recently bulldozer-cleaned area after over 30 years of coffee cultivation. Soil samples were collected in a 20 x 20 m grid with 36 sampling points across a 1 ha area in the layers 0.0-0.2 and 0.2-0.4 m to measure the following chemical properties: pH, organic matter, K+, P, Ca2+, Mg2+, potential acidity, NH4-N, and NO3-N. Descriptive statistics were applied to assess the central tendency and dispersion moments. Geostatistical methods were applied to evaluate and to model the spatial variability of variables by calculating semivariograms and kriging interpolation. Spatial dependence patterns defined by spherical model adjusted semivariograms were made for all cited soil properties. Moderate to strong degrees of spatial dependence were found between 31 and 60 m. It was still possible to map soil spatial variability properties in the layers 0-20 cm and 20-40 cm after plant removal with bulldozers.

Pedotransfer functions related to spatial variability of water retention attributes for lowland soils

The estimation of non available soil variables through the knowledge of other related measured variables can be achieved through pedotransfer functions (PTF) mainly saving time and reducing cost. Great differences among soils, however, can yield non desirable results when applying this method. This study discusses the application of developed PTFs by several authors using a variety of soils of different characteristics, to evaluate soil water contents of two Brazilian lowland soils. Comparisons are made between PTF evaluated data and field measured data, using statistical and geostatistical tools, like mean error, root mean square error, semivariogram, cross-validation, and regression coefficient. The eight tested PTFs to evaluate gravimetric soil water contents (Ug) at the tensions of 33 kPa and 1,500 kPa presented a tendency to overestimate Ug 33 kPa and underestimate Ug1,500 kPa. The PTFs were ranked according to their performance and also with respect to their potential in describing the structure of the spatial variability of the set of measured values. Although none of the PTFs have changed the distribution pattern of the data, all resulted in mean and variance statistically different from those observed for all measured values. The PTFs that presented the best predictive values of Ug33 kPa and Ug1,500 kPa were not the same that had the best performance to reproduce the structure of spatial variability of these variables.

SPATIAL UNCERTAINTY OF NUTRIENT LOSS BY EROSION IN SUGARCANE HARVESTING SCENARIOS

The assessment of spatial uncertainty in the prediction of nutrient losses by erosion associated with landscape models is an important tool for soil conservation planning. The purpose of this study was to evaluate the spatial and local uncertainty in predicting depletion rates of soil nutrients (P, K, Ca, and Mg) by soil erosion from green and burnt sugarcane harvesting scenarios, using sequential Gaussian simulation (SGS). A regular grid with equidistant intervals of 50 m (626 points) was established in the 200-ha study area, in Tabapuã, São Paulo, Brazil. The rate of soil depletion (SD) was calculated from the relation between the nutrient concentration in the sediments and the chemical properties in the original soil for all grid points. The data were subjected to descriptive statistical and geostatistical analysis. The mean SD rate for all nutrients was higher in the slash-and-burn than the green cane harvest scenario (Student’s t-test, p<0.05). In both scenarios, nutrient loss followed the order: Ca>Mg>K>P. The SD rate was highest in areas with greater slope. Lower uncertainties were associated to the areas with higher SD and steeper slopes. Spatial uncertainties were highest for areas of transition between concave and convex landforms.

Spatial statistical analysis and selection of genotypes in plant breeding

The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.

Spatial variability of yield and other parameters associated with pear trees

In the last few years, precision agriculture has become commonly used with many crops, particularly cereals, and there is also interest in precision horticulture. Pear is a seasonal fruit and well appreciated by Brazilian people, although it is mostly imported. Brazilian farmers are nowadays trying to increase pear production. Thus, this research aimed at mapping the yield of pear trees in order to study the spatial variability of yield as well as its comparison with spatial variability of soil and plant attributes. The experimental field had 146 pear trees, variety 'Pêra d'água', distributed on a 1.24 ha. Four harvests were performed according to the fruit ripening and from each tree; only the ripe fruits were harvested. In each harvest, all the fruits were weighed and the total yield was obtained based on the sum of each harvest. The soil attributes analyzed were P, K, Ca, Mg, pH in CaCl2, C, Cu, Zn, Fe, Mn and base saturation, and the plant attributes were fruit length, diameter and yield. Yield had low correlation with soil and plant attributes. An index of spatial variability was suggested in this study and helped in classifying levels of spatial dependence of the various soil and plant attributes: very low (fruit length); low (P, fruit diameter), medium (Mg, pH, Cu, Zn, Fe), high (Ca, K, base saturation and yield), and very high (Mn and C).

Spatial autocorrelation of ndvi and gvi indices derived from landsat/tm images for soybean crops in the western of the state of Paraná in 2004/2005 crop season

This research aims at studying spatial autocorrelation of Landsat/TM based on normalized difference vegetation index (NDVI) and green vegetation index (GVI) of soybean of the western region of the State of Paraná. The images were collected during the 2004/2005 crop season. The data were grouped into five vegetation index classes of equal amplitude, to create a temporal map of soybean within the crop cycle. Moran I and Local Indicators of Spatial Autocorrelation (LISA) indices were applied to study the spatial correlation at the global and local levels, respectively. According to these indices, it was possible to understand the municipality-based profiles of tillage as well as to identify different sowing periods, providing important information to producers who use soybean yield data in their planning.

