The attenuation of concentrations model: a new method for assessing mercury mobility in sediments

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).

Distribuição de metais pesados em sedimentos do sistema estuarino da Ilha de Vitória-ES

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.

O impacto industrial na composição química das águas subterrâneas com enfoque de consumo humano (Rio Grande, RS)

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.

Marcadores metálicos como avaliação do impacto crônico de emissões petroquímicas em zona urbana

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.

Natural regeneration in abandoned fields following intensive agricultural land use in an Atlantic Forest Island, Brazil

The time required to regrowth a forest in degraded areas depends on how the forest is removed and on the type of land use following removal. Natural regeneration was studied in abandoned old fields after intensive agricultural land use in areas originally covered by Brazilian Atlantic Forests of the Anchieta Island, Brazil in order to understand how plant communities reassemble following human disturbances as well as to determine suitable strategies of forest restoration. The fields were classified into three vegetation types according to the dominant plant species in: 1) Miconia albicans (Sw.) Triana (Melastomataceae) fields, 2) Dicranopteris flexuosa (Schrader) Underw. (Gleicheniaceae) thickets, and 3) Gleichenella pectinata (Willd.) Ching. (Gleicheniaceae) thickets. Both composition and structure of natural regeneration were compared among the three dominant vegetation types by establishing randomly three plots of 1 x 3 m in five sites of the island. A gradient in composition and abundance of species in natural regeneration could be observed along vegetation types from Dicranopteris fern thickets to Miconia fields. The gradient did not accurately follow the pattern of spatial distribution of the three dominant vegetation types in the island regarding their proximity of the remnant forests. A complex association of biotic and abiotic factors seems to be affecting the seedling recruitment and establishment in the study plots. The lowest plant regeneration found in Dicranopteris and Gleichenella thickets suggests that the ferns inhibit the recruitment of woody and herbaceous species. Otherwise, we could not distinguish different patterns of tree regeneration among the three vegetation types. Our results showed that forest recovery following severe anthropogenic disturbances is not direct, predictable or even achievable on its own. Appropriated actions and methods such as fern removal, planting ground covers, and enrichment planting with tree species were suggested in order to restore the natural forest regeneration process in the abandoned old fields.

Using aster multispectral imagery for mapping woody invasive species in pico da vara natural reserve (Azores Islands, Portugal)

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.

Soil penetration resistance analysis by multivariate and geostatistical methods

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.

Technical evaluation of artificial ligthing systems for broiler houses

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.

Soybean yield maps using regular and optimized sample with different configurations by simulated annealing

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.

Spatialization of climate, physical and socioeconomic factors that affect the dairy goat production in Brazil and their impact on animal breeding decisions

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.

Phytosociological variability of weeds in soybean field

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.

Weed mapping using techniques of precision agriculture

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.

Climate, soil and tree flora relationships in forests in the state of São Paulo, southeastern Brasil

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.

Phenology, fruit set and dispersal of Cordia multispicata Cham., an important weed shrub of abandoned pastures in eastern Amazonia

ABSTRACT - (Phenology, fruit set and dispersal of Cordia multispicata Cham., an important weed shrub of abandoned pastures in eastern Amazonia). The reproductive ecology of the distylous tropical shrub Cordia multispicata was studied in an abandoned pasture in Paragominas County , Pará state, Brazil. It is a common species in the Amazon basin where it occurs as a weed in open and disturbed habitats. C. multispicata has many flowers per inflorescence (85 ± 12) but 84% abort before fertilization. Flowering occurs throughout the year. Fruits are small, with a red fleshy pericarp (skin-pulp) attractive to birds. Fruit set is lower during the dry season (less than 30%) and higher during the rainy season when there are many visits of insects to the flowers. Fruiting has a peak between the end of the dry season and the middle of the rainy season. Nineteen bird species were observed foraging for the fruits of C. multispicata, and 79% of those species can be considered as potential dispersal agents. The efficient seed dispersal and aggregated spatial distribution associated with some characteristics of the dispersors greatly contributed to the success of this species in abandoned pastures of eastern Amazonia.

Biomass and chemical composition of Nitella furcata subsp. mucronata var. mucronata f. oligospira (A. Braun) R. D. Wood (Chlorophyta, Characeae) in the littoral region of Ninféias Pond, São Paulo, Southeast Brazil

Temporal variation of Nitella furcata (Roxburgh ex Bruzelius) C. Agardh emend. R. D. Wood subsp. mucronata (A. Braun) R. D. Wood var. mucronata f. oligospira (A. Braun) R. D. Wood biomass and chemical composition were studied at the Ninféias Pond (23°38'18.9" S, 46°37'16.3" W), a mesotrophic reservoir located in the Parque Estadual das Fontes do Ipiranga Biological Reserve, Municipality of São Paulo, Southeast Brazil. Plants were collected monthly from October 1996 to October 1997 at three fixed stations of reservoir's littoral region. Charophyte biomass spatial distribution pattern did not vary significantly throughout the study period at all sampling stations. As to seasonal variation, the highest average values of the total alga biomass (98.35-266.06 g m-2 DW) were registered during the rainy season, whereas lowest values (48.86-170.56 g m-2 DW) were in the dry season. P values varied from 23.8 to 225.2 mg m-2 and C from 139 to 353 mg m-2. During the rainy season, greatest air and water temperature, rain precipitation, turbidity and dissolved inorganic nitrogen values were measured, constituting the best conditions for charophyte growth. Water temperature and nutrient availability in the reservoir played a decisive role towards growth and accumulation of algal biomass.