Spatial genetic structure within natural populations of Machaerium villosum Vog. (Leguminosae) at Moji-Guaçu region, SP, Brazil

A spatial autocorrelation study of enzyme loci detected by starch gel electrophoresis was performed to verify the occurrence of spatial genetic structure within two natural populations of Machaerium villosum Vog. The sampled populations were termed "Antropic Model (MA)" and "Natural Model (MN)" and they are situated in Campininha Farm areas, at Moji-Guaçu municipality, 22°10'43''-22°18'19'' S and 47°8'5"-47°11'34" W, in the state of São Paulo. Ten polymorphic loci in the MA population and nine polymorphic loci in the MN population were assessed by Moran's I autocorrelation statistic. No spatial autocorrelation was detected among individuals within sampled populations. Results are in line with other studies in woody species from tropical rain forest.

Ecological distribution of stream macroalgae in different spatial scales using taxonomic and morphological groups

We examined the ecological distribution of macroalgal communities in streams using species groups (taxonomic units = algal phyla, and morphological = morphological types) with similar structures and functions instead of the species themselves. The study was conducted from June to July/2007 in two drainage basins located in mid-southern region of Paraná State , Brazil. Evaluations of macroalgal communities took into consideration the following spatial scales: the drainage basin (the Pedras river and Marrecas river basins), shading regime (open and shaded stream segments), mesohabitats (riffles and pools), and microhabitats (sampling units of 0.05m2). A total of 29 taxa (23 subgeneric, one generic, and five vegetative groups) were identified. On these, 12 taxa belong to Chlorophyta, 11 to Cyanobacteria, four to Heterokontophyta, and two to Rhodophyta. The proportions of morphological types were: 24% free filaments, 17.25% mats, tufts, gelatinous colonies, and gelatinous filaments, 7% crusts. In terms of spatial scales, we observed a predominance of Chlorophyta in open stream segments and Cyanobacteria in shaded stream segments, reflecting the loss of competitive advantage of green algae in sites with low energy availability. In the mesohabitats, the morphological types recorded in pools were predominantly poorly adapted to fast currents (free filaments), while those found in riffles (mats, tufts and gelatinous filaments) were highly resistant to fast water flows. As such, the use of species groupings based on algal taxonomy associated with morphological characteristics proved to be useful to understanding the distributions of these organisms in lotic environments.

The modulation of simple reaction time by the spatial probability of a visual stimulus

Simple reaction time (SRT) in response to visual stimuli can be influenced by many stimulus features. The speed and accuracy with which observers respond to a visual stimulus may be improved by prior knowledge about the stimulus location, which can be obtained by manipulating the spatial probability of the stimulus. However, when higher spatial probability is achieved by holding constant the stimulus location throughout successive trials, the resulting improvement in performance can also be due to local sensory facilitation caused by the recurrent spatial location of a visual target (position priming). The main objective of the present investigation was to quantitatively evaluate the modulation of SRT by the spatial probability structure of a visual stimulus. In two experiments the volunteers had to respond as quickly as possible to the visual target presented on a computer screen by pressing an optic key with the index finger of the dominant hand. Experiment 1 (N = 14) investigated how SRT changed as a function of both the different levels of spatial probability and the subject's explicit knowledge about the precise probability structure of visual stimulation. We found a gradual decrease in SRT with increasing spatial probability of a visual target regardless of the observer's previous knowledge concerning the spatial probability of the stimulus. Error rates, below 2%, were independent of the spatial probability structure of the visual stimulus, suggesting the absence of a speed-accuracy trade-off. Experiment 2 (N = 12) examined whether changes in SRT in response to a spatially recurrent visual target might be accounted for simply by sensory and temporally local facilitation. The findings indicated that the decrease in SRT brought about by a spatially recurrent target was associated with its spatial predictability, and could not be accounted for solely in terms of sensory priming.

Spatial variability of soil fertility and its relationship with seed physiological potential in a soybean production area

The correlation of soil fertility x seed physiological potential is very important in the area of seed technology but results published with that theme are contradictory. For this reason, this study to evaluate the correlations between soil chemical properties and physiological potential of soybean seeds. On georeferenced points, both soil and seeds were sampled for analysis of soil fertility and seed physiological potential. Data were assessed by the following analyses: descriptive statistics; Pearson's linear correlation; and geostatistics. The adjusted parameters of the semivariograms were used to produce maps of spatial distribution for each variable. Organic matter content, Mn and Cu showed significant effects on seed germination. Most variables studied presented moderate to high spatial dependence. Germination and accelerated aging of seeds, and P, Ca, Mg, Mn, Cu and Zn showed a better fit to spherical semivariogram: organic matter, pH and K had a better fit to Gaussian model; and V% and Fe showed a better fit to the linear model. The values for range of spatial dependence varied from 89.9 m for P until 651.4 m for Fe. These values should be considered when new samples are collected for assessing soil fertility in this production area.